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» Models from image triplets using epipolar gradient features
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ICPR
2008
IEEE
16 years 24 days ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
CVIU
2006
76views more  CVIU 2006»
14 years 11 months ago
Homeostatic image perception: An artificial system
This paper describes how a visual system can automatically define features of interest from the observation of a large enough number of natural images. The principle complements t...
Thomas Feldman, Laurent Younes
IVC
2002
132views more  IVC 2002»
14 years 11 months ago
Structure and motion estimation from apparent contours under circular motion
In this paper we address the problem of recovering structure and motion from the apparent contours of a smooth surface. Fixed image features under circular motion and their relati...
Kwan-Yee Kenneth Wong, Paulo R. S. Mendonça...
CVPR
2000
IEEE
16 years 1 months ago
A Curve Evolution Approach to Smoothing and Segmentation Using the Mumford-Shah Functional
In this work, we approach the classic Mumford-Shah problem from a curve evolution perspective. In particular, we let a given family of curves define the boundaries between regions...
Andy Tsai, Anthony J. Yezzi, Alan S. Willsky
ICCV
2011
IEEE
13 years 11 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry