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CVPR
2012
IEEE
13 years 5 days ago
Discovering localized attributes for fine-grained recognition
Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...
CVPR
2005
IEEE
15 years 11 months ago
Randomized Trees for Real-Time Keypoint Recognition
In earlier work, we proposed treating wide baseline matching of feature points as a classification problem, in which each class corresponds to the set of all possible views of suc...
Vincent Lepetit, Pascal Lagger, Pascal Fua
ICIP
2006
IEEE
15 years 11 months ago
A Hierarchical ASM/AAM Approach in a Stochastic Framework for Fully Automatic Tracking and Recognition
This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two part...
Andre Störmer, Gerhard Rigoll, Sascha Schreib...
ICMCS
2005
IEEE
113views Multimedia» more  ICMCS 2005»
15 years 3 months ago
HMM-Based Deception Recognition from Visual Cues
Behavioral indicators of deception and behavioral state are extremely difficult for humans to analyze. This research effort attempts to leverage automated systems to augment human...
Gabriel Tsechpenakis, Dimitris N. Metaxas, Mark Ad...
ICIAR
2010
Springer
15 years 2 months ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic