Revisiting robust visual tracking using pixel-wise posteriors
Schubert F, Casaburo D, Dickmanns D, Belagiannis V (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9163
Pages Range: 275-288
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Copenhagen
ISBN: 9783319209036
DOI: 10.1007/978-3-319-20904-3_26
Abstract
In this paper we present an in-depth evaluation of a recently published tracking algorithm [6] which intelligently couples rigid-registration and color-based segmentation using level-sets. The original method did not arouse the deserved interest in the community, most likely due to challenges in reimplementation and the lack of a quantitative evaluation. Therefore, we reimplemented this baseline approach, evaluated it on state-of-the-art datasets (VOT and OOT) and compared it to alternative segmentation-based tracking algorithms. We believe this is a valuable contribution as such a comparison is missing in the literature. The impressive results help promoting segmentation-based tracking algorithms, which are currently under-represented in the visual tracking benchmarks. Furthermore, we present various extensions to the color model, which improve the performance in challenging situations such as confusions between fore-and background. Last, but not least, we discuss implementation details to speed up the computation by using only a sparse set of pixels for the propagation of the contour, which results in tracking speed of up to 200 Hz for typical object sizes using a single core of a standard 2. 3GHz CPU.
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Germany (DE)How to cite
APA:
Schubert, F., Casaburo, D., Dickmanns, D., & Belagiannis, V. (2015). Revisiting robust visual tracking using pixel-wise posteriors. In Antonios Gasteratos, Lazaros Nalpantidis, Volker Kruger, Jan-Olof Eklundh (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 275-288). Copenhagen, DK: Springer Verlag.
MLA:
Schubert, Falk, et al. "Revisiting robust visual tracking using pixel-wise posteriors." Proceedings of the 10th International Conference on Computer Vision Systems, ICVS 2015, Copenhagen Ed. Antonios Gasteratos, Lazaros Nalpantidis, Volker Kruger, Jan-Olof Eklundh, Springer Verlag, 2015. 275-288.
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