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» Localizing Objects while Learning Their Appearance
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ICIP
2005
IEEE
16 years 3 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
122
Voted
AAAI
2004
15 years 3 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»
14 years 8 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
14 years 11 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...
130
Voted
APIN
1998
132views more  APIN 1998»
15 years 1 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