From Virtual to Real World: Applying Animation to Design the Activity Recognition System (CHI2021 LBW)
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This document discusses using virtual simulation and animation to help design activity recognition systems. It allows testing different sensor positions virtually before collecting real sensory data. The system uses Unity 3D to simulate sensor data streams and test classifiers. This provides accuracy feedback to help evaluate different sensor placements. The virtual sensors and trained classifiers can then be applied to a real activity recognition system. Case studies show applications for daily activity, exercise, and motion recognition with customizable sensor positions. The virtual approach aims to improve the process of designing human activity recognition systems.
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Location-based applications require knowing the user position constantly in order to find out and provide information about user’s context. There is a need for new methods that calculate the location of users in indoor environments using smartphone sensors. In this presentation the authors (Laia Descamps-Vila, Antoni Perez-Navarro, Jordi Conesa) address that problem by presenting two methods that estimate the user position through a smartphone.Real Time Object Dectection using machine learning
This document discusses the development of a real-time object detection system using computer vision techniques. It aims to recognize and label moving objects in video streams from monitoring cameras with high accuracy and in a short amount of time. The system will use a hybrid model of convolutional neural networks and support vector machines for feature extraction and classification of objects from camera feeds into predefined classes. It is intended to help analyze surveillance video by only flagging clips that contain objects of interest like people or vehicles, reducing wasted storage and review time.
slide-171212080528.pptx
This document summarizes a project on real-time object detection using computer vision techniques. It discusses using a system that can recognize objects in a video stream from a camera and label them with bounding boxes and labels. It notes that most video surveillance footage is uninteresting unless there are moving objects. The project aims to address this by building an accurate, fast object detection system that can run on resource-constrained devices. It proposes using a hybrid CNN-SVM model trained on a large dataset to recognize objects and discusses the training and detection phases of the system.
Towards Rapid Implementation of Adaptive Robotic Systems
Current automation design practice produces expensive one-of-a-kind installations where the system cannot be easily modified to
meet changing demands or advancements in technology. It is imperative that we design robot systems to be modular, portable and
easily re-configurable in order to reduce the design lead times and life cycle costs of providing automation alternatives.
The Unified Tele-robotics Architecture Program (UTAP) was developed under the sponsorship of the US Air Force Robotics and
Automation Center of Excellence. A goal of the program was to define and develop prototypes of commonly used software building
blocks for sensor guided real time embedded control of telerobotic devices. Standard building blocks and a non-proprietary
communication protocols would provide the Air Force and specifically the Logistic Centers with a support infrastructure designed to
rapidly and efficiently build and maintain mission critical automation systems.
IRJET= Air Writing: Gesture Recognition using Ultrasound Sensors and Grid-Eye...
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Internet of Things: Energy Efficient Public Sensing
I am Rashed Hossain Miraj, master student at the University of Stuttgart, Germany. I covered the topic as part of my degree requirement.
“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...
“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...Edge AI and Vision Alliance
The document discusses sensor fusion techniques for accurately perceiving objects in the environment. It describes sensor fusion as combining data from multiple sensors to produce more accurate, reliable and complete information. It covers types of sensors including passive sensors like cameras and active sensors like LiDAR. It also discusses challenges in sensor fusion and algorithms like Kalman and particle filters. Centralized and decentralized fusion architectures are described as well as metrics for evaluating fusion approaches.NERC_panoptes_final2
The document describes Panoptes, a dynamic and easy to deploy motion capture system created by researchers at the University at Buffalo. The system uses multiple sensors like Microsoft Kinects to accurately estimate the 3D pose of objects in a scene. It aims to be flexible, dynamic, and cost effective. The system has been tested using sensors like Kinects along with techniques like April Tags and Point Cloud Library for object detection. Future work will focus on developing optimized methods to derive 3D pose from multiple sensors assuming spatial continuity.
Sensor Cloud
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Deep VO and SLAM IV
SLAM, VO ,VIO, deep learning, CNN, RNN, LSTM, end-to-end, supervised, unsupervised, GAN, monocular, stereo, depth, pose, camera, tracking
Track 1 session 1 - st dev con 2016 - contextual awareness
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Rule-based Real-Time Activity Recognition in a Smart Home Environment
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using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system
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Virtual Yoga System Using Kinect Sensor
The document describes a virtual yoga system using the Microsoft Kinect sensor. The system aims to make yoga exercises more engaging and motivating for patients by tracking their poses in real-time and providing feedback. It recognizes skeleton joints and yoga postures using the Kinect's depth sensing capabilities. Voice instructions guide users through different poses. The system is intended to address issues with traditional physiotherapy being tedious and repetitive. It allows customizing exercises to individual needs and challenges. Recognizing poses accurately in real-time could help patients perform exercises correctly and consistently at home without direct supervision.
JPN1414 Distributed Deployment Algorithms for Improved Coverage in a Networ...
Get the latest IEEE ns2 projects in JP INFOTECH; we are having following category wise projects like Industrial Informatics, Vehicular Technology, Networking, WSN and Manet.
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/ns2-projects/
Similar to From Virtual to Real World: Applying Animation to Design the Activity Recognition System (CHI2021 LBW) (20)
RSS and Sensor Fusion Algorithms for Indoor Location Systems on Smartphones
RSS and Sensor Fusion Algorithms for Indoor Location Systems on Smartphones
Real Time Object Dectection using machine learning
Real Time Object Dectection using machine learning
Towards Rapid Implementation of Adaptive Robotic Systems
Towards Rapid Implementation of Adaptive Robotic Systems
IRJET= Air Writing: Gesture Recognition using Ultrasound Sensors and Grid-Eye...
IRJET= Air Writing: Gesture Recognition using Ultrasound Sensors and Grid-Eye...
Internet of Things: Energy Efficient Public Sensing
Internet of Things: Energy Efficient Public Sensing
“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...
“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...
Track 1 session 1 - st dev con 2016 - contextual awareness
Track 1 session 1 - st dev con 2016 - contextual awareness
Rule-based Real-Time Activity Recognition in a Smart Home Environment
Rule-based Real-Time Activity Recognition in a Smart Home Environment
JPN1414 Distributed Deployment Algorithms for Improved Coverage in a Networ...
JPN1414 Distributed Deployment Algorithms for Improved Coverage in a Networ...
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プレイマットのパターン生成支援ツールの評価
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プレイマットのパターン生成支援ツール
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SkinRing: 装着方向に依らない指側面でのジェスチャ入力可能なリング型デバイス
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バイオリンの運弓動作計測による初心者と経験者の差異分析
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Converting Tatamis into Touch Sensors by Measuring Capacitance
This document summarizes a research paper that proposes a method to convert tatami floor mats into touch sensors by measuring capacitance. Conductive sheets are placed under the tatami surface. When a person contacts the tatami, capacitance is measured between the sheets and their skin to detect the touch position. The system identifies 12 hand gestures with approximately 90% accuracy. Future work includes enabling multi-touch detection and using the sensors for footprint tracking and pose estimation.
Pinch Force Measurement Using a Geomagnetic Sensor
This document proposes measuring pinch force using the geomagnetic sensor in a smartphone. A device with embedded magnets and springs is attached to the smartphone. As force is applied, the magnet's distance from the sensor changes, altering the magnetic flux density. Measurements found a strong correlation between force and magnetic flux density. Future work includes testing different smartphone models and collecting user feedback to improve usability.
Smartphone-Based Teaching System for Neonate Soothing Motions
This document describes a proposed smartphone-based teaching system to help first-time caregivers learn how to properly soothe neonates. The system uses sensors in a stuffed toy and a smartphone to capture posture angles and acceleration during cradling motions. It provides real-time feedback on the user's form compared to expert cradling motions. An experiment tested the system's effectiveness in improving users' cradling posture after training compared to just watching a video. Results showed the system helped users better match the expert's inclination angle, indicating it could help ensure neonate safety by teaching proper neck support. Future work is needed to improve measurement accuracy and further validate the system.
Tactile Presentation of Orchestral Conductor's Motion Trajectory
This document proposes presenting a conductor's motion trajectory tactilely for visually impaired musicians using vibrators. It describes capturing conducting movements, mapping them to vibrators, and using tactile apparent movement. An experiment found trajectory presentation helped predict beat timing better than single vibrations, especially for tempo changes and start cues. Future work includes developing a universal device.
TouchLog: Finger Micro Gesture Recognition Using Photo-Reflective Sensors
The researchers developed a fingernail-sized device using 7 photo-reflective sensors to detect finger microgestures based on fingertip skin deformation. They implemented a random forest classifier to recognize 11 gestures with an average accuracy of 91.1% for the general model and 91.5% for the individual model. Future work will focus on addressing limitations like user dependence and developing a device that can be worn comfortably for real-world use.
Seeing the Wind: An Interactive Mist Interface for Airflow Input
Human activities can introduce variations in various environmental cues, such as light and sound, which can serve as inputs for interfaces. However, one often overlooked aspect is the airflow variation caused by these activities, which presents challenges in detection and utilization due to its intangible nature. In this paper, we have unveiled an approach using mist to capture invisible airflow variations, rendering them detectable by Time-of-Flight (ToF) sensors. We investigate the capability of this sensing technique under different types of mist or smoke, as well as the impact of airflow speed. To illustrate the feasibility of this concept, we created a prototype using a humidifier and demonstrated its capability to recognize motions. On this basis, we introduce potential applications, discuss inherent limitations, and provide design lessons grounded in mist-based airflow sensing.
Identification and Authentication Using Clavicles
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Yohei Kawasaki, Yuta Sugiura
2023 62nd Annual Conference of the Society of Instrument and Control Engineers (SICE), Mie, Japan, 2023
Estimation of Violin Bow Pressure Using Photo-Reflective Sensors
Estimation of Violin Bow Pressure Using Photo-Reflective Sensors presents a method for quantitatively estimating bow pressure during violin playing using photo-reflective sensors attached to the bow. Five sensors measure the distance between the bow stick and hair, which changes with applied pressure. A random forest regression model is trained on sensor distance values and actual pressure measurements to estimate pressure based solely on sensor values. In experiments, the model estimated bow pressure with an R2 of 0.84, MAE of 0.11N, and MAPE of 19.1% when tested on data from an experienced violinist. The goal is to provide visual feedback to support practice by quantifying bow pressure.
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ヒアラブルへの入力を想定したユーザ定義型ジェスチャ調査と IMUセンサによる耳タッチジェスチャの認識
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Smartphone-Based Teaching System for Neonate Soothing Motions
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Tactile Presentation of Orchestral Conductor's Motion Trajectory
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TouchLog: Finger Micro Gesture Recognition Using Photo-Reflective Sensors
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Overview
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Paper Link: https://eprint.iacr.org/2024/257
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- 1. From Virtual to Real World: Applying Animation to Design the Activity Recognition System Keio University Chengshuo Xia, Sugiura Yuta Late Breaking Work
- 2. • Data-driven Human Activity Recognition (HAR) system relies on the training dataset which is collected from the significant signal variation regions. • Such regions limited the flexibility to alter the sensor position. • Change the position requires the system to re-collect the sensory data from desired position. 2 Background Specific position sensory data collection HAR Training Application
- 3. • A virtual platform combined with sensor simulation to design the non-visual HAR systems. • Provide the accuracy as the feedback of examined positions via cross-validation. • Virtual sensor can be tested to check the corresponding accuracy. • Classifier interface trained by simulation signal can be generated forwarding to the real activity recognition. 3 System
- 4. UNITY 3D based platform • Input data stream: • Generated from Xsens MVN taken by subjects. • Sensor Simulation: • HAR system based on virtual dataset: • Down-sampled to decrease frame rate influence • Segmentation • Augmentation 4 System
- 5. • Case-a: Wearable acceleromters system for daily activity recognition Testing & Application Several types of daily activity recognition with an accelerometer worn on the body. User can have customized demand of sensor position and activity recognized.
- 6. • Case-b: Wearable distance sensor system for exercises recognition Testing & Application Design a wearable distance sensor system which the sensor is attached on the lower limbs of an individual.
- 7. • Case-c: Distance sensing system for motion recognition in a bathroom Testing & Application Distance map into grayscale figure
- 8. • Result: Testing & Application
- 9. 9 Conclusion • Virtual simulation environment to produce the simulated multi- modal sensor data. • Drop back the position choice to the end-user side. • Arbitrarily to place the sensor in the virtual scenario. • Combine with virtual sensory, improve the process of HAR system design. • Recognize the activity in the real-world • Future work: • Virtual motion generator • VR/AR combined for serious/somatosensory game
- 10. Thank you very much!