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» Randomness and Geometric Features in Computer Vision
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ICCV
2011
IEEE
12 years 7 months ago
Local Intensity Order Pattern for Feature Description
This paper presents a novel method for feature description based on intensity order. Specifically, a Local Intensity Order Pattern(LIOP) is proposed to encode the local ordinal i...
Zhenhua Wang, Bin Fan, Fuchao Wu
CVPR
2008
IEEE
14 years 9 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
CVPR
2007
IEEE
14 years 9 months ago
Cast Shadow Removal Combining Local and Global Features
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM t...
Zhou Liu, Kaiqi Huang, Tieniu Tan, Liangsheng Wang
ICCV
2007
IEEE
14 years 9 months ago
Probabilistic Color and Adaptive Multi-Feature Tracking with Dynamically Switched Priority Between Cues
We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
François Le Clerc, Lionel Oisel, Patrick P&...
ICPR
2008
IEEE
14 years 2 months ago
Model-based visual self-localization using geometry and graphs
In this paper, a geometric approach for global selflocalization based on a world-model and active stereo vision is introduced. The method uses class specific object recognition a...
David Israel Gonzalez-Aguirre, Tamim Asfour, Eduar...