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CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 9 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
CVPR
2003
IEEE
14 years 9 months ago
Multi-scale Phase-based Local Features
Local feature methods suitable for image feature based object recognition and for the estimation of motion and structure are composed of two steps, namely the `where' and `wh...
Gustavo Carneiro, Allan D. Jepson
ICCV
2007
IEEE
14 years 9 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
ICPR
2008
IEEE
14 years 8 months ago
Local shape features for object recognition
We present a shape matching algorithm based on the chamfer distance transform which can be easily integrated into the well-known SIFT framework. The shape matching was designed to...
Bernd Heisele, Carlos Rocha
EPIA
2009
Springer
13 years 11 months ago
Semantic Image Search and Subset Selection for Classifier Training in Object Recognition
Abstract. Robots need to ground their external vocabulary and internal symbols in observations of the world. In recent works, this problem has been approached through combinations ...
Rui Pereira, Luís Seabra Lopes, Augusto Sil...