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» A tensorial framework for color images
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VIP
2003
13 years 9 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin
CVPR
2011
IEEE
12 years 11 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
CVPR
2001
IEEE
14 years 9 months ago
A Bayesian Approach to Digital Matting
This paper proposes a new Bayesian framework for solving the matting problem, i.e. extracting a foreground element from a background image by estimating an opacity for each pixel ...
Yung-Yu Chuang, Brian Curless, David Salesin, Rich...
ICIP
2009
IEEE
13 years 5 months ago
Joint deconvolution and demosaicing
We present a new method to jointly perform deblurring and colordemosaicing of RGB images. Our method is derived following an inverse problem approach in a MAP framework. To avoid ...
Ferréol Soulez, Eric Thiébaut
TIP
2010
129views more  TIP 2010»
13 years 2 months ago
Image Segmentation by MAP-ML Estimations
Abstract--Image segmentation plays an important role in computer vision and image analysis. In this paper, image segmentation is formulated as a labeling problem under a probabilit...
Shifeng Chen, Liangliang Cao, Yueming Wang, Jianzh...