NDLI: Fast visual people tracking using a feature-based people detector

Content Provider	IEEE Xplore Digital Library
Author	Konigs, Achim Schulz, Dirk
Copyright Year	2011
Description	Author affiliation: Unmanned Systems Group, Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE, 53343 Wachtberg, Germany (Konigs, Achim; Schulz, Dirk)
Abstract	This article presents a new technique to visual people tracking that combines feature-based object detection with feature tracking. In comparison to tracking by detection techniques which are frequently employed by feature-based approaches, the explicit tracking of detected features achieves a speed up of the overall tracking process and allows to adapt the chosen features on-line; this way, the tracker can specialize itself to tracking a specific object and gain an improved robustness in multi-object scenarios. Our approach uses a fast version of an implicit shape model detector (ISM) trained on people to initially find a person. The tracking process itself is then based on tracking the features found by the detector. Features are tracked by carrying out a correspondence search from frame to frame in combination with a voting scheme for determining a person's center position in the image. The approach does not require a motion model for the objects and is robust against bumpy or jerky motions of the camera. To further improve robustness, the feature set is continuously updated in order to adapt to changes in appearance. Experiments show that the proposed system is able to track multiple people. It also can re-identify persons after periods of occlusion and distinguish them from each other, even if they are looking similar. The system was tested on the BoBoT dataset and on a small mobile robot following a person traversing rough grassland.
Starting Page	3614
Ending Page	3619
File Size	2050983
Page Count	6
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094902
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Feature extraction Tracking Cameras Mobile robots Robustness Training
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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