An Elderly Fall Detection System using Depth Images

In this proposed conceptual technique, we have collected the Microsoft Kinect depth images of elderly fall event. After collecting the necessary depth images the background subtraction algorithm has been used to subtract the background and retain the subject. Segmentation and feature selection proce...

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Bibliographic Details
Published in2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) pp. 1 - 4
Main Authors Bundele, Mahesh, Sharma, Harish, Gupta, Mukesh, Sisodia, Pushpendra Singh
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2020
Subjects
Computer Vision
Conferences
Decision Tree
Decision trees
Elderly Fall Detection
Fall detection
Feature extraction
Image segmentation
Kinect
Senior citizens
Technological innovation
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DOI10.1109/ICRAIE51050.2020.9358330

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Summary:In this proposed conceptual technique, we have collected the Microsoft Kinect depth images of elderly fall event. After collecting the necessary depth images the background subtraction algorithm has been used to subtract the background and retain the subject. Segmentation and feature selection process have been applied on various daily activity to train the fall detection model. The model has been train using decision tree. To ensure the fall confidence, ground truthing technique has been used.
DOI:10.1109/ICRAIE51050.2020.9358330