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Content Provider | IEEE Xplore Digital Library |
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Author | Grabner, M. Grabner, H. Bischof, H. |
Copyright Year | 2007 |
Description | Author affiliation: Graz Univ. of Technol., Graz (Grabner, M.; Grabner, H.; Bischof, H.) |
Abstract | We treat tracking as a matching problem of detected key-points between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to incorporate background information. Contrary to existing approaches, we are able to start tracking of the object from scratch requiring no off-line training phase before tracking. The tracker is initialized by a region of interest in the first frame. Afterwards an on-line boosting technique is used for learning descriptions of detected keypoints lying within the region of interest. New frames provide new samples for updating the classifiers which increases their stability. A simple mechanism incorporates temporal information for selecting stable features. In order to ensure correct updates a verification step based on estimating homographies using RANSAC is performed. The approach can be used for real-time applications since on-line updating and evaluating classifiers can be done efficiently. |
Starting Page | 1 |
Ending Page | 8 |
File Size | 9354496 |
Page Count | 8 |
File Format | |
ISBN | 1424411793 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2007.382995 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-06-17 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Target tracking Boosting Layout Karhunen-Loeve transforms Classification tree analysis Computer graphics Stability Design methodology Robustness Shape |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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