Revisiting Robust Visual Tracking Using Pixel-Wise Posteriors
In this paper we present an in-depth evaluation of a recently published tracking algorithm by Bibby et al. (Robust Real-Time Visual Tracking using Pixel-Wise Posteriors, ECCV, 2008) 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 200Hz for typical object sizes using a single core of a standard 2.3 GHz CPU. Contact: Falk Schubert, Airbus Group Innovations (falk.schubert@airbus.com)Paper
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F. Schubert, D. Casaburo, D. Dickmanns, V. Belagiannis
Revisiting Robust Visual Tracking Using Pixel-Wise Posteriors 10th International Conference on Computer Vision Systems (ICVS), 6-9 July, 2015, Copenhagen, Denmark (bib) |
Earlier Work: PaFiSS
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V. Belagiannis, F. Schubert, N. Navab, S. Ilic
Segmentation Based Particle Filtering for Real-Time 2D Object Tracking 12th European Conference on Computer Vision (ECCV), Firenze, Italy, October 07-13, 2012 (bib) |
