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133
Voted
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 7 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
121
Voted
CVPR
2004
IEEE
16 years 4 months ago
Value Directed Learning of Gestures and Facial Displays
This paper presents a method for learning decision theoretic models of facial expressions and gestures from video data. We consider that the meaning of a facial display or gesture...
Jesse Hoey, James J. Little
CVPR
2005
IEEE
16 years 4 months ago
Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
Qifa Ke, Takeo Kanade
107
Voted
CVPR
2006
IEEE
16 years 4 months ago
Vertical Parallax from Moving Shadows
This paper presents a method for capturing and computing 3D parallax. 3D parallax, as used here, refers to vertical offset from the ground plane, height. The method is based on an...
Yaron Caspi, Michael Werman
116
Voted
ICCV
2003
IEEE
16 years 4 months ago
Dense Shape Reconstruction of a Moving Object under Arbitrary, Unknown Lighting
We present a method for shape reconstruction from several images of a moving object. The reconstruction is dense (up to image resolution). The method assumes that the motion is kn...
Denis Simakov, Darya Frolova, Ronen Basri