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An object recognition approach based on structural feature for cluttered indoor scene
Yuan WB(袁文博); Cao ZQ(曹志强); Zhao P(赵鹏); Tan M(谭民); Yang YQ(杨月全); Yuan WB(袁文博)
2014
会议名称The 11th IEEE International Conference on Networking, Sensing and Control
会议录名称Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control
会议日期2014
会议地点Miami, United States
摘要In this paper, aiming at the indoor scene under monitoring by visual sensor network (VSN), an object recognition approach based on structural feature is presented. Firstly, we regard the output of existing line segment detector LSD with proper parameters as the preliminary extraction result and it still will be further restored and split. Then, we give an inference model based on structural features of object including line segment ontology characteristics and relative relationship between the line segments. Finally, the objects are recognized with position information through inference. The effectiveness of the approach is verified, and the results show that our approach does not rely on segmentation and has robustness on partial defect and structural deformation to some extent.
关键词Indoor Scene Object Recognition Visual Sensor Network Structural Feature Inference Model
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11723
专题复杂系统认知与决策实验室_先进机器人
通讯作者Yuan WB(袁文博)
推荐引用方式
GB/T 7714
Yuan WB,Cao ZQ,Zhao P,et al. An object recognition approach based on structural feature for cluttered indoor scene[C],2014.
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