NDLI: Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions

Content Provider	IEEE Xplore Digital Library
Author	Chaudhry, R. Ravichandran, A. Hager, G. Vidal, R.
Copyright Year	2009
Description	Author affiliation: Center for Imaging Sci., Johns Hopkins Univ., Baltimore, MD, USA (Chaudhry, R.; Ravichandran, A.; Hager, G.; Vidal, R.)
Abstract	System theoretic approaches to action recognition model the dynamics of a scene with linear dynamical systems (LDSs) and perform classification using metrics on the space of LDSs, e.g. Binet-Cauchy kernels. However, such approaches are only applicable to time series data living in a Euclidean space, e.g. joint trajectories extracted from motion capture data or feature point trajectories extracted from video. Much of the success of recent object recognition techniques relies on the use of more complex feature descriptors, such as SIFT descriptors or HOG descriptors, which are essentially histograms. Since histograms live in a non-Euclidean space, we can no longer model their temporal evolution with LDSs, nor can we classify them using a metric for LDSs. In this paper, we propose to represent each frame of a video using a histogram of oriented optical flow (HOOF) and to recognize human actions by classifying HOOF time-series. For this purpose, we propose a generalization of the Binet-Cauchy kernels to nonlinear dynamical systems (NLDS) whose output lives in a non-Euclidean space, e.g. the space of histograms. This can be achieved by using kernels defined on the original non-Euclidean space, leading to a well-defined metric for NLDSs. We use these kernels for the classification of actions in video sequences using (HOOF) as the output of the NLDS. We evaluate our approach to recognition of human actions in several scenarios and achieve encouraging results.
Starting Page	1932
Ending Page	1939
File Size	1721934
Page Count	8
File Format	PDF
ISBN	9781424439928
ISSN	10636919
DOI	10.1109/CVPR.2009.5206821
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Nonlinear optics Image motion analysis Kernel Nonlinear dynamical systems Humans Data mining Layout Feature extraction Object recognition
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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