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134
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ICCCN
2007
IEEE
15 years 3 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
161
Voted
MMM
2005
Springer
202views Multimedia» more  MMM 2005»
15 years 9 months ago
Image Mining and Retrieval Using Hierarchical Support Vector Machines
For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been la...
Ross Brown, Binh Pham
150
Voted
MM
2006
ACM
218views Multimedia» more  MM 2006»
15 years 9 months ago
SmartLabel: an object labeling tool using iterated harmonic energy minimization
Labeling objects in images is an essential prerequisite for many visual learning and recognition applications that depend on training data, such as image retrieval, object detecti...
Wen Wu, Jie Yang
ICASSP
2011
IEEE
14 years 7 months ago
Multiple instance tracking based on hierarchical maximizing bag's margin boosting
In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...
Chunxiao Liu, Guijin Wang, Xinggang Lin, Bobo Zeng
CVPR
2008
IEEE
16 years 5 months ago
Combining brain computer interfaces with vision for object categorization
Human-aided computing proposes using information measured directly from the human brain in order to perform useful tasks. In this paper, we extend this idea by fusing computer vis...
Ashish Kapoor, Pradeep Shenoy, Desney S. Tan