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» Unsupervised Learning of Invariant Features Using Video
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CVPR
2003
IEEE
14 years 9 months ago
Video-Based Face Recognition Using Adaptive Hidden Markov Models
While traditional face recognition is typically based on still images, face recognition from video sequences has become popular recently. In this paper, we propose to use adaptive...
Xiaoming Liu 0002, Tsuhan Chen
ICPR
2010
IEEE
13 years 6 months ago
Unsupervised Learning from Linked Documents
Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the uns...
Zhen Guo, Shenghuo Zhu, Yun Chi, Zhongfei Zhang, Y...
CVPR
2009
IEEE
15 years 2 months ago
Topology Dictionary with Markov Model for 3D Video Content-Based Skimming and Description
This paper presents a novel approach to skim and describe 3D videos. 3D video is an imaging technology which consists in a stream of 3D models in motion captured by a synchronized ...
Tony Tung (Kyoto University), Takashi Matsuyama (K...
WAPCV
2004
Springer
14 years 1 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
Muhua Li, James J. Clark
ICPR
2006
IEEE
1292views computer vision» more  ICPR 2006»
14 years 8 months ago
Learning-Based License Plate Detection Using Global and Local Features
This paper proposes a license plate detection algorithm using both global statistical features and local Haar-like features. Classifiers using global statistical features are cons...
Huaifeng Zhang, Qiang Wu, Wenjing Jia, Xiangjian H...