Journal ArticleDOI
Robust Video Surveillance for Fall Detection Based on Human Shape Deformation
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TLDR
A new method is proposed to detect falls by analyzing human shape deformation during a video sequence, which gives very good results (as low as 0% error with a multi-camera setup) compared with other common image processing methods.Abstract:
Faced with the growing population of seniors, developed countries need to establish new healthcare systems to ensure the safety of elderly people at home. Computer vision provides a promising solution to analyze personal behavior and detect certain unusual events such as falls. In this paper, a new method is proposed to detect falls by analyzing human shape deformation during a video sequence. A shape matching technique is used to track the person's silhouette along the video sequence. The shape deformation is then quantified from these silhouettes based on shape analysis methods. Finally, falls are detected from normal activities using a Gaussian mixture model. This paper has been conducted on a realistic data set of daily activities and simulated falls, and gives very good results (as low as 0% error with a multi-camera setup) compared with other common image processing methods.read more
Citations
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Journal ArticleDOI
Wear‐free indoor fall detection based on RFID and deep residual networks
TL;DR: In this article , a fall detection approach based on RFID is proposed, where noncontact passive tags are used to construct an array of tags and an action segmentation algorithm is designed to quickly extract human action information based on the short-term variance change of the phase signal.
Book ChapterDOI
A Real-Time Fall Classification Model Based on Frame Series Motion Deformation
Nasim Hajari,Irene Cheng +1 more
TL;DR: In this article , the authors proposed a robust, real-time, computer vision based fall detection technique that can work in different settings, such as indoor environments with different lighting conditions and different viewing directions of the camera.
Journal ArticleDOI
A Cost-Effective Fall-Detection Framework for the Elderly Using Sensor-Based Technologies
Ch. Anwar ul Hassan,Faten Khalid Karim,Assad Abbas,Jawaid Iqbal,Hela Elmannai,Saddam Hussain,Syed Sajid Ullah,Muhammad Sufyan Khan +7 more
TL;DR: In this paper , the authors used pyroelectric infrared sensors (PIRs) mounted on walls around or near the patient bed in a horizontal field of view to detect regular motions and patient fall events; they used PIR sensors along with Arduino Uno to detect patient falls and save the collected data in Arduino SD for classification.
Book ChapterDOI
RGB-D Sensors and Signal Processing for Fall Detection
TL;DR: An overview of the RGB-D sensors mostly used in fall detection applications, by discussing their main properties and the modalities by which they have been used and installed, and the main depth signal processing approaches according to the sensor usage, and what type of information can be extracted from them are provided.
Proceedings ArticleDOI
Fall Detection & Daily Living Activity Recognition using CNN
TL;DR: In this paper , a deep learning-based automated fall detection solution is proposed, where a collection of carefully chosen characteristics acquired by tracking human body silhouettes are input into a CNN-based classifier.
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