Multiview human activity recognition system based on spatiotemporal template for video surveillance system

Alok Kumar Singh Kushwaha; Rajeev Srivastava

doi:10.1117/1.JEI.24.5.051004

1 September 2015 Multiview human activity recognition system based on spatiotemporal template for video surveillance system

Alok Kumar Singh Kushwaha, Rajeev Srivastava

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 5, 051004 (September 2015). https://doi.org/10.1117/1.JEI.24.5.051004

Abstract

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

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Alok Kumar Singh Kushwaha and Rajeev Srivastava "Multiview human activity recognition system based on spatiotemporal template for video surveillance system," Journal of Electronic Imaging 24(5), 051004 (1 September 2015). https://doi.org/10.1117/1.JEI.24.5.051004

Published: 1 September 2015

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