2017
DOI: 10.1108/ir-03-2017-0042
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A target tracking and location robot system based on omnistereo vision

Abstract: Purpose Because of their large field of view, omnistereo vision systems have been widely used as primary vision sensors in autonomous mobile robot tasks. The purpose of this article is to achieve real-time and accurate tracking by the omnidirectional vision robot system. Design/methodology/approach The authors provide in this study the key techniques required to obtain an accurate omnistereo target tracking and location robot system, including stereo rectification and target tracking in complex environment. … Show more

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Cited by 4 publications
(3 citation statements)
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“…So, the vision system based on the catadioptric omnidirectional camera is carried on the mobile robot to percept surroundings in this paper. Detailed imaging theory is introduced in our previous work [29, 30].…”
Section: Methodsmentioning
confidence: 99%
“…So, the vision system based on the catadioptric omnidirectional camera is carried on the mobile robot to percept surroundings in this paper. Detailed imaging theory is introduced in our previous work [29, 30].…”
Section: Methodsmentioning
confidence: 99%
“…The relation of the essential matrix and the fundamental matrix is: where and are the intrinsic parameters of the two images. The decomposition of an essential matrix is: where and differ by a scale factor which can be calculated using two 3D points offline [ 35 ]. According to (9) and (10), (8) can be written as: …”
Section: Methodsmentioning
confidence: 99%
“…1 By detecting and identifying video content, people can quickly access key information in video content and use this key information to help people solve many of the problems they face today. 2 The main research work is to use the deep learning network model to identify the key content in the video by identifying the content in the video. It mainly introduces from the aspects of video data preprocessing, data augmentation, feature extraction, feature aggregation and multimodal feature fusion.…”
Section: Introductionmentioning
confidence: 99%