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» Landmark image retrieval using visual synonyms
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MIR
2006
ACM
145views Multimedia» more  MIR 2006»
14 years 1 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
ETVC
2008
13 years 9 months ago
Abstracts of the LIX Fall Colloquium 2008: Emerging Trends in Visual Computing
s of the LIX Fall Colloquium 2008: Emerging Trends in Visual Computing Frank Nielsen Ecole Polytechnique, Palaiseau, France Sony CSL, Tokyo, Japan Abstract. We list the abstracts o...
Frank Nielsen
CIVR
2010
Springer
247views Image Analysis» more  CIVR 2010»
13 years 2 months ago
Coherent bag-of audio words model for efficient large-scale video copy detection
Current content-based video copy detection approaches mostly concentrate on the visual cues and neglect the audio information. In this paper, we attempt to tackle the video copy d...
Yang Liu, Wanlei Zhao, Chong-Wah Ngo, Changsheng X...
3DPVT
2006
IEEE
194views Visualization» more  3DPVT 2006»
14 years 1 months ago
Histogram Matching for Camera Pose Neighbor Selection
A prerequisite to calibrated camera pose estimation is the construction of a camera neighborhood adjacency graph, a connected graph defining the pose neighbors of the camera set....
Kevin L. Steele, Parris K. Egbert, Bryan S. Morse
CVPR
2000
IEEE
14 years 9 months ago
Improving Visual Matching
Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared di erences ...
Michael S. Lew, Nicu Sebe, Thomas S. Huang