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» Graph-Theoretical Methods in Computer Vision
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CVPR
2005
IEEE
16 years 12 days ago
Nonlinear Face Recognition Based on Maximum Average Margin Criterion
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
Baochang Zhang, Xilin Chen, Shiguang Shan, Wen Gao
ICPR
2002
IEEE
15 years 11 months ago
Detecting a Gazing Region by Visual Direction and Stereo Cameras
We develop a wearable vision system that consists of a user’s visual direction sensor and stereo cameras. First, we establish a method for calibrating the system so that it can ...
Akihiro Sugimoto, Akihiro Nakayama, Takashi Matsuy...
CVPR
2012
IEEE
13 years 9 months ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...
CVPR
2009
IEEE
17 years 1 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CVPR
2000
IEEE
16 years 8 months ago
Representation and Recognition of Complex Human Motion
The quest for a vision system capable of representing and recognizing arbitrary motions benefits from a low dimensional, non-specific representation of flow fields, to be used in ...
Jesse Hoey, James J. Little