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ICIP
2009
IEEE
13 years 5 months ago
Selecting representative and distinctive descriptors for efficient landmark recognition
To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales a...
Sheng Gao, Joo-Hwee Lim
SMI
2008
IEEE
146views Image Analysis» more  SMI 2008»
14 years 2 months ago
SHREC'08 entry: Local volumetric features for 3D model retrieval
In this paper, we describe a method of shape-based 3D model retrieval that employs a set of 3D, local, multi-scale features extracted from a voxel representation of a 3D model to ...
Kunio Osada, Takahiko Furuya, Ryutarou Ohbuchi
ICIP
2006
IEEE
14 years 9 months ago
Video Scene Retrieval Based on Local Region Features
This paper describes a novel method for content extraction and scene retrieval for video sequences based on local region descriptors. The local invariant features are obtained for...
Arasanathan Anjulan, Cedric Nishan Canagarajah
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
ICDAR
2009
IEEE
14 years 2 months ago
Recognition of Degraded Handwritten Characters Using Local Features
The main problems of Optical Character Recognition (OCR) systems are solved if printed latin text is considered. Since OCR systems are based upon binary images, their results are ...
Markus Diem, Robert Sablatnig