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» Illumination Invariant Unsupervised Segmenter
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ICPR
2010
IEEE
13 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
CVPR
2009
IEEE
1848views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Moving Cast Shadow Detection using Physics-based Features
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...
Jia-Bin Huang and Chu-Song Chen
CVPR
2012
IEEE
11 years 10 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
BMVC
1998
13 years 9 months ago
Color Invariant Snakes
Snakes provide high-level information in the form of continuity constraints and minimum energy constraints related to the contour shape and image features. These image features ar...
Theo Gevers, Sennay Ghebreab, Arnold W. M. Smeulde...
ICPR
2008
IEEE
14 years 8 months ago
Object recognition and segmentation using SIFT and Graph Cuts
In this paper, we propose a method of object recognition and segmentation using Scale-Invariant Feature Transform (SIFT) and Graph Cuts. SIFT feature is invariant for rotations, s...
Akira Suga, Keita Fukuda, Tetsuya Takiguchi, Yasuo...