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EVOW
2010
Springer
15 years 6 months ago
Towards Automated Learning of Object Detectors
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
Marc Ebner
CSUR
2004
149views more  CSUR 2004»
15 years 3 months ago
A review of vessel extraction techniques and algorithms
Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put ...
Cemil Kirbas, Francis K. H. Quek
295
Voted

Book
5396views
17 years 2 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
169
Voted
CVPR
2009
IEEE
16 years 10 months ago
Joint Depth and Alpha Matte Optimization via Fusion of Stereo and Time-of-Flight Sensor
We present a new approach to iteratively estimate both high-quality depth map and alpha matte from a single image or a video sequence. Scene depth, which is invariant to illumin...
Jiejie Zhu (University of Kentucky), Miao Liao (Un...
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
16 years 5 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson