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» Generic Object Detection using Model Based Segmentation
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CAIP
2003
Springer
166views Image Analysis» more  CAIP 2003»
15 years 7 months ago
Unsupervised Segmentation Incorporating Colour, Texture, and Motion
Abstract. In this paper we integrate colour, texture, and motion into a segmentation process. The segmentation consists of two steps, which both combine the given information: a pr...
Thomas Brox, Mikaël Rousson, Rachid Deriche, ...
ICCV
2003
IEEE
16 years 4 months ago
Inferring 3D Structure with a Statistical Image-Based Shape Model
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...
132
Voted
ISBI
2009
IEEE
15 years 9 months ago
A New Interactive Method for Coronary Arteries Segmentation Based on Tubular Anisotropy
In this paper we present a new interactive method for tubular structure extraction. The main application and motivation for this work is vessel tracking in 3D medical images. The ...
Fethallah Benmansour, Laurent D. Cohen
125
Voted
ICPR
2006
IEEE
16 years 3 months ago
Object Detection in Video via Particle Filters
We propose an object detection method using particle filters. Our approach estimates the probability of object presence in the current image given the history of observations up t...
Jacek Czyz
170
Voted
ACL
2006
15 years 4 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...