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» Adaptation of SIFT Features for Robust Face Recognition
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IBPRIA
2005
Springer
13 years 11 months ago
Monte Carlo Localization Using SIFT Features
The ability of finding its situation in a given environment is crucial for an autonomous agent. While navigating through a space, a mobile robot must be capable of finding its lo...
Arturo Gil, Óscar Reinoso, Maria Asunci&oac...
CVPR
2006
IEEE
14 years 7 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang
MM
2010
ACM
462views Multimedia» more  MM 2010»
13 years 6 months ago
KPB-SIFT: a compact local feature descriptor
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
Gangqiang Zhao, Ling Chen, Gencai Chen, Junsong Yu...
IBPRIA
2009
Springer
13 years 10 months ago
Gender Recognition from a Partial View of the Face Using Local Feature Vectors
This paper proposes a gender recognition scheme focused on local appearance-based features to describe the top half of the face. Due to the fact that only the top half of the face ...
Yasmina Andreu, Ramón Alberto Mollineda, Pe...
CVPR
2005
IEEE
13 years 11 months ago
The Distinctiveness, Detectability, and Robustness of Local Image Features
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
Gustavo Carneiro, Allan D. Jepson