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WACV
2005
IEEE
15 years 5 months ago
Incorporating Background Invariance into Feature-Based Object Recognition
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
Andrew N. Stein, Martial Hebert
IJCV
2002
157views more  IJCV 2002»
14 years 11 months ago
Dense Features for Semi-Dense Stereo Correspondence
We present a new feature based algorithm for stereo correspondence. Most of the previous feature based methods match sparse features like edge pixels, producing only sparse dispar...
Olga Veksler
ICIP
2009
IEEE
16 years 25 days ago
Ppiq: A Probabilistic Framework For Image Quality Assessment
In this paper a framework for Image Quality Assessment (IQA) is introduced based on the properties of Receptive Fields (RFs) which are the primary mechanism for detection of visua...
MICAI
2000
Springer
15 years 3 months ago
Detection and Tracking of Facial Features in Video Sequences
This work presents a real time system for detection and tracking of facial features in video sequences. Such system may be used in visual communication applications, such as teleco...
Rogério Schmidt Feris, Teófilo Em&ia...
ICPR
2008
IEEE
15 years 6 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock