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» Features for image retrieval: an experimental comparison
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AMR
2007
Springer
197views Multimedia» more  AMR 2007»
16 years 11 days ago
How to Use SIFT Vectors to Analyze an Image with Database Templates
During last years, local image descriptors have received much attention because of their efficiency for several computer vision tasks such as image retrieval, image comparison, fea...
Adrien Auclair, Laurent D. Cohen, Nicole Vincent
TMM
2010
249views Management» more  TMM 2010»
15 years 27 days ago
Bridging the Semantic Gap Between Image Contents and Tags
With the exponential growth of Web 2.0 applications, tags have been used extensively to describe the image contents on the Web. Due to the noisy and sparse nature in the human gene...
Hao Ma, Jianke Zhu, Michael R. Lyu, Irwin King
CVPR
2004
IEEE
16 years 8 months ago
Hidden Semantic Concept Discovery in Region Based Image Retrieval
This paper addresses Content Based Image Retrieval (CBIR), focusing on developing a hidden semantic concept discovery methodology to address effective semanticsintensive image ret...
Ruofei Zhang, Zhongfei (Mark) Zhang
MM
2010
ACM
199views Multimedia» more  MM 2010»
15 years 6 months ago
TOP-SURF: a visual words toolkit
TOP-SURF is an image descriptor that combines interest points with visual words, resulting in a high performance yet compact descriptor that is designed with a wide range of conte...
Bart Thomee, Erwin M. Bakker, Michael S. Lew
ICCV
2007
IEEE
16 years 8 months ago
Feature Preserving Image Smoothing Using a Continuous Mixture of Tensors
Many computer vision and image processing tasks require the preservation of local discontinuities, terminations and bifurcations. Denoising with feature preservation is a challeng...
Özlem N. Subakan, Bing Jian, Baba C. Vemuri, ...