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FGR
2000
IEEE
150views Biometrics» more  FGR 2000»
15 years 8 months ago
From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination
Image variability due to changes in pose and illumination can seriously impair object recognition. This paper presents appearance-based methods which, unlike previous appearance-b...
Athinodoros S. Georghiades, Peter N. Belhumeur, Da...
216
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ICIP
2010
IEEE
15 years 1 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
CVPR
2008
IEEE
16 years 5 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
226
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AVBPA
2005
Springer
583views Biometrics» more  AVBPA 2005»
15 years 9 months ago
A Survey of 3D Face Recognition Methods
Many researches in face recognition have been dealing with the challenge of the great variability in head pose, lighting intensity and direction,facial expression, and aging. The m...
Alize E. H. Scheenstra, Arnout Ruifrok, Remco C. V...
ACCV
2007
Springer
15 years 9 months ago
Object Detection Combining Recognition and Segmentation
Abstract. We develop an object detection method combining top-down recognition with bottom-up image segmentation. There are two main steps in this method: a hypothesis generation s...
Liming Wang, Jianbo Shi, Gang Song, I-fan Shen