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» Object recognition and Random Image Structure Evolution
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CVPR
2001
IEEE
14 years 8 months ago
Mixtures of Trees for Object Recognition
Efficient detection of objects in images is complicated by variations of object appearance due to intra-class object differences, articulation, lighting, occlusions, and aspect va...
Sergey Ioffe, David A. Forsyth
ICIAR
2009
Springer
13 years 4 months ago
Invariant Shape Matching for Detection of Semi-local Image Structures
Abstract. Shape features applied to object recognition has been actively studied since the beginning of the field in 1950s and remain a viable alternative to appearance based metho...
Lech Szumilas, Horst Wildenauer, Allan Hanbury
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 8 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ICMCS
2006
IEEE
143views Multimedia» more  ICMCS 2006»
14 years 23 days ago
Object Recognition and Recovery by Skeleton Graph Matching
This paper presents a robust and efficient skeleton-based graph matching method for object recognition and recovery applications. The novel feature is to unify both object recogni...
Lei He, Chia Y. Han, William G. Wee
IJCV
2006
115views more  IJCV 2006»
13 years 6 months ago
Object Recognition as Many-to-Many Feature Matching
Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation e...
M. Fatih Demirci, Ali Shokoufandeh, Yakov Keselman...