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» Application of Level Set Methods in Computer Vision
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ICPR
2010
IEEE
15 years 6 months ago
Scene-Adaptive Human Detection with Incremental Active Learning
In many computer vision tasks, scene changes hinder the generalization ability of trained classifiers. For instance, a human detector trained with one set of images is unlikely t...
Ajay Joshi, Fatih Porikli
ICCV
2011
IEEE
14 years 7 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
CVPR
2004
IEEE
16 years 9 months ago
Linear Model Hashing and Batch RANSAC for Rapid and Accurate Object Recognition
This paper proposes a joint feature-based model indexing and geometric constraint based alignment pipeline for efficient and accurate recognition of 3D objects from a large model ...
Ying Shan, Bogdan Matei, Harpreet S. Sawhney, Rake...
CVPR
2005
IEEE
16 years 9 months ago
Bayesian Object Detection in Dynamic Scenes
Detecting moving objects using stationary cameras is an important precursor to many activity recognition, object recognition and tracking algorithms. In this paper, three innovati...
Yaser Sheikh, Mubarak Shah
CVPR
2000
IEEE
16 years 9 months ago
High Dynamic Range Imaging: Spatially Varying Pixel Exposures
While real scenes produce a wide range of brightness variations, vision systems use low dynamic range image detectors that typically provide 8 bits of brightness data at each pixe...
Shree K. Nayar, Tomoo Mitsunaga