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Human Activity Recognition in RGB-D Videos by Dynamic Images by Mukherjee, Snehasis; Anvitha, Leburu; Lahari, T. Mohana is a scholarly article available to read on EtoBox.

What is Human Activity Recognition in RGB-D Videos by Dynamic Images about?

Human Activity Recognition in RGB-D videos has been an active research topic during the last decade. However, no efforts have been found in the literature, for recognizing human activity in RGB-D videos where several performers are performing simultaneously. In this paper we introduce such a challenging dataset with several performers performing the activities. We present a novel method for recognizing human activities in such videos. The proposed method aims in capturing the motion information of the whole video by producing a dynamic image corresponding to the input video. We use two parallel ResNext-101 to produce the dynamic images for the RGB video and depth video separately. The dynamic images contain only the motion information and hence, the unnecessary background information are eliminated. We send the two dynamic images extracted from the RGB and Depth videos respectively, through a fully connected layer of neural networks. The proposed dynamic image reduces the complexity of the recognition process by extracting a sparse matrix from a video. However, the proposed system maintains the required motion information for recognizing the activity. The proposed method has been t

Author

Mukherjee, Snehasis; Anvitha, Leburu; Lahari, T. Mohana

Published

2018

Language

EN