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ICCV
2009
IEEE
15 years 4 months ago
Incremental Multiple Kernel Learning for object recognition
A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining ...
Aniruddha Kembhavi, Behjat Siddiquie, Roland Miezi...
ICCV
2009
IEEE
15 years 4 months ago
Group-sensitive multiple kernel learning for object categorization
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
ACCV
2010
Springer
15 years 1 months ago
Multiple Viewpoint Recognition and Localization
This paper presents a novel approach for labeling objects based on multiple spatially-registered images of a scene. We argue that such a multi-view labeling approach is a better fi...
Scott Helmer, David Meger, Marius Muja, James J. L...
CVPR
2012
IEEE
13 years 9 months ago
Coupling detection and data association for multiple object tracking
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
CVPR
2009
IEEE
17 years 1 months ago
Visual Tracking with Online Multiple Instance Learning
In this paper, we address the problem of learning an adaptive appearance model for object tracking. In particular, a class of tracking techniques called “tracking by detectionâ...
Boris Babenko, Ming-Hsuan Yang, Serge J. Belongie