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» Learning to localize detected objects
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ISBI
2009
IEEE
14 years 4 months ago
Probabilistic Branching Node Detection Using Hybrid Local Features
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
CVPR
2010
IEEE
14 years 6 months ago
Tracking the Invisible: Learning Where the Object Might be
Objects are usually embedded into context. Visual context has been successfully used in object detection tasks, however, it is often ignored in object tracking. We propose a metho...
Helmut Grabner, Jiri Matas, Philippe Cattin, Luc V...
CVPR
2007
IEEE
14 years 12 months ago
Unsupervised Segmentation of Objects using Efficient Learning
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
GECCO
2010
Springer
232views Optimization» more  GECCO 2010»
13 years 11 months ago
Genetic algorithms for automatic classification of moving objects
This paper presents an integrated approach, combining a state-of-the-art commercial object detection system and genetic algorithms (GA)-based learning for automatic object classif...
Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosen...
IVC
2008
101views more  IVC 2008»
13 years 10 months ago
Occlusion analysis: Learning and utilising depth maps in object tracking
Complex scenes such as underground stations and malls are composed of static occlusion structures such as walls, entrances, columns, turnstiles and barriers. Unless this occlusion...
Darrel Greenhill, John-Paul Renno, James Orwell, G...