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» The Dark Side of Object Learning: Learning Objects
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ICCV
2007
IEEE
14 years 3 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
MM
2005
ACM
150views Multimedia» more  MM 2005»
14 years 2 months ago
Reading SCORM compliant multimedia courses using heterogeneous pervasive devices
The Sharable Content Object Reference Model (SCORM) provides some important representation for distance learning content and the learning behavior. In general, SCORM-Compliant lea...
Te-Hua Wang, Hsuan-Pu Chang, Yun-Long Sie, Kun-Han...
ICCV
1998
IEEE
14 years 11 months ago
Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
Existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. In some situations ...
Tony Heap, David Hogg
CEC
2009
IEEE
14 years 4 months ago
Multi-objective optimization using self-adaptive differential evolution algorithm
- In this paper, we propose a Multiobjective Self-adaptive Differential Evolution algorithm with objective-wise learning strategies (OW-MOSaDE) to solve numerical optimization pr...
Vicky Ling Huang, Shuguang Z. Zhao, Rammohan Malli...
WACV
2007
IEEE
14 years 3 months ago
Extraction of Person Silhouettes from Surveillance Imagery using MRFs
We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object sh...
Vinay Sharma, James W. Davis