NDLI: Correlated probabilistic trajectories for pedestrian motion detection

Content Provider	IEEE Xplore Digital Library
Author	Perbet, Frank Maki, Atsuto Stenger, Bjorn
Copyright Year	2009
Description	Author affiliation: Toshiba Research Europe, Cambridge Research Laboratory, USA (Perbet, Frank; Maki, Atsuto; Stenger, Bjorn)
Abstract	This paper introduces an algorithm for detecting walking motion using point trajectories in video sequences. Given a number of point trajectories, we identify those which are spatio-temporally correlated as arising from feet in walking motion. Unlike existing techniques we do not assume clean point tracks but instead propose “probabilistic trajectories” as new features to classify. These are extracted from directed acyclic graphs whose edges represent temporal point correspondences and are weighted with their matching probability in terms of appearance and location. This representation tolerates the inherent trajectory ambiguity, for example due to occlusions. We then learn the correlation between the movement of two feet using a random forest classifier. The effectiveness of the algorithm is demonstrated in experiments on image sequences captured with a static camera.
Starting Page	1647
Ending Page	1654
File Size	2771821
Page Count	8
File Format	PDF
ISBN	9781424444205
ISSN	15505499
DOI	10.1109/ICCV.2009.5459372
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-29
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Motion detection Legged locomotion Trajectory Image sequences Tracking Feature extraction Computer vision Foot Video sequences Cameras
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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