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Tracking Revisited using RGBD Camera: Unified Benchmark and Baselines
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| Citations: | 7 - 1 self |
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@MISC{Song_trackingrevisited,
author = {Shuran Song and Jianxiong Xiao},
title = {Tracking Revisited using RGBD Camera: Unified Benchmark and Baselines},
year = {}
}
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Abstract
Despite significant progress, tracking is still considered to be a very challenging task. Recently, the increased popularity of depth sensors has made it possible to obtain reliable depth easily. This may be a game changer for tracking, since depth can be used to prevent model drift and handle occlusion. We also observe that current tracking algorithms are mostly evaluated on a very small number of videos collected and annotated by different groups. The lack of a reasonable size and consistently constructed benchmark has prevented a persuasive comparison among different algorithms. In this paper, we construct a unified benchmark dataset of 100 RGBD videos with high diversity, propose different kinds of RGBD tracking algorithms using 2D or 3D model, and present a quantitative comparison of various algorithms with RGB or RGBD input. We aim to lay the foundation for further research in both RGB and RGBD tracking, and will make our dataset as well as evaluation server available online. 1.
Keyphrases
rgbd camera reasonable size various algorithm handle occlusion evaluation server available online current tracking algorithm rgbd video persuasive comparison unified benchmark dataset different algorithm rgbd input reliable depth increased popularity depth sensor high diversity rgbd tracking small number different kind different group model drift significant progress challenging task quantitative comparison game changer
