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» A probabilistic framework for image segmentation
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ICCV
2005
IEEE
14 years 1 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla
NIPS
2008
13 years 9 months ago
Cascaded Classification Models: Combining Models for Holistic Scene Understanding
One of the original goals of computer vision was to fully understand a natural scene. This requires solving several sub-problems simultaneously, including object detection, region...
Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daph...
IJCV
2006
115views more  IJCV 2006»
13 years 7 months ago
Object Recognition as Many-to-Many Feature Matching
Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation e...
M. Fatih Demirci, Ali Shokoufandeh, Yakov Keselman...
PAMI
2010
225views more  PAMI 2010»
13 years 2 months ago
Semi-Supervised Classification via Local Spline Regression
Abstract--This paper presents local spline regression for semisupervised classification. The core idea in our approach is to introduce splines developed in Sobolev space to map the...
Shiming Xiang, Feiping Nie, Changshui Zhang
ECCV
2002
Springer
14 years 9 months ago
Neuro-Fuzzy Shadow Filter
In video sequence processing, shadow remains a major source of error for object segmentation. Traditional methods of shadow removal are mainly based on colour difference threshold...
Benny P. L. Lo, Guang-Zhong Yang