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CVPR
2010
IEEE
13 years 9 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
MM
2010
ACM
146views Multimedia» more  MM 2010»
13 years 11 months ago
Making computers look the way we look: exploiting visual attention for image understanding
Human Visual attention (HVA) is an important strategy to focus on specific information while observing and understanding visual stimuli. HVA involves making a series of fixations ...
Harish Katti, Subramanian Ramanathan, Mohan S. Kan...
CAIP
2005
Springer
14 years 1 months ago
Improvement of a Temporal Video Index Produced by an Object Detector
The goal of the works described in this paper is to improve results produced by an object detector operating independently on each frame of a video document in order to generate a ...
Gaël Jaffré, Philippe Joly
AVSS
2006
IEEE
14 years 3 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CVPR
2007
IEEE
15 years 1 months ago
Accurate Object Detection with Deformable Shape Models Learnt from Images
We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models dire...
Cordelia Schmid, Frédéric Jurie, Vit...
CVPR
2006
IEEE
15 years 1 months ago
Putting Objects in Perspective
Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. In this paper, we provide a framework for p...
Derek Hoiem, Alexei A. Efros, Martial Hebert