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» Application of Level Set Methods in Computer Vision
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CVPR
2004
IEEE
16 years 9 months ago
Super-Resolution through Neighbor Embedding
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...
Hong Chang, Dit-Yan Yeung, Yimin Xiong
CVPR
2008
IEEE
16 years 9 months ago
Structure learning in random fields for heart motion abnormality detection
Coronary Heart Disease can be diagnosed by assessing the regional motion of the heart walls in ultrasound images of the left ventricle. Even for experts, ultrasound images are dif...
Glenn Fung, Kevin Murphy, Mark Schmidt, Róm...
CVPR
2010
IEEE
16 years 27 days ago
Cascaded L1-norm Minimization Learning (CLML) Classifier for Human Detection
This paper proposes a new learning method, which integrates feature selection with classifier construction for human detection via solving three optimization models. Firstly, the ...
Ran Xu, Baochang Zhang, Qixiang Ye, jian bin Jiao
ACCV
2009
Springer
16 years 6 days ago
Multilevel Algebraic Invariants Extraction by Incremental Fitting Scheme
Algebraic invariants extracted from coefficients of implicit polynomials (IPs) have been attractive because of its convenience for solving the recognition problem in computer visio...
Bo Zheng, Jun Takamatsu, Katsushi Ikeuchi
ICPR
2010
IEEE
15 years 5 months ago
Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling
We propose a region-based foreground object segmentation method capable of dealing with image sequences containing noise, illumination variations and dynamic backgrounds (as often...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell