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» Online Selection of Tracking Features using AdaBoost
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ICCV
2007
IEEE
16 years 6 months ago
Gradient Feature Selection for Online Boosting
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...
Ting Yu, Xiaoming Liu 0002
ICIP
2009
IEEE
16 years 5 months ago
Online Subjective Feature Selection For Occlusion Management In Tracking Applications
Most of the state-of-the-art tracking algorithms are prone to error when dealing with occlusions, especially when the involved moving objects are hardly discernible in appearance....
CVPR
2007
IEEE
16 years 6 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
MVA
2011
336views Computer Vision» more  MVA 2011»
14 years 11 months ago
In-vehicle camera traffic sign detection and recognition
: In this paper we discuss theoretical foundations and a practical realization of a real-time traffic sign detection, tracking and recognition system operating on board of a vehicl...
Andrzej Ruta, Fatih Porikli, Shintaro Watanabe, Yo...
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
16 years 4 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...