SYSTEM AND METHOD FOR ACQUIRING OF STATIC IMAGES OF OBJECTS IN MOTION
•Download as PPTX, PDF•
1 like•46 views
This invention provides a system and method for acquiring static side images of vehicles in motion using video surveillance cameras along toll roads. The system detects vehicles in motion in video frames and stitches together relevant frames to create a single static image of each vehicle as it passes. This allows toll road operators to photograph vehicles for identification and monitoring purposes, without needing direct access or space alongside the road for stationary cameras. The invention is intended to assist toll road operators in Brazil with maintaining traffic order and vehicle supervision on highways.
Report
Share
Report
Share
Recommended
Robust Block-Matching Motion Estimation of Flotation Froth Using Mutual Infor...
This document presents a new method for estimating motion in flotation froth images using mutual information as the similarity metric. It proposes using mutual information with a bin size of two (MI2) for block matching motion estimation of froth images. The paper finds that MI2 improves motion estimation accuracy in terms of peak signal-to-noise ratio compared to the commonly used mean absolute difference (MAD) metric, while having a similar computational cost. It tests the MI2 method on two froth video sequences using three-step search and new three-step search, and finds MI2 yields slightly better reconstructed image quality than MAD according to PSNR measurements.
Introduction to Optial Flow
This document provides a short introduction to the optical flow problem. After explaining the basics, we go through different basic approaches.
System and method for motion compensation
The document describes a system and method for motion compensation that transforms a reference picture to a current picture for improved compression efficiency. It uses redacted tools to select the best practices for motion compensation by comparing differences between frames and determining transformations from prior motion compensated data. The system includes redacted tools comprising various redacted components and a redacted processor.
Block Matching Project
This document summarizes the block matching based motion estimation algorithm. The algorithm estimates motion between two frames by comparing blocks in the reference frame to blocks in the target frame. It discusses key parameters like block size, search window, and matching criteria. Experimental results on example images demonstrate how varying these parameters affects the motion fields and computation time. The best results were found with a block size of 16x16, search window of 16, and threshold of 1.7.
A Comparison of Block-Matching Motion Estimation Algorithms
A Comparison of Block-Matching Motion Estimation AlgorithmsMultimedia and Vision Laboratory at Universidad del Valle
This document compares different block-matching motion estimation algorithms. It introduces block-matching motion estimation and describes popular distortion metrics like MSE and SAD. It then explains the full-search algorithm and more efficient algorithms like three-step search and four-step search that evaluate fewer candidate blocks to reduce computational cost. These algorithms are evaluated and compared using video test sequences to analyze their performance and quality.The motion estimation
Introduction to Digital Videos, Motion Estimation: Principles & Compensation. Learn more in IIT Kharagpur's Image and Video Communication online certificate course.
Curved Wavelet Transform For Image Denoising using MATLAB.
This document summarizes a student project on image denoising using wavelet analysis. It introduces wavelet transforms as a method to denoise digital images corrupted by noise. The project uses MATLAB to apply a discrete wavelet transform with a Haar wavelet, thresholds wavelet coefficients at different levels to compress and denoise the image, and demonstrates the results on an example image.
Dip review
The document discusses digital image processing and provides an overview of key concepts. It defines digital and analog images and explains how digital images are represented by pixels. It outlines fundamental steps in digital image processing like image acquisition, enhancement, restoration, morphological processing, segmentation, representation, compression and object recognition. It also discusses applications in areas like remote sensing, medical imaging, film and video effects.
Recommended
Robust Block-Matching Motion Estimation of Flotation Froth Using Mutual Infor...
This document presents a new method for estimating motion in flotation froth images using mutual information as the similarity metric. It proposes using mutual information with a bin size of two (MI2) for block matching motion estimation of froth images. The paper finds that MI2 improves motion estimation accuracy in terms of peak signal-to-noise ratio compared to the commonly used mean absolute difference (MAD) metric, while having a similar computational cost. It tests the MI2 method on two froth video sequences using three-step search and new three-step search, and finds MI2 yields slightly better reconstructed image quality than MAD according to PSNR measurements.
Introduction to Optial Flow
This document provides a short introduction to the optical flow problem. After explaining the basics, we go through different basic approaches.
System and method for motion compensation
The document describes a system and method for motion compensation that transforms a reference picture to a current picture for improved compression efficiency. It uses redacted tools to select the best practices for motion compensation by comparing differences between frames and determining transformations from prior motion compensated data. The system includes redacted tools comprising various redacted components and a redacted processor.
Block Matching Project
This document summarizes the block matching based motion estimation algorithm. The algorithm estimates motion between two frames by comparing blocks in the reference frame to blocks in the target frame. It discusses key parameters like block size, search window, and matching criteria. Experimental results on example images demonstrate how varying these parameters affects the motion fields and computation time. The best results were found with a block size of 16x16, search window of 16, and threshold of 1.7.
A Comparison of Block-Matching Motion Estimation Algorithms
A Comparison of Block-Matching Motion Estimation AlgorithmsMultimedia and Vision Laboratory at Universidad del Valle
This document compares different block-matching motion estimation algorithms. It introduces block-matching motion estimation and describes popular distortion metrics like MSE and SAD. It then explains the full-search algorithm and more efficient algorithms like three-step search and four-step search that evaluate fewer candidate blocks to reduce computational cost. These algorithms are evaluated and compared using video test sequences to analyze their performance and quality.The motion estimation
Introduction to Digital Videos, Motion Estimation: Principles & Compensation. Learn more in IIT Kharagpur's Image and Video Communication online certificate course.
Curved Wavelet Transform For Image Denoising using MATLAB.
This document summarizes a student project on image denoising using wavelet analysis. It introduces wavelet transforms as a method to denoise digital images corrupted by noise. The project uses MATLAB to apply a discrete wavelet transform with a Haar wavelet, thresholds wavelet coefficients at different levels to compress and denoise the image, and demonstrates the results on an example image.
Dip review
The document discusses digital image processing and provides an overview of key concepts. It defines digital and analog images and explains how digital images are represented by pixels. It outlines fundamental steps in digital image processing like image acquisition, enhancement, restoration, morphological processing, segmentation, representation, compression and object recognition. It also discusses applications in areas like remote sensing, medical imaging, film and video effects.
Image denoising
This document discusses image denoising techniques. It begins by defining image denoising as removing unwanted noise from an image to restore the original signal. It then discusses several types of noise like additive Gaussian noise, impulse noise, uniform noise, and periodic noise. For denoising, it covers spatial domain techniques like linear filters (mean, weighted mean), non-linear filters (median filter), and frequency domain techniques that apply a low-pass filter to the Fourier transform of the noisy image. The document provides examples of denoising noisy images using mean and median filters to remove different types of noise.
final_project
This document is a project report on noise reduction in images using filters. It was submitted by 4 students - Priya M, Dondla Leela Vasundhara, Inderpreet Kaur, and Nisha Mathew - to the Department of Computer Science at Mount Carmel College in Bengaluru, India. The report discusses image processing techniques including different types of noise, noise reduction methods, and the use of filters to reduce noise in digital images.
digital image processing, image processing
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Image denoising algorithms
The document discusses various image denoising algorithms. It defines image denoising as removing noise from an image. Common denoising algorithms discussed include spatial domain filters like Gaussian filtering, anisotropic filtering, and total variation minimization. Neighborhood filtering and non-local means (NL-means) are also summarized. Gaussian filtering blurs edges and textures while anisotropic filtering degrades flat and texture regions. Total variation minimization can oversmooth textures. Neighborhood filtering is not robust to noisy pixel values. In contrast, NL-means compares neighborhood configurations and is more robust than neighborhood filtering alone.
digital image processing
1) Digital image processing involves processing digital images using computer software and algorithms. It includes techniques like image enhancement, restoration, compression, and segmentation.
2) The key stages in digital image processing are image acquisition, enhancement, restoration, morphological processing, segmentation, object recognition, representation and description, compression, and color image processing.
3) Digital image processing has various applications including medical imaging, space exploration, document processing, photography, remote sensing, and video/film special effects. It covers almost the entire electromagnetic spectrum from gamma to radio waves.
Image denoising
The document discusses image denoising techniques based on partial differential equations (PDEs). It begins by defining image noise and describing conventional denoising filters like averaging and median filters. It then focuses on diffusion-based denoising methods, particularly the influential 1987 work of Perona and Malik which introduced nonlinear anisotropic diffusion. Their approach uses an edge-stopping function to reduce diffusion near edges. The document outlines linear and nonlinear diffusion models, conditions for the diffusion coefficient function, and extensions of the Perona-Malik model. It summarizes a 2014 paper proposing a robust anisotropic diffusion scheme using novel variants of the edge-stopping function and diffusivity parameter computation.
Real time image processing ppt
This document provides an overview of real-time image processing. It begins with introducing real-time image processing and how it differs from ordinary image processing by having deadlines and predictable response times. The document then discusses the requirements for a real-time image processing system including high resolution video input, low latency, and high processing performance. It also covers applications such as mobile robots and human-computer interaction. In the end, it provides definitions of real-time image processing in both the perceptual and signal processing senses.
Introduction to Digital Image Processing Using MATLAB
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
Project Proposal Project Proposal Project Proposal Project Proposal
The document discusses a system to detect motorcyclists wearing helmets and capture vehicle license plates if they are not wearing a helmet using YOLO v7. The system takes video frames as input and outputs the license plate of any motorcyclist detected without a helmet. It uses data preprocessing, model implementation including object detection, and outputs the results of helmet detection and license plate detection within boundary boxes. The proposed system aims to automatically detect violations and enforce traffic safety regulations in real-time.
Real Time Object Identification for Intelligent Video Surveillance Applications
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
IRJET- Reckoning the Vehicle using MATLAB
This document discusses a method for vehicle detection and counting using MATLAB. It begins with an introduction describing the need for automated vehicle counting systems. It then reviews existing vehicle detection methods and their limitations. The proposed method uses background subtraction to detect vehicles in video frames. Vehicles are tracked across frames, segmented from other objects, and counted. The algorithm involves taking the first frame as the background, subtracting subsequent frames to find differences (moving vehicles), processing and segmenting images, tuning vehicle boundaries, and incrementing a count when new vehicles are detected. Pseudocode and data flow diagrams illustrate the process. Test video input and output showing detected vehicles in bounding boxes is presented. The method provides an efficient way to automatically count vehicles for
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
This document summarizes and compares different approaches for vehicle traffic analysis, including edge detection, background subtraction, blob detection, and the YOLO convolutional neural network approach. It finds that while earlier approaches have advantages for daytime use, YOLO provides more accurate real-time analysis of traffic by detecting stationary and moving vehicles with fewer errors related to illumination or occlusion. YOLO analyzes entire frames simultaneously for faster processing while maintaining precision.
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
The document summarizes various approaches used for vehicle traffic analysis and their pros and cons. It discusses traditional sensor-based methods like magnetic loops and infrared sensors which are prone to damage. It also examines earlier computer vision techniques like edge detection, background subtraction, and blob detection that have limitations in accuracy and handling occlusion. The document proposes using a convolutional neural network model called YOLO for real-time vehicle detection and counting from video. YOLO can process each video frame once to generate bounding boxes and counts, balancing speed and accuracy. It aims to provide more reliable analysis across different traffic and lighting conditions.
Imagus_Whitepaper_250515
Dr. Brian Lovell discusses emerging trends in face recognition technology that could help with security screening. He describes challenges with current automated border screening using facial verification and the need for more accurate face recognition of non-cooperative individuals in video streams. The document outlines Imagus Technology's approach to developing face recognition algorithms that can rapidly and reliably match low-quality images from surveillance cameras in real-time, which could help with challenges in border security and video surveillance more broadly.
Imagus_Whitepaper_250515
Dr. Brian Lovell discusses emerging trends in video surveillance and face recognition technology. He describes how Imagus has developed a non-cooperative face recognition technology that can identify individuals from video in real-time, even when images are of low quality or the individuals are not cooperating. This technology has applications in airport security, access control, social media monitoring, and more. It leverages techniques like hardware acceleration and GPU processing to enable real-time matching of faces across hundreds of cameras.
IRJET - Pothole Detection System
This document describes a pothole detection system using a Raspberry Pi, camera, and image processing algorithms. The system works by using a camera to capture video of the road surface. The video is converted to frames and each frame is converted to grayscale. Edge detection is then performed on the grayscale images. Potholes are identified by analyzing the edges in the images using techniques like morphological operations and thresholding. The system is able to detect potholes in real-time and could provide warnings to drivers about upcoming potholes to help avoid accidents.
Identification and classification of moving vehicles on road
This document describes a system for automatically identifying and classifying vehicles in traffic video. The system uses image processing and machine learning techniques. Video frames are first processed to detect vehicles by subtracting background images. Features like width, length, area, and perimeter are then extracted from vehicle images. These features are input to a neural network classifier trained on sample vehicle data to classify vehicles as big or small. The system was tested on real traffic video from Saudi Arabia. It aims to automate traffic monitoring and reduce costs compared to manual methods.
Smart Parking Solution using Camera Networks and Real-time Computer Vision
This document proposes a smart parking solution using computer vision and AI techniques applied to existing surveillance camera footage. The system would detect vacant parking spots, identify vehicle license plates, detect collisions, and track parking durations to calculate fees. It would provide real-time parking information and status updates to drivers via a mobile app. The system would use deep learning models like YOLOv5 trained on labeled camera images to perform tasks like license plate recognition and space availability detection without additional hardware. This could help optimize urban parking infrastructure and reduce traffic compared to alternative IoT-based approaches.
IRJET- Vehicle Seat Vacancy Identification using Image Processing Technique
This document describes a system that uses image processing techniques on images captured by a webcam installed in a vehicle to detect passengers' faces and estimate the number of passengers and seat vacancy. The system first captures images of the passenger area and sends them to a server. It then uses techniques like morphological operations, CLAHE, and Haar classifiers for face detection. Features are extracted using LBP and HOG, and an SVM classifies images to estimate passengers' gender. Experimental results show the system can accurately detect faces and estimate numbers even from low quality images, providing real-time vacancy information to help passengers plan their travel.
A017430110
1) The document proposes techniques for real-time Indian road analysis using image processing and computer vision, including lane detection, pothole detection, object detection from video, and road sign classification.
2) It discusses using the Hough transform for lane detection, color segmentation and shape modeling with thin spline transformation for road sign classification, and k-means clustering for pothole detection.
3) The techniques are tested on images and video streams from Indian roads to show they can be used for real-time analysis in an automated driver guidance system.
An Overview of Parking Slot Detection Techniques
The aim of this study is to design and implement an automatic parking system to increase parking usability and safety and to collect parking fees for vehicles without having to use a magnetic card. A clever car park system can work with fewer human connections and does not need a magnetic card. There is also a parking assistance system that can advise and guide the user to the correct car park. In order to detect the number plates for the parking and payment system, the system used image processing. In general, the systems use pre programmed controls to ensure that at least one person is involved in the parking system and control access to restricted areas. Ashu Yadav | Kirti Bhatia | Rohini Sharma "An Overview of Parking Slot Detection Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd46321.pdf Paper URL: https://www.ijtsrd.com/computer-science/realtime-computing/46321/an-overview-of-parking-slot-detection-techniques/ashu-yadav
Pothole Detection Using ML and DL Algorithms
The document presents an integrated approach for pothole detection and classification using computer vision and machine learning techniques. Specifically, it uses YOLOv7 for object detection, SVM for classification, and image segmentation. A web application is also developed using Streamlit to provide an intuitive interface for users to upload images and view detection results. The methodology section describes data collection and preprocessing, model training and testing using YOLOv7 and SVM, pothole detection through these deep learning models, and image segmentation techniques. The results section shows outputs of edge detection, segmentation, bounding box detection through YOLOv7, and SVM classification accuracy. The proposed approach aims to help authorities identify problematic road areas efficiently.
More Related Content
Viewers also liked
Image denoising
This document discusses image denoising techniques. It begins by defining image denoising as removing unwanted noise from an image to restore the original signal. It then discusses several types of noise like additive Gaussian noise, impulse noise, uniform noise, and periodic noise. For denoising, it covers spatial domain techniques like linear filters (mean, weighted mean), non-linear filters (median filter), and frequency domain techniques that apply a low-pass filter to the Fourier transform of the noisy image. The document provides examples of denoising noisy images using mean and median filters to remove different types of noise.
final_project
This document is a project report on noise reduction in images using filters. It was submitted by 4 students - Priya M, Dondla Leela Vasundhara, Inderpreet Kaur, and Nisha Mathew - to the Department of Computer Science at Mount Carmel College in Bengaluru, India. The report discusses image processing techniques including different types of noise, noise reduction methods, and the use of filters to reduce noise in digital images.
digital image processing, image processing
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Image denoising algorithms
The document discusses various image denoising algorithms. It defines image denoising as removing noise from an image. Common denoising algorithms discussed include spatial domain filters like Gaussian filtering, anisotropic filtering, and total variation minimization. Neighborhood filtering and non-local means (NL-means) are also summarized. Gaussian filtering blurs edges and textures while anisotropic filtering degrades flat and texture regions. Total variation minimization can oversmooth textures. Neighborhood filtering is not robust to noisy pixel values. In contrast, NL-means compares neighborhood configurations and is more robust than neighborhood filtering alone.
digital image processing
1) Digital image processing involves processing digital images using computer software and algorithms. It includes techniques like image enhancement, restoration, compression, and segmentation.
2) The key stages in digital image processing are image acquisition, enhancement, restoration, morphological processing, segmentation, object recognition, representation and description, compression, and color image processing.
3) Digital image processing has various applications including medical imaging, space exploration, document processing, photography, remote sensing, and video/film special effects. It covers almost the entire electromagnetic spectrum from gamma to radio waves.
Image denoising
The document discusses image denoising techniques based on partial differential equations (PDEs). It begins by defining image noise and describing conventional denoising filters like averaging and median filters. It then focuses on diffusion-based denoising methods, particularly the influential 1987 work of Perona and Malik which introduced nonlinear anisotropic diffusion. Their approach uses an edge-stopping function to reduce diffusion near edges. The document outlines linear and nonlinear diffusion models, conditions for the diffusion coefficient function, and extensions of the Perona-Malik model. It summarizes a 2014 paper proposing a robust anisotropic diffusion scheme using novel variants of the edge-stopping function and diffusivity parameter computation.
Real time image processing ppt
This document provides an overview of real-time image processing. It begins with introducing real-time image processing and how it differs from ordinary image processing by having deadlines and predictable response times. The document then discusses the requirements for a real-time image processing system including high resolution video input, low latency, and high processing performance. It also covers applications such as mobile robots and human-computer interaction. In the end, it provides definitions of real-time image processing in both the perceptual and signal processing senses.
Introduction to Digital Image Processing Using MATLAB
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
Viewers also liked (8)
Introduction to Digital Image Processing Using MATLAB
Introduction to Digital Image Processing Using MATLAB
Similar to SYSTEM AND METHOD FOR ACQUIRING OF STATIC IMAGES OF OBJECTS IN MOTION
Project Proposal Project Proposal Project Proposal Project Proposal
The document discusses a system to detect motorcyclists wearing helmets and capture vehicle license plates if they are not wearing a helmet using YOLO v7. The system takes video frames as input and outputs the license plate of any motorcyclist detected without a helmet. It uses data preprocessing, model implementation including object detection, and outputs the results of helmet detection and license plate detection within boundary boxes. The proposed system aims to automatically detect violations and enforce traffic safety regulations in real-time.
Real Time Object Identification for Intelligent Video Surveillance Applications
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
IRJET- Reckoning the Vehicle using MATLAB
This document discusses a method for vehicle detection and counting using MATLAB. It begins with an introduction describing the need for automated vehicle counting systems. It then reviews existing vehicle detection methods and their limitations. The proposed method uses background subtraction to detect vehicles in video frames. Vehicles are tracked across frames, segmented from other objects, and counted. The algorithm involves taking the first frame as the background, subtracting subsequent frames to find differences (moving vehicles), processing and segmenting images, tuning vehicle boundaries, and incrementing a count when new vehicles are detected. Pseudocode and data flow diagrams illustrate the process. Test video input and output showing detected vehicles in bounding boxes is presented. The method provides an efficient way to automatically count vehicles for
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
This document summarizes and compares different approaches for vehicle traffic analysis, including edge detection, background subtraction, blob detection, and the YOLO convolutional neural network approach. It finds that while earlier approaches have advantages for daytime use, YOLO provides more accurate real-time analysis of traffic by detecting stationary and moving vehicles with fewer errors related to illumination or occlusion. YOLO analyzes entire frames simultaneously for faster processing while maintaining precision.
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
The document summarizes various approaches used for vehicle traffic analysis and their pros and cons. It discusses traditional sensor-based methods like magnetic loops and infrared sensors which are prone to damage. It also examines earlier computer vision techniques like edge detection, background subtraction, and blob detection that have limitations in accuracy and handling occlusion. The document proposes using a convolutional neural network model called YOLO for real-time vehicle detection and counting from video. YOLO can process each video frame once to generate bounding boxes and counts, balancing speed and accuracy. It aims to provide more reliable analysis across different traffic and lighting conditions.
Imagus_Whitepaper_250515
Dr. Brian Lovell discusses emerging trends in face recognition technology that could help with security screening. He describes challenges with current automated border screening using facial verification and the need for more accurate face recognition of non-cooperative individuals in video streams. The document outlines Imagus Technology's approach to developing face recognition algorithms that can rapidly and reliably match low-quality images from surveillance cameras in real-time, which could help with challenges in border security and video surveillance more broadly.
Imagus_Whitepaper_250515
Dr. Brian Lovell discusses emerging trends in video surveillance and face recognition technology. He describes how Imagus has developed a non-cooperative face recognition technology that can identify individuals from video in real-time, even when images are of low quality or the individuals are not cooperating. This technology has applications in airport security, access control, social media monitoring, and more. It leverages techniques like hardware acceleration and GPU processing to enable real-time matching of faces across hundreds of cameras.
IRJET - Pothole Detection System
This document describes a pothole detection system using a Raspberry Pi, camera, and image processing algorithms. The system works by using a camera to capture video of the road surface. The video is converted to frames and each frame is converted to grayscale. Edge detection is then performed on the grayscale images. Potholes are identified by analyzing the edges in the images using techniques like morphological operations and thresholding. The system is able to detect potholes in real-time and could provide warnings to drivers about upcoming potholes to help avoid accidents.
Identification and classification of moving vehicles on road
This document describes a system for automatically identifying and classifying vehicles in traffic video. The system uses image processing and machine learning techniques. Video frames are first processed to detect vehicles by subtracting background images. Features like width, length, area, and perimeter are then extracted from vehicle images. These features are input to a neural network classifier trained on sample vehicle data to classify vehicles as big or small. The system was tested on real traffic video from Saudi Arabia. It aims to automate traffic monitoring and reduce costs compared to manual methods.
Smart Parking Solution using Camera Networks and Real-time Computer Vision
This document proposes a smart parking solution using computer vision and AI techniques applied to existing surveillance camera footage. The system would detect vacant parking spots, identify vehicle license plates, detect collisions, and track parking durations to calculate fees. It would provide real-time parking information and status updates to drivers via a mobile app. The system would use deep learning models like YOLOv5 trained on labeled camera images to perform tasks like license plate recognition and space availability detection without additional hardware. This could help optimize urban parking infrastructure and reduce traffic compared to alternative IoT-based approaches.
IRJET- Vehicle Seat Vacancy Identification using Image Processing Technique
This document describes a system that uses image processing techniques on images captured by a webcam installed in a vehicle to detect passengers' faces and estimate the number of passengers and seat vacancy. The system first captures images of the passenger area and sends them to a server. It then uses techniques like morphological operations, CLAHE, and Haar classifiers for face detection. Features are extracted using LBP and HOG, and an SVM classifies images to estimate passengers' gender. Experimental results show the system can accurately detect faces and estimate numbers even from low quality images, providing real-time vacancy information to help passengers plan their travel.
A017430110
1) The document proposes techniques for real-time Indian road analysis using image processing and computer vision, including lane detection, pothole detection, object detection from video, and road sign classification.
2) It discusses using the Hough transform for lane detection, color segmentation and shape modeling with thin spline transformation for road sign classification, and k-means clustering for pothole detection.
3) The techniques are tested on images and video streams from Indian roads to show they can be used for real-time analysis in an automated driver guidance system.
An Overview of Parking Slot Detection Techniques
The aim of this study is to design and implement an automatic parking system to increase parking usability and safety and to collect parking fees for vehicles without having to use a magnetic card. A clever car park system can work with fewer human connections and does not need a magnetic card. There is also a parking assistance system that can advise and guide the user to the correct car park. In order to detect the number plates for the parking and payment system, the system used image processing. In general, the systems use pre programmed controls to ensure that at least one person is involved in the parking system and control access to restricted areas. Ashu Yadav | Kirti Bhatia | Rohini Sharma "An Overview of Parking Slot Detection Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd46321.pdf Paper URL: https://www.ijtsrd.com/computer-science/realtime-computing/46321/an-overview-of-parking-slot-detection-techniques/ashu-yadav
Pothole Detection Using ML and DL Algorithms
The document presents an integrated approach for pothole detection and classification using computer vision and machine learning techniques. Specifically, it uses YOLOv7 for object detection, SVM for classification, and image segmentation. A web application is also developed using Streamlit to provide an intuitive interface for users to upload images and view detection results. The methodology section describes data collection and preprocessing, model training and testing using YOLOv7 and SVM, pothole detection through these deep learning models, and image segmentation techniques. The results section shows outputs of edge detection, segmentation, bounding box detection through YOLOv7, and SVM classification accuracy. The proposed approach aims to help authorities identify problematic road areas efficiently.
IRJET- Time To Cross – Traffic Light Control System using Image Processing
This document describes a proposed smart traffic light control system using image processing. The system uses cameras installed at an intersection to capture images of vehicles and pedestrians. Image processing algorithms like cascade classification and histogram of oriented gradients are used to detect vehicles and pedestrians in the images and determine traffic density. Based on the detected densities, the system adjusts the timing of the traffic lights to prioritize vehicles or pedestrians accordingly. It also notifies pedestrians of the remaining crossing time using a connected speaker. The goal is to reduce conflicts and give equal priority to both vehicles and pedestrians at intersections using real-time traffic density detection from camera images rather than sensors.
VEHICLE DETECTION, CLASSIFICATION, COUNTING, AND DETECTION OF VEHICLE DIRECTI...
This document summarizes a research paper that proposes methods for vehicle detection, classification, counting, and determining vehicle direction and lane detection using computer vision and deep learning techniques. The paper aims to demonstrate how these techniques can be used for applications in self-driving cars, driver assistance systems, traffic management, and parking systems. It reviews existing literature on related topics and proposes a methodology that uses YOLO for vehicle detection and classification, frame differencing to determine vehicle direction, and techniques like edge detection and Hough transforms for lane detection.
TraVis CTTHES3
The document outlines a proposed system called TraVis that uses computer vision techniques to count vehicles and estimate traffic congestion levels from traffic surveillance camera videos. The system would detect, track, classify and count vehicles in video frames to generate traffic statistics. A web interface would allow users to access the traffic data and congestion estimates calculated from the video analysis. The document discusses the objectives, system design, implementation details and experimental results of the proposed TraVis system.
Real time deep-learning based traffic volume count for high-traffic urban art...
This document proposes and tests a deep learning-based system for real-time traffic volume counting on high-traffic urban arterial roads. Video clips from 4 camera views along arterial roads with estimated annual average daily traffic over 50,000 vehicles were used to test the system. The system achieved average accuracy rates between 93.84-97.68% across the camera views for 5 and 15-minute video clips. It was also able to process frames in real-time at an average of 37.27ms per frame. The proposed system provides an accurate and efficient method for traffic authorities to conduct traffic volume surveys on busy urban roads.
IRJET- i-Surveillance Crime Monitoring and Prevention using Neural Networks
This document proposes an intelligent video surveillance system called i-Surveillance that can detect dangerous or abnormal behaviors by using neural networks and image processing. The system would monitor CCTV footage and alert operators when it detects things like someone entering a danger zone, handling weapons, or acts of abuse. This aims to reduce the workload of human CCTV operators as the number of camera views increases. It focuses on limiting false alarms so it can be effectively used in real-world applications. The system would only record video and trigger alerts during detected "situations of interest", helping to address privacy and confidentiality concerns compared to continuously recording surveillance footage.
Traffic Monitoring Using Visual Big Data Analytics in Smart Cities
This document proposes a visual big data analytics framework for automatically detecting bike riders without helmets in city traffic using surveillance cameras. It involves a two phase process: 1) identifying bike riders in video frames using background subtraction, object segmentation and classification algorithms. 2) Identifying if the rider is wearing a helmet or not by detecting the head region and applying algorithms like HOG, SIFT and LBP for feature extraction and classification. The framework is designed to process large volumes of video data in real-time using distributed computing over cloud infrastructure for traffic monitoring in smart cities. Experimental results show the approach can detect 93.8% of cases with a processing time of 11.58ms per frame.
Similar to SYSTEM AND METHOD FOR ACQUIRING OF STATIC IMAGES OF OBJECTS IN MOTION (20)
Project Proposal Project Proposal Project Proposal Project Proposal
Project Proposal Project Proposal Project Proposal Project Proposal
Real Time Object Identification for Intelligent Video Surveillance Applications
Real Time Object Identification for Intelligent Video Surveillance Applications
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
IRJET- A Survey of Approaches for Vehicle Traffic Analysis
Identification and classification of moving vehicles on road
Identification and classification of moving vehicles on road
Smart Parking Solution using Camera Networks and Real-time Computer Vision
Smart Parking Solution using Camera Networks and Real-time Computer Vision
IRJET- Vehicle Seat Vacancy Identification using Image Processing Technique
IRJET- Vehicle Seat Vacancy Identification using Image Processing Technique
IRJET- Time To Cross – Traffic Light Control System using Image Processing
IRJET- Time To Cross – Traffic Light Control System using Image Processing
VEHICLE DETECTION, CLASSIFICATION, COUNTING, AND DETECTION OF VEHICLE DIRECTI...
VEHICLE DETECTION, CLASSIFICATION, COUNTING, AND DETECTION OF VEHICLE DIRECTI...
Real time deep-learning based traffic volume count for high-traffic urban art...
Real time deep-learning based traffic volume count for high-traffic urban art...
IRJET- i-Surveillance Crime Monitoring and Prevention using Neural Networks
IRJET- i-Surveillance Crime Monitoring and Prevention using Neural Networks
Traffic Monitoring Using Visual Big Data Analytics in Smart Cities
Traffic Monitoring Using Visual Big Data Analytics in Smart Cities
More from USP
AGENTES DE IMAGEN MOLECULAR MULTITÉCNICA Y SUS RESPECTIVOS KITS PARA DIAGNÓSTICO
Este documento describe agentes de imagen molecular multitécnica y sus kits de diagnóstico respectivos para detectar tumores. Los agentes son nanoformulaciones que pueden concentrarse en tumores y señalar su presencia y ubicación a través de varias técnicas de imagen como resonancia magnética, tomografía por emisión de positrones, SPECT y gammagrafía. El objetivo es mejorar la sensibilidad del diagnóstico de tumores de manera menos invasiva para un diagnóstico temprano y un tratamiento más efectivo.
MULTI-TECHNIQUE MOLECULAR IMAGING AGENTS AND THEIR DIAGNOSTIC KITS
This document describes an invention for multi-technique molecular imaging agents and their diagnostic kits. The agents can be concentrated on tumors and indicate their existence and location using techniques like MRI, PET, SPECT, and scintigraphy. The main purposes are to increase the sensitivity of imaging diagnosis and allow radiopharmaceuticals to be carried precisely to treatment sites in a less invasive way, enabling earlier diagnosis and more effective tumor treatment. The formulations are also available as "cold kits" whose procedures are already familiar to medical professionals, making them easier to adopt for diagnosis and treatment.
AGENTES DE IMAGEM MOLECULAR MULTITÉCNICA E RESPECTIVOS KITS PARA DIAGNÓSTICO
Este documento descreve agentes de imagem molecular multitécnica e respectivos kits de diagnóstico para detecção de câncer. Os agentes são nanoagentes que podem ser detectados por várias técnicas de imagem e se concentram em tumores para indicar sua localização. Os kits fornecem maior sensibilidade para diagnóstico precoce de câncer e possibilidade de tratamento menos invasivo, aumentando as chances de cura.
SENSOR QUÍMICO, PROCESO DE FABRICACIÓN Y SU USO EN LA MEDICIÓN DEL pH EN SIS...
Este documento describe un sensor químico y su proceso de fabricación para medir el pH en sistemas microfluidicos. El sensor se coloca en un substrato base con un agujero para que entre en contacto con el líquido a medir. El chip se conecta eléctricamente al substrato mediante soldadura por viraje. El objetivo es resolver problemas en la medición de parámetros químicos protegiendo las estructuras eléctricas del chip y la región sensible durante el proceso de fabricación para evitar daños o errores.
CHEMICAL SENSOR, FABRICATION PROCESS AND ITS USE IN pH MEASUREMENT IN MICROFL...
Currently, chemical processes that use water as substance for chemical reactions are very common. In such processes, it is important to obtain parameters of water quality, in order not to interfere with chemical reaction results.
SENSOR QUÍMICO, PROCESSO DE FABRICAÇÃO E SEU USO NA MEDIÇÃO DE PH EM SISTEMAS...
Este documento descreve um sensor químico para medir o pH em sistemas microfluidicos. O sensor é fabricado colocando um chip sobre um substrato com um furo, permitindo que o sensor entre em contato com o líquido a ser testado. O chip é conectado eletricamente ao substrato por soldagem, protegendo a região sensível durante o processo de fabricação. O objetivo é resolver problemas com sensores atuais, como danificar a região sensível ou ter erros na medição.
Anuário de Patentes USP 2016
Este arquivo contem os flyers de divulgação de todas as patentes divulgadas pela Agência USP de Inovação em 2016.
Todas as patentes apresentadas são de titularidade da Universidade de São Paulo, e estão disponíveis para contratos de licenciamento e exploração.
Dental Radiographic Individualized Positioner
Radiography of periapical region has become an ordinary and indispensable examination in several areas of dentistry. The high quality, definition and fidelity between the images are fundamental requisites for a correct interpretation and reliability in the use of these results in researches and aid for the construction of clinical diagnosis.
However, errors in the radiographic technique application, mainly errors of angulation, are often reported. With this reflection in mind, research accomplished by the Faculty of Odontology developed an innovative standard device for dental radiography.
Posicionador Radiográfico Odontológico Individualizado
El documento describe un posicionador radiográfico odontológico individualizado desarrollado por investigadores de la Facultad de Odontología. El dispositivo permite la estandarización geométrica de imágenes radiográficas para mejorar la precisión del diagnóstico reduciendo errores de ángulo. Fue desarrollado para ser asequible, sostenible y compatible con cualquier posicionador radiográfico existente.
Posicionador Radiográfico Odontológico Individualizado
O exame radiográfico periapical se tornou rotineiro e indispensável em diversas áreas da odontologia. A alta qualidade, definição e fidelidade entre as imagens são requisitos fundamentais à correta interpretação e confiabilidade no uso desses resultados em pesquisas e no auxílio para a construção de diagnóstico.
Contudo, erros na aplicação da técnica radiográfica, principalmente erros de angulação, são comumente relatados. Pensando nisso, pesquisa realizada pela Faculdade de Odontologia desenvolveu o dispositivo padronizador radiográfico odontológico.
Obtención de Leveduras Enriquecidas con Selenio a partir de Residuos Vegetales
De acuerdo con investigación reciente publicada pela revista Molecules, el selenio es uno de los elementos clasificados dentro del grupo de micronutrientes indispensables a la garantía del buen funcionamiento de organismos. Incluso, en los últimos años, varias descubiertas fueran hechas sobre las potencialidades del selenio en la dieta animal y humana, tal como su poder antitumoral.
Considerando la importancia nutricional de ese componente y la necesidad de modelos de producción cada vez más ambientalmente amigables, la presente tecnología describe un proceso de producción de levaduras enriquecidas con selenio a partir de residuos vegetales; tales como el bagazo de caña de azúcar y el salvado de arroz, los cuales funcionan como fuentes de carbono y nitrógeno.
Acquisition of Selenium-Enriched Yeast based on Agro-Industrial Residues
According to recent article published by Molecules Journal, selenium is one of the elements classified into the group of micronutrients indispensable to guarantee the proper functioning of organisms. In addition, over the last few years, many new discoveries come up about selenium potentialities in the animal and human diet, such as its power anticarcinogen.
Considering the important nutritional rule of this component and the need of a production models more and more environmentally-friendly, the present invention describes a production process of selenium enriched yeasts based on agro-industrial residues, such as sugarcane bagasse and rice bran, which serve as carbon and nitrogen sources.
Obtenção de Leveduras Enriquecidas com Selênio a partir de Resíduos Vegetais
De acordo com artigo recente publicado pela revista Molecules, o selênio é um dos elementos classificados dentro do grupo de micronutrientes indispensáveis à garantia do bom funcionamento de organismos. Inclusive, nos últimos anos, várias foram as descobertas sobre suas potencialidades na dieta animal e humana, tal como seu poder anticancerígeno.
Considerando a importância nutricional desse componente e a necessidade de modelos de produção cada vez mais ambientalmente amigáveis, a presente invenção descreve um processo de produção de leveduras enriquecidas com selênio a partir de resíduos vegetais; tais como o bagaço da cana-de-açúcar e o farelo de arroz, cujos funcionam como fontes de carbono e nitrogênio.
PROCESO DE OBTENCIÓN DE NANOPARTÍCULAS DE PLATA, NANOPARTÍCULA DE PLATA Y SUS...
Datos recientes de la Organización Mundial de la Salud (OMS) indican que a cada año 8,8 millones de personas mueren de cáncer en todo el mundo. Por lo tanto, el desarrollo de nuevas tecnologías más eficaces, baratas y ambientalmente sostenibles para el tratamiento de esa enfermedad se convierten en muy relevantes propósitos en los días de hoy.
Esta invención resulta en una nueva metodología de síntesis de Nanopartículas de plata, observando los principios de la química verde y utilizando extracto de algas marinas como agente reductor de iones de plata. Las Nanopartículas obtenidas a partir de esa síntesis constituyen buenos agentes antitumorales.
PROCESS TO OBTAIN SILVER NANOPARTICLES, SILVER NANOPARTICLES AND THEIR USES
Recent data published by the World Health Organization (WHO) shows that every year 8, 8 million people died from cancer around the world.
Therefore, the development of new technologies more efficient, chipper and environmentally-friendly for the treatment of this disease it is currently a very relevant goal. This invention is about a new methodology of synthesis of silver nanoparticles, in observance of the green chemistry and by using seaweed extracts as reducing agent of silver ions.
PROCESSO DE OBTENÇÃO DE NANOPARTÍCULAS DE PRATA, NANOPARTÍCULAS DE PRATA E US...
Dados recentes da Organização Mundial da Saúde (OMS) indicam que a cada ano 8,8 milhões de pessoas morrem de câncer em todo mundo. Portanto, o desenvolvimento de novas formas mais eficazes, baratas e ambientalmente sustentáveis para o tratamento dessa doença se tornam muito relevantes nos dias de hoje. Esta invenção trata de uma nova metodologia de síntese de nanopartículas de prata, observando os princípios da química verde e utilizando extrato de algas marinhas como agente redutor de íons prata. As nanopartículas obtidas através dessa síntese constituem bons agentes antitumorais.
AUGMENTED VISUALIZATION TECHNIQUE FOR VIRTUAL KEYBOARDS
The present invention consists in a Augmented Visualization Technique for Virtual Keyboards controlled by a pointing device, such as the eyes or the head. The Technique innovates in the field of computer and communication technology and has an important social role of inclusion and accessibility, because it makes possible the access to the moderns technologies for people with severe disabilities. Among its main contributions, there are, for example, the improvement of comfort and typing speed, that is achieved through the diversity of keyboard virtual information which includes, among others, information about the typing context and the acceleration of the words.
TÉCNICA DE VISUALIZACIÓN AUMENTADA PARA TECLADOS VIRTUALES
La presente invención se refiere a una Técnica de Visualización Aumentada para Teclados Virtuales controlados a través de un dispositivo señalador, como la mirada o la cabeza. La Técnica abre nuevos caminos en el campo de la Tecnología de la Informática y de la Comunicación y cumple un importante papel social de inclusión y accesibilidad, pues permite que personas con discapacidad motora tengan acceso a las tecnologías modernas. Entre sus principales aportaciones están el mayor confort y velocidad de escritura alcanzados a través del enriquecimiento de las informaciones visuales del teclado, que incluyen, entre otros, informaciones del contexto escrito y la aceleración de las palabras.
TÉCNICA DE VISUALIZAÇÃO AUMENTADA PARA TECLADOS VIRTUAIS
A presente invenção consiste em uma Técnica de visualização aumentada para teclados virtuais controlados por um dispositivo de apontamento como o olhar ou a cabeça. A Técnica inova no campo da tecnologia da informática e comunicação e cumpre papel social de inclusão e acessibilidade, ao possibilitar que pessoas com deficiência motora severa tenham acesso às tecnologias modernas. Dentre as principais contribuições do invento estão o maior conforto e velocidade de digitação alcançadas por meio do enriquecimento das informações visuais do teclado que incluem, entre outras, informações do contexto digitado e aceleração de palavras.
ADQUISICIÓN DE IMÁGENES ESTÁTICAS DE OBJETOS EN MOVIMIENTO
Este documento describe una invención para adquirir imágenes estáticas de objetos en movimiento a partir de videos. La invención se enfoca en capturar imágenes laterales de vehículos que pasan por peajes de autopistas brasileñas, donde no hay espacio suficiente para fotografías estándar. El sistema propuesto utiliza procesamiento de video para detectar objetos y "coser" cuadros para crear imágenes planas de vehículos completos en movimiento.
More from USP (20)
AGENTES DE IMAGEN MOLECULAR MULTITÉCNICA Y SUS RESPECTIVOS KITS PARA DIAGNÓSTICO
AGENTES DE IMAGEN MOLECULAR MULTITÉCNICA Y SUS RESPECTIVOS KITS PARA DIAGNÓSTICO
MULTI-TECHNIQUE MOLECULAR IMAGING AGENTS AND THEIR DIAGNOSTIC KITS
MULTI-TECHNIQUE MOLECULAR IMAGING AGENTS AND THEIR DIAGNOSTIC KITS
AGENTES DE IMAGEM MOLECULAR MULTITÉCNICA E RESPECTIVOS KITS PARA DIAGNÓSTICO
AGENTES DE IMAGEM MOLECULAR MULTITÉCNICA E RESPECTIVOS KITS PARA DIAGNÓSTICO
SENSOR QUÍMICO, PROCESO DE FABRICACIÓN Y SU USO EN LA MEDICIÓN DEL pH EN SIS...
SENSOR QUÍMICO, PROCESO DE FABRICACIÓN Y SU USO EN LA MEDICIÓN DEL pH EN SIS...
CHEMICAL SENSOR, FABRICATION PROCESS AND ITS USE IN pH MEASUREMENT IN MICROFL...
CHEMICAL SENSOR, FABRICATION PROCESS AND ITS USE IN pH MEASUREMENT IN MICROFL...
SENSOR QUÍMICO, PROCESSO DE FABRICAÇÃO E SEU USO NA MEDIÇÃO DE PH EM SISTEMAS...
SENSOR QUÍMICO, PROCESSO DE FABRICAÇÃO E SEU USO NA MEDIÇÃO DE PH EM SISTEMAS...
Posicionador Radiográfico Odontológico Individualizado
Posicionador Radiográfico Odontológico Individualizado
Posicionador Radiográfico Odontológico Individualizado
Posicionador Radiográfico Odontológico Individualizado
Obtención de Leveduras Enriquecidas con Selenio a partir de Residuos Vegetales
Obtención de Leveduras Enriquecidas con Selenio a partir de Residuos Vegetales
Acquisition of Selenium-Enriched Yeast based on Agro-Industrial Residues
Acquisition of Selenium-Enriched Yeast based on Agro-Industrial Residues
Obtenção de Leveduras Enriquecidas com Selênio a partir de Resíduos Vegetais
Obtenção de Leveduras Enriquecidas com Selênio a partir de Resíduos Vegetais
PROCESO DE OBTENCIÓN DE NANOPARTÍCULAS DE PLATA, NANOPARTÍCULA DE PLATA Y SUS...
PROCESO DE OBTENCIÓN DE NANOPARTÍCULAS DE PLATA, NANOPARTÍCULA DE PLATA Y SUS...
PROCESS TO OBTAIN SILVER NANOPARTICLES, SILVER NANOPARTICLES AND THEIR USES
PROCESS TO OBTAIN SILVER NANOPARTICLES, SILVER NANOPARTICLES AND THEIR USES
PROCESSO DE OBTENÇÃO DE NANOPARTÍCULAS DE PRATA, NANOPARTÍCULAS DE PRATA E US...
PROCESSO DE OBTENÇÃO DE NANOPARTÍCULAS DE PRATA, NANOPARTÍCULAS DE PRATA E US...
AUGMENTED VISUALIZATION TECHNIQUE FOR VIRTUAL KEYBOARDS
AUGMENTED VISUALIZATION TECHNIQUE FOR VIRTUAL KEYBOARDS
TÉCNICA DE VISUALIZACIÓN AUMENTADA PARA TECLADOS VIRTUALES
TÉCNICA DE VISUALIZACIÓN AUMENTADA PARA TECLADOS VIRTUALES
TÉCNICA DE VISUALIZAÇÃO AUMENTADA PARA TECLADOS VIRTUAIS
TÉCNICA DE VISUALIZAÇÃO AUMENTADA PARA TECLADOS VIRTUAIS
ADQUISICIÓN DE IMÁGENES ESTÁTICAS DE OBJETOS EN MOVIMIENTO
ADQUISICIÓN DE IMÁGENES ESTÁTICAS DE OBJETOS EN MOVIMIENTO
Recently uploaded
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Dmitrii Kamaev, PhD
Senior Product Owner - QIAGEN
GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Artificial Intelligence and Electronic Warfare
Artificial Intelligence and Electronic WarfarePapadakis K.-Cyber-Information Warfare Analyst & Cyber Defense/Security Consultant-Hellenic MoD
AI & Electronic WarfareAppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Principle of conventional tomography-Bibash Shahi ppt..pptx
before the computed tomography, it had been widely used.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Recently uploaded (20)
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Principle of conventional tomography-Bibash Shahi ppt..pptx
Principle of conventional tomography-Bibash Shahi ppt..pptx
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
SYSTEM AND METHOD FOR ACQUIRING OF STATIC IMAGES OF OBJECTS IN MOTION
- 1. Fabrício Shigueru Catae, Mário Piai Júnior and Hae Yong Kim SYSTEM AND METHOD FOR ACQUIRING OF STATIC IMAGES OF OBJECTS IN MOTION Introduction Purposes Application and Target Markets Patent protected under No.: BR 102013014158-5Field: Technology of Information and Communications School of Engineering This invention assists the needs from the toll road concession companies. The vehicle supervision in Brazilian highways has an important role in the maintenance of public order in the traffic. Hence, the present invention is a system for acquisition of static images of objects in motion from videos in the surveillance, such as lateral images of vehicles which move in toll roads. Moreover, this invention also describes a method which consists in a process of detection of objects and video stitching. In many Brazilian toll roads, vehicles in motion should be photographed sidelong. Common cameras cannot be used for this goal, mainly, because there is no enough space between the roads that allows the acquisition of photos of whole vehicles. This invention proposes a system and method for acquiring static images of objects in motion from videos, of which video frames are “stitching” to obtain just one image. 0060/2013 programação testes operacional Development Stage Information Technology