Title

Trajectory Rectification And Path Modeling For Video Surveillance

Abstract

Path modeling for video surveillance is an active area of research. We address the issue of Euclidean path modeling in a single camera for activity monitoring in a multicamera video surveillance system. The paper proposes (i) a novel linear solution to auto-calibrate any camera observing pedestrians and (ii) to use these calibrated cameras to detect unusual object behavior. During the unsupervised training phase, after auto-calibrating a camera and metric rectifying the input trajectories, the input sequences are registered to the satellite imagery and prototype path models are constructed. This allows us to estimate metric information directly from the video sequences. During the testing phase, using our simple yet efficient similarity measures, we seek a relation between the input trajectories derived from a sequence and the prototype path models. We test the proposed method on synthetic as well as on real-world pedestrian sequences. ©2007 IEEE.

Publication Date

12-1-2007

Publication Title

Proceedings of the IEEE International Conference on Computer Vision

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ICCV.2007.4409008

Socpus ID

50649086381 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/50649086381

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