Volumetric 3D Tracking by Detection

Huang CH, Allain B, Franco JS, Navab N, Ilic S, Boyer E (2016)

Publication Type: Conference contribution

Publication year: 2016

Journal

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society; 1999

Publisher: IEEE Computer Society

Book Volume: 2016-December

Pages Range: 3862-3870

Conference Proceedings Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Event location: Las Vegas, NV, USA

ISBN: 9781467388504

DOI: 10.1109/CVPR.2016.419

Abstract

In this paper, we propose a new framework for 3D tracking by detection based on fully volumetric representations. On one hand, 3D tracking by detection has shown robust use in the context of interaction (Kinect) and surface tracking. On the other hand, volumetric representations have recently been proven efficient both for building 3D features and for addressing the 3D tracking problem. We leverage these benefits by unifying both families of approaches into a single, fully volumetric tracking-by-detection framework. We use a centroidal Voronoi tessellation (CVT) representation to compactly tessellate shapes with optimal discretization, construct a feature space, and perform the tracking according to the correspondences provided by trained random forests. Our results show improved tracking and training computational efficiency and improved memory performance. This in turn enables the use of larger training databases than state of the art approaches, which we leverage by proposing a cross-tracking subject training scheme to benefit from all subject sequences for all tracking situations, thus yielding better detection and less overfitting.

Involved external institutions

University of Grenoble Alpes (UGA) / Université de Grenoble

France (FR) Technische Universität München (TUM)

Germany (DE)

How to cite

APA:

Huang, C.-H., Allain, B., Franco, J.-S., Navab, N., Ilic, S., & Boyer, E. (2016). Volumetric 3D Tracking by Detection. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3862-3870). Las Vegas, NV, USA: IEEE Computer Society.

MLA:

Huang, Chun-Hao, et al. "Volumetric 3D Tracking by Detection." Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA IEEE Computer Society, 2016. 3862-3870.

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