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» Localizing Objects while Learning Their Appearance
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ICIP
2005
IEEE
14 years 9 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang
AAAI
2004
13 years 9 months ago
Rapid Object Recognition from Discriminative Regions of Interest
Object recognition and detection represent a relevant component in cognitive computer vision systems, such as in robot vision, intelligent video surveillance systems, or multi-mod...
Gerald Fritz, Christin Seifert, Lucas Paletta, Hor...
TMI
2011
147views more  TMI 2011»
13 years 2 months ago
Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model
Abstract—Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements ...
Raja' S. Alomari, Jason J. Corso, Vipin Chaudhary
ICCV
2009
IEEE
13 years 5 months ago
SURF Tracking
Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motionbased trackin...
Wei He, Takayoshi Yamashita, Hongtao Lu, Shihong L...
APIN
1998
132views more  APIN 1998»
13 years 7 months ago
Evolution-Based Methods for Selecting Point Data for Object Localization: Applications to Computer-Assisted Surgery
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
Shumeet Baluja, David Simon