STD: A Stereo Tracking Dataset for Evaluating Binocular Tracking Algorithms

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	STD: A Stereo Tracking Dataset for Evaluating Binocular Tracking Algorithms
	Zheng Zhu1,2 ; Wei Zou1,2 ; Qingbin Wang1,2 ; Feng Zhang1,2
	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.
内容类型	会议论文
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.