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Erschienen in:
2013 | OriginalPaper | Buchkapitel
MATRIOSKA: A Multi-level Approach to Fast Tracking by Learning
verfasst von : Mario Edoardo Maresca, Alfredo Petrosino
Erschienen in: Image Analysis and Processing – ICIAP 2013
Verlag: Springer Berlin Heidelberg
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In this paper we propose a novel framework for the detection and tracking in real-time of unknown object in a video stream. We decompose the problem into two separate modules: detection and learning. The detection module can use multiple keypoint-based methods (ORB, FREAK, BRISK, SIFT, SURF and more) inside a fallback model, to correctly localize the object frame by frame exploiting the strengths of each method. The learning module updates the object model, with a growing and pruning approach, to account for changes in its appearance and extracts negative samples to further improve the detector performance. To show the effectiveness of the proposed tracking-by-detection algorithm, we present quantitative results on a number of challenging sequences where the target object goes through changes of pose, scale and illumination.