Co-operative multi-target tracking and classification
Date
2004
Authors
Kumar, P.
Ranganath, S.
Sengupta, K.
Weimin, H.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Co-operative Multi-Target Tracking and Classification. Computer vision, ECCV 2004 : 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004 : proceedings / Tomáš Pajdla, Jiří Matas, (eds.) : pp. 376 - 389
Statement of Responsibility
Pankaj Kumar, Surendra Ranganath, Kuntal Sengupta and Huang Weimin
Conference Name
European Conference on Computer Vision (8th : 2004 : Prague, Czech Republic)
Abstract
This paper describes a real-time system for multi-target tracking and classification in image sequences from a single stationary camera. Several targets can be tracked simultaneously in spite of splits and merges amongst the foreground objects and presence of clutter in the segmentation results. In results we show tracking of upto 17 targets simultaneously. The algorithm combines Kalman filter-based motion and shape tracking with an efficient pattern matching algorithm. The latter facilitates the use of a dynamic programming strategy to efficiently solve the data association problem in presence of multiple splits and merges. The system is fully automatic and requires no manual input of any kind for initialization of tracking. The initialization for tracking is done using attributed graphs. The algorithm gives stable and noise free track initialization. The image based tracking results are used as inputs to a Bayesian network based classifier to classify the targets into different categories. After classification a simple 3D model for each class is used along with camera calibration to obtain 3D tracking results for the targets. We present results on a large number of real world image sequences, and accurate 3D tracking results compared with the readings from the speedometer of the vehicle. The complete tracking system including segmentation of moving targets works at about 25Hz for 352×288 resolution color images on a 2.8 GHz pentium-4 desktop.
School/Discipline
Dissertation Note
Provenance
Description
The original publication can be found at www.springerlink.com