TY - GEN
T1 - Recognition and visual learning of articulated shape by accumulative Hopfield matching
AU - Li, W. J.
AU - Lee, T.
PY - 2001
Y1 - 2001
N2 - In this paper, we describe a system that can recognize and learn visual model of an articulated object automatically given different views of the object, provided that the local structure is unchanged. The system is based on the Hopfield style network to find the feature correspondences between different views of an articulated object. With this proposed matching system, we can finally learn the relationship between articulated parts of the object with the poses detected. Experiments on real images show the effectiveness of the proposed system.
AB - In this paper, we describe a system that can recognize and learn visual model of an articulated object automatically given different views of the object, provided that the local structure is unchanged. The system is based on the Hopfield style network to find the feature correspondences between different views of an articulated object. With this proposed matching system, we can finally learn the relationship between articulated parts of the object with the poses detected. Experiments on real images show the effectiveness of the proposed system.
UR - https://www.scopus.com/pages/publications/0034869894
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0034869894&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
VL - 3
SP - 2153
EP - 2158
BT - Proceedings of the International Joint Conference on Neural Networks
T2 - International Joint Conference on Neural Networks (IJCNN'01)
Y2 - 15 July 2001 through 19 July 2001
ER -