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» Models from image triplets using epipolar gradient features
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ICPR
2008
IEEE
14 years 8 months 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»
13 years 7 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»
13 years 7 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
14 years 9 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
12 years 7 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