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» Boosting Object Detection Using Feature Selection
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CVPR
2007
IEEE
13 years 11 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
ECCV
2006
Springer
14 years 9 months ago
A Boundary-Fragment-Model for Object Detection
The objective of this work is the detection of object classes, such as airplanes or horses. Instead of using a model based on salient image fragments, we show that object class det...
Andreas Opelt, Axel Pinz, Andrew Zisserman
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 25 days ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
CVPR
2009
IEEE
2358views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
Non-rigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
ECCV
2008
Springer
14 years 9 months ago
Contour Context Selection for Object Detection: A Set-to-Set Contour Matching Approach
Abstract. We introduce a shape detection framework called Contour Context Selection for detecting objects in cluttered images using only one exemplar. Shape based detection is inva...
Qihui Zhu, Liming Wang, Yang Wu, Jianbo Shi