This document discusses gesture phones and gesture recognition technology. It begins by explaining how gestures are recognized through optical tracking, inertial tracking, and calibration. Examples are given of how gestures could control a smartphone, such as answering calls or controlling media playback. Challenges of gesture recognition are also mentioned. The document then discusses applications of gesture technology on Android and Windows phones through various apps that enable gesture control. Benefits of gesture technology include more intuitive interaction and control when touch is not possible.
This presentation provides an overview of multi-touch hardware, products, applications and market examples as well as samples of projects of TNO. More information on http://www.tno.nl/nui
Study of Various Touch Screen TechnologiesSantosh Ankam
Study of different types of touch screen technologies, their history, advantages, disadvantages, working, functionalities, comparison, examples, components, hardware, explanations, future scope, pro and cons.
The document discusses touchless touchscreen technology, including touch walls that use infrared lasers to scan surfaces, touchless UIs that sense finger movements in 3D space without touching the screen, and touchless monitors that detect 3D motion without sensors. It provides examples of touchless technology inspired by Minority Report including eye tracking, gesture recognition, and motion sensing devices. The document concludes that touchless interfaces could transform bodies into virtual input devices in the future.
Design of Image Projection Using Combined Approach for TrackingIJMER
Over the years the techniques and methods that have been used to interact with the
computers have evolved significantly. From the primitive use of punch cards to the latest touch screen
panels we can see the vast improvement in interaction with the system. There are many new ways of
projection and interaction technologies that can reshape our perception and interaction
methodologies. Also projection technology is very useful for creating various geometric displays. In
earlier generations, the projector technology was used for projecting images and videos on single
screen, using large and bulky setup. To overcome the earlier limitations we are designing “Wireless
Image Projection Tracking”, which is a system that uses IR (Infrared) technology to track the body in
the IR range and uses their movements for image orientation and manipulations like zoom, tilt/rotate,
and scale. We are presenting a method of mapping IR light source position and orientation to an
image. By using this system we can also track single and multiple IR light source positions and also it
can be used effectively to see the image projection in 3D view. Extension in this technology can further
be useful for future tracking capabilities to implement the touch screen feature for commercial
applications.
This presentation explains how to use hand gestures recognized by accelerometers or digital image processing to control devices in a simple way without physical contact. Applications include sending text messages, making phone calls, gaming, controlling computers, and virtually controlling robots. Future enhancements could allow gesture control on flights or for security systems.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2014-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Francis MacDougall, Senior Director of Technology at Qualcomm, presents the "Vision-Based Gesture User Interfaces" tutorial at the May 2014 Embedded Vision Summit.
The means by which we interact with the machines around us is undergoing a fundamental transformation. While we may still sometimes need to push buttons, touch displays and trackpads, and raise our voices, we’ll increasingly be able to interact with and control our devices simply by signaling with our fingers, gesturing with our hands, and moving our bodies.
This presentation explains how gestures fit into the spectrum of advanced user interface options, compares and contrasts the various 2-D and 3-D technologies (vision and other) available to implement gesture interfaces, gives examples of the various gestures (and means of discerning them) currently in use by systems manufacturers, and forecasts how the gesture interface market may evolve in the future.
The document proposes a novel approach to simulate mouse functions using only a webcam and computer vision techniques. Two colored tapes would be worn on the fingers to detect hand gestures for controlling mouse movements and clicks. The yellow tape on the index finger would control cursor position while the distance between the yellow and red tapes would determine click events. Left clicks would occur when the thumb tape nears the index finger tape, right clicks from pausing in position, and double clicks from pausing both tapes in position. This vision-based mouse simulation could revolutionize human-computer interaction by eliminating physical devices.
This presentation provides an overview of multi-touch hardware, products, applications and market examples as well as samples of projects of TNO. More information on http://www.tno.nl/nui
Study of Various Touch Screen TechnologiesSantosh Ankam
Study of different types of touch screen technologies, their history, advantages, disadvantages, working, functionalities, comparison, examples, components, hardware, explanations, future scope, pro and cons.
The document discusses touchless touchscreen technology, including touch walls that use infrared lasers to scan surfaces, touchless UIs that sense finger movements in 3D space without touching the screen, and touchless monitors that detect 3D motion without sensors. It provides examples of touchless technology inspired by Minority Report including eye tracking, gesture recognition, and motion sensing devices. The document concludes that touchless interfaces could transform bodies into virtual input devices in the future.
Design of Image Projection Using Combined Approach for TrackingIJMER
Over the years the techniques and methods that have been used to interact with the
computers have evolved significantly. From the primitive use of punch cards to the latest touch screen
panels we can see the vast improvement in interaction with the system. There are many new ways of
projection and interaction technologies that can reshape our perception and interaction
methodologies. Also projection technology is very useful for creating various geometric displays. In
earlier generations, the projector technology was used for projecting images and videos on single
screen, using large and bulky setup. To overcome the earlier limitations we are designing “Wireless
Image Projection Tracking”, which is a system that uses IR (Infrared) technology to track the body in
the IR range and uses their movements for image orientation and manipulations like zoom, tilt/rotate,
and scale. We are presenting a method of mapping IR light source position and orientation to an
image. By using this system we can also track single and multiple IR light source positions and also it
can be used effectively to see the image projection in 3D view. Extension in this technology can further
be useful for future tracking capabilities to implement the touch screen feature for commercial
applications.
This presentation explains how to use hand gestures recognized by accelerometers or digital image processing to control devices in a simple way without physical contact. Applications include sending text messages, making phone calls, gaming, controlling computers, and virtually controlling robots. Future enhancements could allow gesture control on flights or for security systems.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2014-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Francis MacDougall, Senior Director of Technology at Qualcomm, presents the "Vision-Based Gesture User Interfaces" tutorial at the May 2014 Embedded Vision Summit.
The means by which we interact with the machines around us is undergoing a fundamental transformation. While we may still sometimes need to push buttons, touch displays and trackpads, and raise our voices, we’ll increasingly be able to interact with and control our devices simply by signaling with our fingers, gesturing with our hands, and moving our bodies.
This presentation explains how gestures fit into the spectrum of advanced user interface options, compares and contrasts the various 2-D and 3-D technologies (vision and other) available to implement gesture interfaces, gives examples of the various gestures (and means of discerning them) currently in use by systems manufacturers, and forecasts how the gesture interface market may evolve in the future.
The document proposes a novel approach to simulate mouse functions using only a webcam and computer vision techniques. Two colored tapes would be worn on the fingers to detect hand gestures for controlling mouse movements and clicks. The yellow tape on the index finger would control cursor position while the distance between the yellow and red tapes would determine click events. Left clicks would occur when the thumb tape nears the index finger tape, right clicks from pausing in position, and double clicks from pausing both tapes in position. This vision-based mouse simulation could revolutionize human-computer interaction by eliminating physical devices.
Gesture recognition technology uses mathematical algorithms to interpret human gestures and enable interaction with machines without physical devices. It has various applications including sign language recognition, interpreting facial expressions, and electrical field sensing of body proximity. Vision-based and device-based techniques use cameras, gloves, or other sensors to detect gestures. Challenges include varying lighting and background items that can reduce accuracy. The future potential is vast across entertainment, home automation, education, medicine and security.
The Gesture Recognition Technology is rapidly growing technology and this PPT describes about the working of gesture recognition technology,the sub fields in it, its applications and the challenges it faces.
project presentation on mouse simulation using finger tip detection Sumit Varshney
This project presentation describes a virtual mouse interface using finger tip detection. A group of 3 students will design a vision-based mouse that detects hand gestures to control cursor movement and clicks instead of using a physical mouse. The system will use a webcam to capture finger tip motion and apply image processing algorithms like segmentation, denoising, and convex hull analysis to identify gestures and control mouse functions accordingly. The goal is to allow gesture-based computer interaction for applications like presentations to reduce workspace needs.
This document summarizes a research paper about developing a finger tracking and gesture recognition application for smartphones using the front-facing camera. The application aims to enable new touchless interaction methods on mobile devices. It utilizes computer vision techniques like background subtraction, skin detection and contour analysis to track finger movements in varied lighting conditions. The key stages of the framework include receiving video frames from the camera, processing the frames to recognize gestures, and sending commands to third-party apps based on the detected gestures. The application could allow contactless control of tasks like answering calls, changing music tracks or images without additional hardware requirements.
This document summarizes a technology called Sixth Sense, which allows users to perform gestures to interact with digital information rather than using keyboards or mice. It discusses using commands recognized by a speech integrated circuit instead of gestures to overcome limitations of gesture recognition. The speech IC is trained to recognize commands, which then trigger actions performed by a mobile device and projected for the user.
SixthSense is a name for extra information supplied by a wearable computer, such as the device called EyeTap (Mann), Telepointer (Mann), and "WuW" (Wear yoUr World) by Pranav Mistry
IRJET- Enhanced Look Based Media Player with Hand Gesture RecognitionIRJET Journal
The document describes a proposed enhanced media player that uses face detection and hand gesture recognition to control playback. Specifically, it will:
1. Continuously monitor the user's face using a webcam and only play the video when the user is looking at the screen, pausing otherwise.
2. Detect hand gestures like raising a hand to increase volume, decrease volume, switch to the next video, or previous video.
3. The system is intended to provide a better media playback experience by automating control and preventing the user from missing parts of a video if they look away. Both face detection and hand gesture recognition are implemented using computer vision algorithms like HAAR cascades.
Gesture Based Interface Using Motion and Image Comparisonijait
This paper gives a new approach for movement of mouse and implementation of its functions using a real time camera. Here we propose to change the hardware design. Most of the existing technologies mainly depend on changing the mouse parts features like changing the position of tracking ball and adding more buttons. We use a camera, colored substance, image comparison technology and motion detection technology to control mouse movement and implement its functions (right click, left click, scrolling and double click) .
Gesture Recognition Techniques, Leap Motion Sensor: Taking leap to control anything in a real human manner unlike traditional artificial taps and clicks , Sviacam, Eviacam, moves the mouse pointer as you move your Head.
Hand gesture recognition system for human computer interaction using contour ...eSAT Journals
This document describes a hand gesture recognition system that allows users to control computer operations using hand gestures captured by a webcam. The system involves four main phases: 1) image acquisition using a webcam, 2) image pre-processing to extract the hand and reduce noise, 3) feature extraction by detecting hand contours, and 4) gesture recognition by comparing contour features to stored templates and assigning computer commands. The system was able to recognize various gestures like opening programs or pressing keys with an average recognition rate of 95%. Future work could involve reducing constraints on the user environment and allowing both hands to perform more operations.
This document presents a virtual mouse system that uses computer vision and hand gesture recognition to control the mouse cursor and perform mouse tasks. The system aims to provide a more natural and convenient way to control the computer without requiring physical mouse hardware. It uses a webcam to detect colored fingertips and track hand movements in real-time. Image processing algorithms are employed for tasks like segmentation, denoising, finding the hand center and size, and detecting individual fingertips. Detected gestures are then mapped to mouse functions like cursor movement, left/right clicks, and scrolling. The document outlines the goals, design approach, and implementation details of the system, as well as advantages, limitations, and directions for future work.
This document summarizes a research project that developed an interactive display system using image feedback localization techniques. The system uses an infrared LED or laser pointer as an input device on projected surfaces to replace a mouse or keyboard. A projector is used for display, and a camera captures images to localize the infrared pointer and track user movement. Several applications are demonstrated, including using the pointer on projected surfaces like tables or car windows to interact with documents, games, and more. The system aims to provide an intuitive, low-cost interactive display environment.
Sixth Sense is a wearable gestural interface device developed by Pranav Mistry, a PhD student in the Fluid Interfaces Group at the MIT Media Lab. It is similar to Telepointer, a neck worn projector/camera system developed by Media Lab student Steve Mann (which Mann originally referred to as "Synthetic Synesthesia of the Sixth Sense").
This document is a final report on gesture recognition submitted by three students. It contains an abstract, introduction, background information on gesture recognition including American Sign Language and object recognition techniques. It discusses digital image processing and neural networks. It outlines the approach, modules, flowcharts, results and conclusions of the project, which developed a method to recognize static hand gestures using a perceptron neural network trained on orientation histograms of the input images. Source code and applications are also discussed.
Gesture based computing uses gestures as a form of human-computer interaction. It can be used to replace mice and keyboards by allowing users to navigate interfaces and interact with 3D environments through gestures detected by cameras. Common technologies for gesture recognition include depth cameras, controllers, and single visible light cameras. Gestures can be used for applications in entertainment, gaming, communications for disabled individuals, and as an alternative computer interface.
Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Co...Waqas Tariq
This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm where three algorithms for hand segmentation using different color spaces with required morphological processing have were utilized. Hand tracking and segmentation algorithm (HTS) is found to be most efficient to handle the challenges of vision based system such as skin color detection, complex background removal and variable lighting condition. Noise may contain, sometime, in the segmented image due to dynamic background. An edge traversal algorithm was developed and applied on the segmented hand contour for removal of unwanted background noise.
Gesture recognition is the process of understanding and
interpreting meaningful movements of the hands, arms, face,
or sometimes head. It is of great need in designing an
efficient human-computer interface. The technology has
been in study in recent years because of its potential for
application in user interfaces
Natural Hand Gestures Recognition System for Intelligent HCI: A SurveyEditor IJCATR
Gesture recognition is to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head,
and/or body. Hand Gestures have greater importance in designing an intelligent and efficient human–computer interface. The applications
of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper a survey on
various recent gesture recognition approaches is provided with particular emphasis on hand gestures. A review of static hand posture
methods are explained with different tools and algorithms applied on gesture recognition system, including connectionist models, hidden
Markov model, and fuzzy clustering. Challenges and future research directions are also highlighted.
This document provides information about the history of Earth's climate and global warming. It discusses how Earth originally had a hotter climate with less intense sunlight billions of years ago. It then describes how the appearance of life and the onset of photosynthesis led to periods of cooling and warming as greenhouse gases levels fluctuated. More recently, the Earth began its current cycle of glacial and interglacial periods around 3 million years ago. The document then provides explanations and illustrations of the greenhouse effect, human activities that contribute to increased greenhouse gases and global warming, and some actions individuals can take to reduce their emissions.
I 2013 blev jeg spurgt om jeg havde lyst til at lave en hjemmeside for Gerlach Import, hvilket jeg hurtigt sagde ja til, fordi at jeg tænkte at det var en spændende udfording at at udarbejde så stort et site fra bunden.
Gesture recognition technology uses mathematical algorithms to interpret human gestures and enable interaction with machines without physical devices. It has various applications including sign language recognition, interpreting facial expressions, and electrical field sensing of body proximity. Vision-based and device-based techniques use cameras, gloves, or other sensors to detect gestures. Challenges include varying lighting and background items that can reduce accuracy. The future potential is vast across entertainment, home automation, education, medicine and security.
The Gesture Recognition Technology is rapidly growing technology and this PPT describes about the working of gesture recognition technology,the sub fields in it, its applications and the challenges it faces.
project presentation on mouse simulation using finger tip detection Sumit Varshney
This project presentation describes a virtual mouse interface using finger tip detection. A group of 3 students will design a vision-based mouse that detects hand gestures to control cursor movement and clicks instead of using a physical mouse. The system will use a webcam to capture finger tip motion and apply image processing algorithms like segmentation, denoising, and convex hull analysis to identify gestures and control mouse functions accordingly. The goal is to allow gesture-based computer interaction for applications like presentations to reduce workspace needs.
This document summarizes a research paper about developing a finger tracking and gesture recognition application for smartphones using the front-facing camera. The application aims to enable new touchless interaction methods on mobile devices. It utilizes computer vision techniques like background subtraction, skin detection and contour analysis to track finger movements in varied lighting conditions. The key stages of the framework include receiving video frames from the camera, processing the frames to recognize gestures, and sending commands to third-party apps based on the detected gestures. The application could allow contactless control of tasks like answering calls, changing music tracks or images without additional hardware requirements.
This document summarizes a technology called Sixth Sense, which allows users to perform gestures to interact with digital information rather than using keyboards or mice. It discusses using commands recognized by a speech integrated circuit instead of gestures to overcome limitations of gesture recognition. The speech IC is trained to recognize commands, which then trigger actions performed by a mobile device and projected for the user.
SixthSense is a name for extra information supplied by a wearable computer, such as the device called EyeTap (Mann), Telepointer (Mann), and "WuW" (Wear yoUr World) by Pranav Mistry
IRJET- Enhanced Look Based Media Player with Hand Gesture RecognitionIRJET Journal
The document describes a proposed enhanced media player that uses face detection and hand gesture recognition to control playback. Specifically, it will:
1. Continuously monitor the user's face using a webcam and only play the video when the user is looking at the screen, pausing otherwise.
2. Detect hand gestures like raising a hand to increase volume, decrease volume, switch to the next video, or previous video.
3. The system is intended to provide a better media playback experience by automating control and preventing the user from missing parts of a video if they look away. Both face detection and hand gesture recognition are implemented using computer vision algorithms like HAAR cascades.
Gesture Based Interface Using Motion and Image Comparisonijait
This paper gives a new approach for movement of mouse and implementation of its functions using a real time camera. Here we propose to change the hardware design. Most of the existing technologies mainly depend on changing the mouse parts features like changing the position of tracking ball and adding more buttons. We use a camera, colored substance, image comparison technology and motion detection technology to control mouse movement and implement its functions (right click, left click, scrolling and double click) .
Gesture Recognition Techniques, Leap Motion Sensor: Taking leap to control anything in a real human manner unlike traditional artificial taps and clicks , Sviacam, Eviacam, moves the mouse pointer as you move your Head.
Hand gesture recognition system for human computer interaction using contour ...eSAT Journals
This document describes a hand gesture recognition system that allows users to control computer operations using hand gestures captured by a webcam. The system involves four main phases: 1) image acquisition using a webcam, 2) image pre-processing to extract the hand and reduce noise, 3) feature extraction by detecting hand contours, and 4) gesture recognition by comparing contour features to stored templates and assigning computer commands. The system was able to recognize various gestures like opening programs or pressing keys with an average recognition rate of 95%. Future work could involve reducing constraints on the user environment and allowing both hands to perform more operations.
This document presents a virtual mouse system that uses computer vision and hand gesture recognition to control the mouse cursor and perform mouse tasks. The system aims to provide a more natural and convenient way to control the computer without requiring physical mouse hardware. It uses a webcam to detect colored fingertips and track hand movements in real-time. Image processing algorithms are employed for tasks like segmentation, denoising, finding the hand center and size, and detecting individual fingertips. Detected gestures are then mapped to mouse functions like cursor movement, left/right clicks, and scrolling. The document outlines the goals, design approach, and implementation details of the system, as well as advantages, limitations, and directions for future work.
This document summarizes a research project that developed an interactive display system using image feedback localization techniques. The system uses an infrared LED or laser pointer as an input device on projected surfaces to replace a mouse or keyboard. A projector is used for display, and a camera captures images to localize the infrared pointer and track user movement. Several applications are demonstrated, including using the pointer on projected surfaces like tables or car windows to interact with documents, games, and more. The system aims to provide an intuitive, low-cost interactive display environment.
Sixth Sense is a wearable gestural interface device developed by Pranav Mistry, a PhD student in the Fluid Interfaces Group at the MIT Media Lab. It is similar to Telepointer, a neck worn projector/camera system developed by Media Lab student Steve Mann (which Mann originally referred to as "Synthetic Synesthesia of the Sixth Sense").
This document is a final report on gesture recognition submitted by three students. It contains an abstract, introduction, background information on gesture recognition including American Sign Language and object recognition techniques. It discusses digital image processing and neural networks. It outlines the approach, modules, flowcharts, results and conclusions of the project, which developed a method to recognize static hand gestures using a perceptron neural network trained on orientation histograms of the input images. Source code and applications are also discussed.
Gesture based computing uses gestures as a form of human-computer interaction. It can be used to replace mice and keyboards by allowing users to navigate interfaces and interact with 3D environments through gestures detected by cameras. Common technologies for gesture recognition include depth cameras, controllers, and single visible light cameras. Gestures can be used for applications in entertainment, gaming, communications for disabled individuals, and as an alternative computer interface.
Hand Segmentation Techniques to Hand Gesture Recognition for Natural Human Co...Waqas Tariq
This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm where three algorithms for hand segmentation using different color spaces with required morphological processing have were utilized. Hand tracking and segmentation algorithm (HTS) is found to be most efficient to handle the challenges of vision based system such as skin color detection, complex background removal and variable lighting condition. Noise may contain, sometime, in the segmented image due to dynamic background. An edge traversal algorithm was developed and applied on the segmented hand contour for removal of unwanted background noise.
Gesture recognition is the process of understanding and
interpreting meaningful movements of the hands, arms, face,
or sometimes head. It is of great need in designing an
efficient human-computer interface. The technology has
been in study in recent years because of its potential for
application in user interfaces
Natural Hand Gestures Recognition System for Intelligent HCI: A SurveyEditor IJCATR
Gesture recognition is to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head,
and/or body. Hand Gestures have greater importance in designing an intelligent and efficient human–computer interface. The applications
of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper a survey on
various recent gesture recognition approaches is provided with particular emphasis on hand gestures. A review of static hand posture
methods are explained with different tools and algorithms applied on gesture recognition system, including connectionist models, hidden
Markov model, and fuzzy clustering. Challenges and future research directions are also highlighted.
This document provides information about the history of Earth's climate and global warming. It discusses how Earth originally had a hotter climate with less intense sunlight billions of years ago. It then describes how the appearance of life and the onset of photosynthesis led to periods of cooling and warming as greenhouse gases levels fluctuated. More recently, the Earth began its current cycle of glacial and interglacial periods around 3 million years ago. The document then provides explanations and illustrations of the greenhouse effect, human activities that contribute to increased greenhouse gases and global warming, and some actions individuals can take to reduce their emissions.
I 2013 blev jeg spurgt om jeg havde lyst til at lave en hjemmeside for Gerlach Import, hvilket jeg hurtigt sagde ja til, fordi at jeg tænkte at det var en spændende udfording at at udarbejde så stort et site fra bunden.
I et skoleprojekt blev vi bedt om at udvikle en digital løsning der kunne skabe merværdi indenfor sundhedsområdet og her valgte vi at fokusere på diabetes.
Skoleprojekt - e-konceptudvikling - Redesign af 4yourbodyMia Christensen
På 1.semester på e-konceptudviklingsuddannelsen skulle vi komme med forslag til et redesign af en virksomhed efter eget valg. Her kan du se mit redsign og den teoretiske redegørelse for hvilke elementer jeg har brugt.
Vi blev i vores midtvejsprojekt bedt om at komme med et forslag til hvad Kvindemuseet i Århus kunne gøre digitalt for at gøre deres udstillinger interaktive og interessant for yngre målgrupper.
The document discusses the benefits of exercise for mental health. It states that regular exercise can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help alleviate symptoms of mental illnesses.
The doctrine of odious debt holds that sovereign debt incurred by a regime for purposes against the interests of the nation should not be repayable by successor governments. The concept originated from Alexander Sack who argued that debts incurred without citizen consent or interest should be considered "odious" and personal to the regime. The Vienna Convention expanded on this, defining odious debt as that incurred without benefit to the populace or in violation of international law. While the doctrine draws from sovereignty and fairness principles, it is not well established in international law due to challenges in application and identifying truly odious debts. Examples of odious debt disputes include those related to apartheid South Africa and Iraq.
The document discusses gesture phones and gesture recognition technology. It covers different tracking methods for gestures like optical tracking using cameras and inertial tracking using a single camera and rolling shutter. It provides examples of using gesture recognition like answering calls, operating devices, browsing pages, and switching off phones. Future innovations discussed include using gestures to smudge backgrounds for privacy, set alarms for anti-theft, and use ultrasonic waves for gestures in darkness. It also lists references for online gesture recognition, real-time tracking on cellphones, 6D motion gesture recognition, and enabling natural interactions with electronics using gesture recognition.
This document discusses gesture phones and gesture recognition technologies. It describes different tracking methods for gestures like optical tracking using stereoscopic vision and triangulation, and inertial tracking using a single camera and rolling shutter. Examples of using gestures to answer calls, browse the web, and control other devices are provided. Both the benefits and challenges of gesture recognition technologies are outlined, like the need for a flexible programming environment versus high power consumption. Potential future applications using ultrasonic waves and infrared are also mentioned.
1. The story takes place in 1948 at a hotel in Jamaica, where the narrator sits by the pool and observes an interaction between a marine boy, an English girl, and a little man named Carlos.
2. The marine boy brags about his lighter always working and bets Carlos that he can light it 10 times in a row, with Carlos betting his little finger against the boy's Cadillac if he loses.
3. They go to Carlos's room to settle the bet, but before it's finished, a woman arrives who reveals Carlos is actually poor and crazy, with only one finger on his hand.
Tanda tanda kehamilan dan pemeriksaan diagnostik kehamilaniiesti
Tanda-tanda kehamilan dan pemeriksaan diagnostik kehamilan memberikan penjelasan tentang tanda-tanda kehamilan yang terbagi menjadi tanda pasti, presumtif, dan kemungkinan serta pemeriksaan diagnostik seperti tes HCG, USG, dan palpasi abdomen untuk menentukan kehamilan.
The document discusses bionic eyes and their development. It begins by defining a bionic eye as an electronic device that replaces some or all of the eye's functionality. It then covers the anatomy and biology of the normal eye, common causes of blindness, and several technologies that have been applied to create bionic eyes, including the MIT-Harvard device, artificial silicon retina (ASR), Argus II, and holographic technology. A key technology discussed is MARC (Multiple Unit of Artificial Retinal Chipset System), which uses a chip implanted behind the retina to simulate remaining retinal cells. The document concludes by noting the challenges of powering implants and connecting them to the brain, but the promise of bionic devices
Sherlock: Monitoring sensor broadcasted data to optimize mobile environmentijsrd.com
Sherlock is a framework that uses sensors in smartphones to optimize the micro-environment around the phone. It runs as a daemon process and provides finer-grained environmental information to applications through APIs. The goal is to save battery by adapting the phone's behavior based on accurate context, such as dimming the screen when in a pocket or bag. It covers major usage scenarios and can detect if the phone is in the hand, on a desk, etc. using sensors like proximity, accelerometer, gyroscope. This allows applications to provide customized services based on the user's situation.
This document discusses gesture recognition, including what gestures are, types of gesture recognition like facial, hand, and sign language recognition. It covers the basic working of gesture technology and types of gesture sensing technologies such as device, electrical field, and vision-based sensing. Some applications of gesture recognition discussed include controlling devices, sign language translation, and assisting with patient rehabilitation. Challenges to gesture recognition are also mentioned such as lack of standard gesture languages and issues with robustness due to lighting and noise factors.
Sign Language Identification based on Hand GesturesIRJET Journal
This document presents a study on sign language identification based on hand gestures. The researchers aim to develop a system that can recognize American Sign Language gestures from video sequences. They use two different models - a Convolutional Neural Network (CNN) to analyze the spatial features of video frames, and a Recurrent Neural Network (RNN) to analyze the temporal features across frames. The document discusses the methodology used, including data collection from videos, pre-processing of frames, feature extraction using CNN models, and gesture classification. It also provides a literature review on previous studies related to sign language recognition and communication systems for deaf people.
This document summarizes a survey on detecting hand gestures to be used as input for computer interactions. The introduction discusses how graphical user interfaces are being upgraded to provide more efficient visual interfaces using touchscreen technologies. However, these technologies are still too expensive for laptops and desktops. The paper then proposes developing a virtual mouse system using a webcam to capture hand movements and perform mouse functions like left and right clicks. The methodology section outlines the key steps of the proposed system which includes skin detection, contour extraction from images, and mapping detected hand gestures to cursor movements and controls. Finally, the conclusion discusses the goal of making this technology cheaper and more accessible to use as a standard input device without additional hardware requirements.
Visteon has been researching time-of-flight (ToF) gesture interaction technology for use in vehicles. They integrated a ToF camera system into a test vehicle to investigate use cases. The ToF system can accurately detect spatial gestures, hand poses, touch inputs, and distinguish between the driver and passenger. It enables a more natural human-machine interface with potential applications like controlling infotainment and opening windows without physical contact. While progress has been made, future research needs to further explore passive gestures and driver monitoring capabilities.
IRJET- Mouse on Finger Tips using ML and AIIRJET Journal
This document describes a system that uses computer vision and machine learning to allow users to control a computer mouse using only their fingertips. The system tracks colored fingertips using a webcam and processes the video frames in real-time to detect and track the fingertips. It then maps the fingertip movements to mouse movements and gestures to control clicking, scrolling, and other mouse functions without any physical contact with the computer. The system was created using Python and aims to provide a more natural and cost-effective way for human-computer interaction through a virtual mouse controlled by hand gestures.
IRJET- Sixth Sense Technology in Image ProcessingIRJET Journal
This document describes sixth sense technology, which allows users to interact with digital information by using hand gestures that are detected by a camera. The technology was developed by Pranav Mistry to bridge the gap between the digital and physical worlds. It consists of a camera, projector, mirror, mobile phone, and colored markers on the fingers. The camera detects hand gestures and objects, and the projector displays related digital information onto physical surfaces. Pattern matching through image processing is used to recognize hand gestures and colors and trigger the appropriate responses from the sixth sense device. This technology has applications in areas like maps, drawing, calling, and photos.
Gesture recognition technology uses cameras to read human body movements and gestures as a form of input to control devices and applications. A camera captures gestures like hand movements and facial expressions and sends that data to a computer for interpretation. Gesture recognition allows humans to interact with machines naturally without physical devices by using gestures to control cursors, activate menus, or control games and other applications. There are different methods for capturing and interpreting gestures including using wired gloves, depth cameras, stereo cameras, single cameras, or motion controllers.
This document describes an "EyePhone" technology that allows users to control a mobile phone using only their eyes. It tracks eye movement and blinks using the front-facing camera and machine learning algorithms. Blinks can activate applications that the user is looking at. Potential applications include accessibility for disabled users and monitoring driver safety. Accuracy is limited on mobile phones due to camera quality and phone movement compared to desktop systems. The document outlines the eye tracking and detection algorithms used and discusses challenges of developing such a system for mobile use cases.
Top sensors inside the smartphone you want to knowsoniyasag
The document discusses the key sensors inside smartphones that enable their smart capabilities. It describes sensors such as the accelerometer, which senses device orientation; the magnetometer, which works with the digital compass to detect direction; the gyroscope, which maintains position and orientation; and the fingerprint sensor, which provides biometric authentication. It also mentions other sensors like the back-illuminated sensor for cameras, ambient light sensor for display brightness, GPS for location, proximity for detecting nearby objects, NFC for short-range connectivity, and more. All of these sensors collectively convert a normal phone into a smart device.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Gesture control algorithm for personal computerseSAT Journals
Abstract As our dependency on computers is increasing every day, these intelligent machines are making inroads in our daily life and society. This requires more friendly methods for interaction between humans and computers (HCI) than the conventionally used interaction devices (mouse & keyboard) because they are unnatural and cumbersome to use at times (by disabled people). Gesture Recognition can be useful under such conditions and provides intuitive interaction. Gestures are natural and intuitive means of communication and mostly occur from hands or face of human beings. This work introduces a hand gesture recognition system to recognize real time gestures of the user (finger movements) in unstrained environments. This is an effort to adapt computers to our natural means of communication: Speech and Hand Movements. All the work has been done using Matlab 2011b and in a real time environment which provides a robust technique for feature extraction and speech processing. A USB 2.0 camera continuously tracks the movement of user’s finger which is covered with red marker by filtering out green and blue colors from the RGB color space. Java based commands are used to implement the mouse movement through moving finger and GUI keyboard. Then a microphone is used to make use of the speech processing and instruct the system to click on a particular icon or folder throughout the screen of the system. So it is possible to take control of the whole computer system. Experimental results show that proposed method has high accuracy and outperforms Sub-gesture Modeling based methods [5] Keywords: Hand Gesture Recognition (HGR), Human-Computer Interaction (HCI), Intuitive Interaction
Sign Language Recognition using Machine LearningIRJET Journal
This document describes a study on sign language recognition using machine learning. The researchers developed a convolutional neural network model to detect hand movements and classify them as letters of the alphabet from sign language. They used a dataset of images of American Sign Language letters and trained their CNN model on this data. Their model was able to accurately recognize the letters in real-time using input from a webcam. The document also discusses using background subtraction and other techniques to improve the model's performance at sign language recognition.
EyePhone is a system that allows users to control their mobile phone using only their eyes. It tracks the user's eye movements across the phone's display using the front-facing camera. EyePhone detects eye blinks to emulate mouse clicks and activate target applications. It works by first detecting the user's eyes, then tracking eye movements to infer gaze position on the screen. Blinks are detected by applying a threshold to normalized correlation scores from template matching of the user's open eye template. EyePhone was evaluated on a Nokia N810 and shown to accurately track eyes and detect blinks with low computational overhead. Potential applications include eye-based menus and detecting driver drowsiness. Future work could improve performance under different lighting conditions and online
Gesture recognition technology allows for control of devices through hand and body motions. It works by using cameras, sensors and algorithms to interpret gestures and movements. Key applications include controlling smart TVs with hand motions, sign language translation, and assisting disabled individuals. Challenges include variations between individuals, reading motions accurately due to lighting and noise, and lack of standardized gesture languages.
Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand.
presentation for augmented reality. ,It consists of introduction, working, components of AR, applications, limitations, recent development and conclusion. all the best for your presentation
Controlling Computer using Hand GesturesIRJET Journal
This document describes a research project on controlling a computer using hand gestures. The researchers created a real-time gesture recognition system using convolutional neural networks (CNNs). They developed a dataset of 3000 training images of 10 different hand gestures for tasks like opening apps. A CNN model was trained to detect hands in images and recognize gestures. The model achieved 80.4% validation accuracy and was able to successfully perform operations like opening WhatsApp, PowerPoint and other apps based on detected gestures in real-time. The system provides a cost-effective and contactless way of interacting with computers using hand gestures only.
Security Application for Smart Phones and other Mobile Devices
Gesture phones final
1. Gesture phones
Krishna Kumar.S, Sai Venkata Vinay .C
1st
year- ECE,
Sona College of Technology, Salem, Tamil Nadu.
Abstract: There are thousands of cell
phone models available in the market, all
with varying features in recent years, cell
phones have also seen considerable
progress in terms of user interaction,
evolving all the way from QWERTY keypad
to touch screens, and the next transition in
user interface is gesture recognitions on
Smartphone, such phones are termed as
gesture phones. This document comprises
of gesture control technology which
explains how a Smartphone understands
gestures. The scenarios where smart
phones are operated by gesture recognition
on the day to day basis are also explained.
They are adding a whole new dimension to
multimedia via touch free technology.
Mobile operating like android and windows
8 and so on use gesture recognition with
their own features. With that, this new
experience can be offered to broader
audiences on a wider range of devices.
Gesture phones are enforcing many
innovations on because of its advantages to
mankind. But it’s not so simple for it has
many several challenges which remain a
mystery for gesture recognition. However,
these problems can be overcome with
different tracking and new technologies
with good reasoning. This paper precisely
includes the innovations that can be
implemented for more efficient use of
gesture phones.
1. How a Smartphone
Understands gestures
Gesture recognition is done through a few
types, among them a few are optical
tracking, inertial tracking, and calibration.
The device understands by computing the
position of the gesture, its orientation,
acceleration and also its angular speed. The
information collected is processed and
finally the gesture is recognized and the
necessary response is given. Fig. 1 explains
clearly the model of recognition of gestures
Fig.1: Prototype of gesture phones[1]
2. on Smart phones.
1.1 Optical Tracking
The gestures are tracked by analyzing the
variations in the color of each and every
pixel recorded through one or more
cameras. The different movement is
recognized by the camera and compares it
with saved gestures while the phone is in a
steady position and it gives vibration. This
buzz indicates that the movement has been
recognized. The gesture is saved and
implemented to carry out the corresponding
task(s) you have attached to its profile.[3]
There are three common technologies that
can acquire optical tracking that is 3-d
images, each with its own advantages.
Stereoscopic vision, structured light pattern
and time of flight (TOF) among which
stereoscopic vision is ideal for Smartphone,
tablets and other consumer devices. The
analysis of these 3-d images brings 3-d
technology into reality.[4]
1.1.1 Stereoscopic vision
It uses two cameras to obtain a left and right
stereo image. As the computer compares the
two different images, it develops a disparity
image that computes the displacement of the
objects in the images.
The views from each camera are different; it
becomes possible to determine the distance
to scene points by triangulation. Essentially,
if we can identify a pair of pixels that image
the same 3D point, one in the left camera
image and the other in the right image, then
the 3D coordinates of the point can be
calculated as the intersection of light rays
from that point to each of the pixels.
Fig.2: a rock on the surface of Mars, as imaged
by a stereo pair on one of the Mars Exploration
Rovers. Both the original (typically left camera)
intensity image and a false-color “elevation
map” image are shown.[1]
1.1.2 Pros and cons of stereoscopic
vision technology
Stereoscopic vision technology requires
amount of software complexity for highly
precise 3D depth data that can be processed
and analyzed in real time by digital signal
processors (DSPs).[1] Errors in camera
alignment as well as insufficient lighting
leads to significant errors in the calculation
of depth values. Precise camera
synchronization is required if the object is in
motion.
Advantages of the sensors are the use of
well established hardware (2D-cameras)
with a wide range of capabilities. Cost
effective and fit in a small form factor,
making them a suitable for Smartphone,
tablets and other consumer devices. It
3. cannot deliver high accuracy and response
time.
1.1.3 Triangulation
The coordinates and distance to a point can
be found by calculating the length of one
side of a triangle, given measurements of
angles and sides of the triangles formed by
that point and two other known reference
points.
Fig.3: two cameras focusing on the same point
1.1.3.1 Calculation:
𝒍 =
𝒅
𝒕𝒂𝒏𝜶
+
𝒅
𝒕𝒂𝒏𝜷
Therefore,
𝟏
𝒅
=
𝟏
𝒍
(
𝟏
𝒕𝒂𝒏𝜶
+
𝟏
𝒕𝒂𝒏𝜷
)
Using the trigonometric identities,
𝒕𝒂𝒏 𝜶 =
𝒔𝒊𝒏 𝜶
𝒄𝒐𝒔 𝜶
and
𝒔𝒊𝒏(𝜶 + 𝜷) = 𝒔𝒊𝒏 𝜶 𝒄𝒐𝒔 𝜷 + 𝒔𝒊𝒏 𝜷 𝒄𝒐𝒔 𝜶
This is equivalent to:
𝟏
𝒅
=
𝒔𝒊𝒏(𝜶 + 𝜷)
𝒍 𝒔𝒊𝒏 𝜶 𝒔𝒊𝒏 𝜷
From this way, it is easy to determine the
distance of the unknown point from
observation point, its north or south and east
or west offsets from the observation point,
finally its full coordinates.
1.2 Inertial Tracking
The motion of Smartphone and similar
devices is tracked with high precision,
without depending on external structure or
prior knowledge of the environment of
usage.
The camera was assumed to have a global
shutter, where all the pixels in an image are
captured at the same time. But cameras for
inertial tracking use CMOS sensors with
rolling shutters, capturing each row of pixels
at slightly different time instant. By this way
the variation in the position of the pixels in
comparison with the image with normal
shutters, the Smartphone understands its
own motions.[2]
These motions are recognized as inputs for
which the response is to perform some task.
Fig.4: Example of an image taken using rolling
shutters.[2]
4. Fig.5: These motions are recognized as inputs for
which the response is to perform some task.
Different movements are saved and each of them
can perform functions.
2. Cases of Gesture Recognition
Technology
Gesture recognition technology would be
widely spread and used in future on mobile
phones as a common feature in them. A few
examples of cases, which are enhancing the
user experience compared to what is
available today, are listed below as follows:
1. We can answer or unanswered an
incoming call with a wave of the hand while
driving and can make outgoing calls
similarly. This feature is termed as call
control. This comes under optical tracking
2. We can skip tracks on your media player
while listening songs using simple hand
motions either optically or inertial or two
dimensionally.
3. We can even operate the other devices
without using their remote control but by
using gesture phones.
4. We can turn down or increase the volume
phone or switch off the mobile through it.
5. The most interesting feature at future on
mobile phones would be browsing
WebPages with the hand movements
without operating a phone
6. We can scroll web pages, or within an
eBook with simple left and right hand
gestures.
7. We can switch off the mobile phone,
mute it or can change to vibration mode
through gestures.
8. Another interesting use case is when
using the Smartphone as a media hub; a user
can dock the device to the TV and watch
content from the device- while controlling
the content in a touch-free manner from a far
position.
Amongst the above mentioned cases, a few
are available in the market as a feature in
phones that come under the labels like
iPhone, Samsung, micromax, Kinect, Lava,
QUALCOMM, etc. These mentioned cases
are ideal when touching the device is a
barrier such as when hands are wet, with
5. gloves, dirty etc. (we all are familiar with
the annoying smudges on the screen from
touching). Moreover, these are done either
by two dimension gesture recognition or
optically, in an inertial way.
3. Applications of gesture
technology on android and windows
phones
The few above mentioned cases are inbuilt
features in mobile phones but a few are not
inbuilt in them. In order to overcome this
problems and give more emphasis on
gesture tool. Software developers have
developed and coined some apps which can
be operated on mobile OS’s. The apps which
are brilliant in use and usage are listed
below but for them to operate we need front
view camera at most one or sensors in them.
Of course, all most all smart phones have
them. Point Grab’s [5] solution is ideal for
use with tablets and smartphones in two
primary scenarios: when operating the
device closely without the possibility of
physically touching the screen (i.e. hands are
not clean), or when the user wishes to watch
the device content on a large screen that is
connected to the device. In both cases, Point
Grab’s solution brings next generation hand
gesture technology with gestural
interfaces to a diverse range of applications.
Air Swiper is one of the most feature rich
apps in this set. This application allows you
to work more effectively and faster with
your phone. It has a number of features
including unlocking and locking the device,
controlling SMS and sound control.
Hovering Controls is one other such app
which costs $1.34 and you can set it up to
launch predetermined apps by hovering over
the sensor, swiping once, or swiping twice.
Some of the things you can do with this app
include silencing an alarm, controlling
media playback like videos or photos with
just gestures. [9]
3.1 Modes of two dimensional app
The app has two modes. The Target mode
which opens a pre-determined app with a set
gesture and the carousel mode, which allows
you to select from a set list of apps. Scribble
to open any app-Google Gesture Search is
an app that has been around for some time
and even though it requires you to actually
touch the screen it is a really useful app. The
app allows users to quickly access contacts,
applications, settings, music and bookmarks
on your Android device by just drawing
letters or numbers on the screen. The app is
self- learning and becomes more useful the
more you use it.
4. Benefits of gesture technology
As gesture technology is a high level
processing vision algorithm. There are
various benefits available for this gesture
architecture and these benefits helped the
researchers to coin many innovations and
develop applications. These benefits are:
1. This gesture technology enables a
flexible programming environment to
the user.
2. It is very user friendly as it provides
multiple tasking, multiple programming,
6. multiple sharing, multiple instructions,
and multiple data transmission.
3. These gestures help in paralysing the
data and task with throughput which
includes fast prototyping and
optimisation.
4. Moreover, this gesture phone would be
highly portable than any other device.
As there are benefits, cons would also be
there running back of it.
5. Challenges of gesture
technology
1. The entire gesture technology depends
on compiler’s performance if he is slow,
then efficiency in fast prototyping would
decrease and may lead to misconception in
programming for what we program is what
we get.
2. Optical tracking consumes battery
highly due to high clock cycle so it affects
the fair performance.
3. If the inter processor is of low
standard then memory access would be
inefficient.
4. Optical tracking requires a camera and
with good camera resolution. More over this
may require good consistent lighting. Items
in the background or distinct features of the
users may make recognition more difficult.
5. In periods of prolonged use of hand
movements, may lead to disease called
gorilla arm[6] that is users’ arms began to
feel fatigue and/or discomfort.
These cons can be overcome but it requires
ultrasonic waves, which is called as
ultrasonic tracking. This feature in mobile
phones would be the future innovation.
6. Innovations:
Ultrasonic waves[7][8] can be used
for gesture recognition where it contains
sensor and speakers which could produce
these waves and sensors would sense the
change in amplitude and follow the
command based on the profile given to it
.Since battery consumption is low and can’t
be affected by light. It can widely be used
like operating a machine far away from us.
Infrared waves are also used for
gesture recognition but only for smaller
applications which can be achieved by
phone because infrared can’t travel through
obstacles where as there is no such problem
arises in ultrasonic waves but it produces
intense heat when passed through obstacle
but can be overcome.
The Smartphone can pause sending
sound signals where we close the cell with
hand while someone else is talking. This
prevents the person on the other side from
entering into speakers personal issues.
Sometimes people really don’t want
to reveal their background during video
chats. We can use the depth estimation
techniques to recognize the background and
only send a blurred or blackened or different
background.
The Smartphone can understand
stealing gesture and can actually alarm you
7. about the burglar. This way it keeps itself in
safe hands.
7. Conclusions:
Gesture phones can recognise gestures by
two methods, optical and inertial tracking.
Optical tracking uses triangulation method
for the estimation of details including the
depth of the object. Inertial tracking is based
on the idea of rolling shutters. The most
widely accepted innovations on gesture
phones are also mentioned. Their
applications in android and windows phones
along with different modes of app are
explained. Challenges the gesture phones
will face are described. Considering
different areas where this technology can be
implemented for efficient use of
Smartphone, few innovations are stated.
References:
1. BongWhan Choe, Jun-Ki Min, and Sung-
Bae Cho; Online Gesture Recognition for
User Interface.
2. Mingyang Li, Byung Hyung Kim and
Anastasios I. Mourikis; Real-time Motion
Tracking on a Cellphone using Inertial
Sensing and a Rolling-Shutter Camera.
3. Mingyu Chen, Ghassan AlRegib, Senior
Member, IEEE, and Biing-Hwang Juang,
Fellow, IEEE; Feature Processing and
Modeling for 6D Motion Gesture
Recognition.
4. Dong-ik ko, Lead engineer, gesture
recognition and depth –sensing gaurav
agarwal, Manager, Gesture recognition and
depth-sensing; Gesture recognition:
Enabling natural interactions with
electronics.
5. Innovations on gesture technology,
http://www.pointgrab.com/276/gesture-
mobile/
6. Diseases related to gesture recognition on
phones.http://www.incosecc.org/http:/ww
w.incosecc.org/images/2012_01_18_Gestu
re-Recognition.pdf
7. Ultrasonic waves usage in gesture phones
http://phys.org/news/2013-11-spinoff-
ultrasonic-gesture-recognition-small.html
8. Ultrasonic waves usage in gesture phones
http://www.washington.edu/news/2014/02/
27/battery-free-technology-brings-gesture-
recognition-to-all-devices/
9. Li yin Kong 2009127643; supervisor: dr.
Kenneth Wong; fyp12026 gesture
recognition on Smartphone