CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
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
Conference NameThe 11th IEEE International Conference on Networking, Sensing and Control
Source PublicationProceedings of the 11th IEEE International Conference on Networking, Sensing and Control
Conference Date2014
Conference PlaceMiami, United States
AbstractIn 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.
KeywordIndoor Scene Object Recognition Visual Sensor Network Structural Feature Inference Model
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11723
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorYuan WB(袁文博)
Recommended Citation
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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