NDLI: Frequencygrams and multi-feature joint sparse representation for action and gesture recognition

Content Provider	IEEE Xplore Digital Library
Author	Sandhan, Tushar Choi, Jin Young
Copyright Year	2014
Description	Author affiliation: Perception and Intelligence Laboratory, Department of Electrical and Computer Engineering, ASRI, Seoul National University, Seoul, Republic of Korea (Sandhan, Tushar; Choi, Jin Young)
Abstract	Features play a vital role in human action recognition (HAR), as they encapsulate the underlying dynamics of the action. We propose the features (frequencygrams) based on frequency domain analysis of histograms of the motion and its spatiotemporal gradient (rate of change in motion flow). Feature extraction is quite simple and can be performed in real time using sparse or interest point motion flow. They are resilient to delayed initiated actions, scale variation, moving background, sudden illumination changes (high frequency noise) and avoid the overload of person detection and tracking. Being robust to camera motions, they also provide a natural, compact and discriminative representation for reciprocating motions by preserving comprehensive temporal information of the action sequences. As other global features also bear some action semantics, we fuse all these features together in a systematic way to improve the overall HAR performance, by employing the joint sparse representation with group sparsity regularization. The extensive experimental results, on three benchmark action datasets and one gesture recognition dataset, show the effectiveness and generality of the proposed method.
Starting Page	1450
Ending Page	1454
File Size	830434
Page Count	5
File Format	PDF
ISBN	9781479957514
DOI	10.1109/ICIP.2014.7025290
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Hafnium Cameras Dynamics Legged locomotion Joints Semantics video analysis Sparse representation activity recognition histogram feature gesture recognition
Content Type	Text
Resource Type	Article

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