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NIPS
2004
13 years 9 months ago
A Topographic Support Vector Machine: Classification Using Local Label Configurations
The standard approach to the classification of objects is to consider the examples as independent and identically distributed (iid). In many real world settings, however, this ass...
Johannes Mohr, Klaus Obermayer
CVPR
2005
IEEE
14 years 9 months ago
Tracking Multiple Objects through Occlusions
We present an approach for tracking varying number of objects through both temporally and spatially significant occlusions. Our method builds on the idea of object permanence to r...
Yan Huang, Irfan A. Essa
ICIP
2002
IEEE
14 years 17 days ago
Segmentation-based object tracking using image warping and Kalman filtering
We propose a segmentation-based method of object tracking using image warping and Kalman filtering. The object region is defined to include a group of patches, which are obtained ...
Yu Huang, Thomas S. Huang, Heinrich Niemann
DAGM
2006
Springer
13 years 11 months ago
Robust Non-rigid Object Tracking Using Point Distribution Manifolds
Abstract. We present an approach to non-rigid object tracking designed to handle textured objects in crowded scenes captured by non-static cameras. For this purpose, groups of low-...
Tom Mathes, Justus H. Piater
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng