STD: A Stereo Tracking Dataset for Evaluating Binocular Tracking Algorithms
文献类型：会议论文
| 作者 | Zheng Zhu1,2 ; Wei Zou1,2; Qingbin Wang1,2; Feng Zhang1,2
|
| 出版日期 | 2016 |
| 会议日期 | December 3-7, 2016 |
| 会议地点 | Qingdao, China |
| 英文摘要 | In this paper, a Stereo Tracking Dataset is proposed for evaluating binocular tracking algorithms. The dataset contains stereoscopic videos which are collected by our mobile platform in different scenarios and videos that are available publicly. All sequences are carefully synchronized and rectified, and the ground truth of object is annotated by authors. Both raw and processed sequences are provided in the dataset. We also develop a Scalable and Occlusion-aware Multi-cues Correlation Filter Tracker (SOMCFT) and evaluate it on the STD. The SOMCFT framework fuses different clues in confidence map level and uses depth information to handle scale changes and occlusion. Quantitative evaluation on STD demonstrates effectiveness of the proposed dataset. All data, including stereo image pairs, calibrations, annotations and attributes, are available for research purposes and comparative evaluation on https://github.com/zhengzhugithub/StereoTracking. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19779]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 |
| 作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Zheng Zhu,Wei Zou,Qingbin Wang,et al. STD: A Stereo Tracking Dataset for Evaluating Binocular Tracking Algorithms[C]. 见:. Qingdao, China. December 3-7, 2016. |
入库方式： OAI收割
来源：自动化研究所
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