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ISVC
2010
Springer
13 years 6 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
PAMI
2007
194views more  PAMI 2007»
13 years 7 months ago
Robust Object Tracking Via Online Dynamic Spatial Bias Appearance Models
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Datong Chen, Jie Yang
ICASSP
2011
IEEE
12 years 11 months ago
Efficient block-division model for robust multiple object tracking
Tracking multiple objects under occlusion is one of the most challenging issues in computer vision. Occlusion results in mistaken match when finding the most similar candidate. A...
Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weimin...
ECCV
2008
Springer
14 years 9 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
ECCV
2008
Springer
13 years 9 months ago
Robust Real-Time Visual Tracking Using Pixel-Wise Posteriors
We derive a probabilistic framework for robust, real-time, visual tracking of previously unseen objects from a moving camera. The tracking problem is handled using a bag-of-pixels ...
Charles Bibby, Ian D. Reid