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ICCV
2009
IEEE
15 years 3 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
15 years 23 days ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
GIS
2009
ACM
16 years 6 months ago
Sea Floor Bathymetry Trackline Surface Fitting Without Visible Artifacts Using ODETLAP
High quality, artifact-free fitting a bathymetry (sea-floor) surface to very unevenly spaced depth data from ship tracklines is possible with ODETLAP (Overdetermined Laplacian Par...
Tsz-Yam Lau, W. Randolph Franklin, You Li, Zhongyi...
ACCV
2009
Springer
16 years 10 days ago
Image-Set Based Face Recognition Using Boosted Global and Local Principal Angles
Face recognition using image-set or video sequence as input tends to be more robust since image-set or video sequence provides much more information than single snapshot about the ...
Xi Li, Kazuhiro Fukui, Nanning Zheng
APIN
1998
132views more  APIN 1998»
15 years 5 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