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Accurate object recognition with assembling appearance and motion information
Chang, Yongxin1,2,3; Yu, Huapeng1,2,3; Xu, Zhiyong1; Zhang, Jing2; Gao, Chunming2
Source PublicationMathematical Problems in Engineering
Volume2014Pages:195941
2014
Language英语
ISSN1024123X
DOI10.1155/2014/195941
Indexed BySCI ; Ei
WOS IDWOS:000345040300001
Subtype期刊论文
AbstractHow to effectively detect object and accurately give out its visible parts is a major challenge for object detection. In this paper we propose an explicit occlusion model through integrating appearance and motion information. The model combines together two parts: part-level object detection with single frame and object occlusion estimation with continuous frames. It breaks through the performance bottleneck caused by lack of information and effectively improves object detection rate under severe occlusion. Through reevaluating the semantic parts, the detecting performance of partial object detectors is largely enhanced. The explicit model enables the partial detectors to have the capability of occlusion estimation. By discarding the geometric representation in rigid single-angle perspective and applying effective pattern of objective shape, our proposed approaches greatly improve the performance and robustness of similarity measurement. For validating the performance of proposed methods, we designed a comparative experiment on challenging pedestrian frame sequences database. The experimental results on challenging pedestrian frame sequence demonstrate that, compared to the traditional algorithms, the methods proposed in this paper have significantly improved the detection rate for severe occlusion. Furthermore, it also can achieve better localization of semantic parts and estimation of occluding.; How to effectively detect object and accurately give out its visible parts is a major challenge for object detection. In this paper we propose an explicit occlusion model through integrating appearance and motion information. The model combines together two parts: part-level object detection with single frame and object occlusion estimation with continuous frames. It breaks through the performance bottleneck caused by lack of information and effectively improves object detection rate under severe occlusion. Through reevaluating the semantic parts, the detecting performance of partial object detectors is largely enhanced. The explicit model enables the partial detectors to have the capability of occlusion estimation. By discarding the geometric representation in rigid single-angle perspective and applying effective pattern of objective shape, our proposed approaches greatly improve the performance and robustness of similarity measurement. For validating the performance of proposed methods, we designed a comparative experiment on challenging pedestrian frame sequences database. The experimental results on challenging pedestrian frame sequence demonstrate that, compared to the traditional algorithms, the methods proposed in this paper have significantly improved the detection rate for severe occlusion. Furthermore, it also can achieve better localization of semantic parts and estimation of occluding.
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Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/5074
Collection光电探测与信号处理研究室(五室)
Corresponding AuthorChang, Yongxin
Affiliation1. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China
2. School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China
3. Graduate University, Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Chang, Yongxin,Yu, Huapeng,Xu, Zhiyong,et al. Accurate object recognition with assembling appearance and motion information[J]. Mathematical Problems in Engineering,2014,2014:195941.
APA Chang, Yongxin,Yu, Huapeng,Xu, Zhiyong,Zhang, Jing,&Gao, Chunming.(2014).Accurate object recognition with assembling appearance and motion information.Mathematical Problems in Engineering,2014,195941.
MLA Chang, Yongxin,et al."Accurate object recognition with assembling appearance and motion information".Mathematical Problems in Engineering 2014(2014):195941.
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