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» Multiple Object Class Detection with a Generative Model
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ACCV
2007
Springer
14 years 1 months ago
Object Detection Combining Recognition and Segmentation
Abstract. We develop an object detection method combining top-down recognition with bottom-up image segmentation. There are two main steps in this method: a hypothesis generation s...
Liming Wang, Jianbo Shi, Gang Song, I-fan Shen
PAMI
2011
12 years 10 months ago
Robust Object Tracking with Online Multiple Instance Learning
In this paper we address the problem of tracking an object in a video given its location in the first frame and no other information. Recently, a class of tracking techniques cal...
Boris Babenko, Ming-Hsuan Yang, Serge Belongie
ICCAD
2006
IEEE
134views Hardware» more  ICCAD 2006»
14 years 4 months ago
A delay fault model for at-speed fault simulation and test generation
We describe a transition fault model, which is easy to simulate under test sequences that are applied at-speed, and provides a target for the generation of at-speed test sequences...
Irith Pomeranz, Sudhakar M. Reddy
CVPR
2005
IEEE
14 years 9 months ago
Generative versus Discriminative Methods for Object Recognition
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Ilkay Ulusoy, Christopher M. Bishop
BMVC
2001
13 years 10 months ago
Hierarchical Combination of Object Models using Mutual Information
Combining different and complementary object models promises to increase the robustness and generality of today’s computer vision algorithms. This paper introduces a new method ...
Hannes Kruppa, Bernt Schiele