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Informations générales |
| Auteur |
Zhang, Shi-hui; Liu, Jian-xin |
| Publié |
InTech Open Access Publisher, 2012
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| Abstract |
This paper describes a novel self‐occlusion
detection approach for depth image using SVM. This
work is distinguished by three contributions. The first
contribution is the introduction of a new self‐occlusion
detection idea, which takes the self‐occlusion as a
classification problem for the first time, thus the accuracy
of the detection result is improved. The second
contribution is two new self‐occlusion‐related features,
named maximal depth difference and included angle. The
third contribution is a specific self‐occlusion detection
algorithm. Experimental results not only show that the
proposed approach is feasible and effective, but also
show that our works produce better results than those
previously published. |
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International Journal of Advanced Robotic Systems
Auteur: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publié: 2004
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