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Conference Paper Patched-based Deep Boltzmann Shape Priors for Visual Tracking
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Authors
Sanghoon Lee, Shin Il Hong, Rhee Eun Jun, Lee Sunghee, Lee Nam Kyung
Issue Date
201710
Source
International Conference on Information and Communication Technology Convergence (ICTC) 2017, pp.1110-1112
DOI
https://dx.doi.org/10.1109/ICTC.2017.8190869
Project Code
17HR1800, Development of Digilog Signage System on Non-planar Screen, Lee Nam Kyung
Abstract
In this paper, we propose a patched-based deep Boltzmann shape priors for visual tracking. The shape priors are generated from deep Boltzmann machine network. The network consists of three layers of hidden and visible units. The generated shapes not only maintain general shapes from a variety of poses, but also entail local modifications with high probability.
KSP Keywords
Deep Boltzmann machine(DBM), Local modifications, Visual Tracking, shape prior, three layers