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» Boosting Object Detection Using Feature Selection
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ICPR
2008
IEEE
15 years 8 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock
DIS
2010
Springer
14 years 12 months ago
Sparse Substring Pattern Set Discovery Using Linear Programming Boosting
In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem ...
Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Mas...
FGR
2006
IEEE
173views Biometrics» more  FGR 2006»
15 years 8 months ago
Facial Feature Detection and Tracking with Automatic Template Selection
We describe an accurate and robust method of locating facial features. The method utilises a set of feature templates in conjunction with a shape constrained search technique. The...
David Cristinacce, Timothy F. Cootes
ICCV
2007
IEEE
16 years 3 months ago
N3M: Natural 3D Markers for Real-Time Object Detection and Pose Estimation
In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and relia...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...
ICIP
2009
IEEE
14 years 11 months ago
Effective image splicing detection based on image chroma
A color image splicing detection method based on gray level cooccurrence matrix (GLCM) of thresholded edge image of image chroma is proposed in this paper. Edge images are generat...
Wei Wang, Jing Dong, Tieniu Tan