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97
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ICCV
2001
IEEE
16 years 2 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black
141
Voted
ICIAP
2005
ACM
15 years 6 months ago
Markovian Energy-Based Computer Vision Algorithms on Graphics Hardware
This paper shows how Markovian segmentation algorithms used to solve well known computer vision problems such as motion estimation, motion detection and stereovision can be signi...
Pierre-Marc Jodoin, Max Mignotte, Jean-Franç...
95
Voted
ECCV
2010
Springer
15 years 1 months ago
Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision
The saddle point framework provides a convenient way to formulate many convex variational problems that occur in computer vision. The framework unifies a broad range of data and re...
Jan Lellmann, Dirk Breitenreicher, Christoph Schn&...
81
Voted
ICTAI
2003
IEEE
15 years 5 months ago
Interactive Open Architecture Computer Vision
In this paper, design and implementation of an interactive open architecture computer vision software package called Ch OpenCV is presented. Benefiting from both Ch and OpenCV, C...
Qingcang Yu, Harry H. Cheng, Wayne W. Cheng, Xiaod...
75
Voted
CVIU
2008
75views more  CVIU 2008»
15 years 14 days ago
Performance characterization in computer vision: A guide to best practices
It is frequently remarked that designers of computer vision algorithms and systems cannot reliably predict how algorithms will respond to new problems. A variety of reasons have b...
Neil A. Thacker, Adrian F. Clark, John L. Barron, ...