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» Detecting Pedestrians by Learning Shapelet Features
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CVPR
2009
IEEE
13 years 11 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
ICCV
2005
IEEE
14 years 9 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
PCM
2007
Springer
114views Multimedia» more  PCM 2007»
14 years 1 months ago
Random Convolution Ensembles
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
Michael Mayo
ICPR
2006
IEEE
14 years 8 months ago
A Viewpoint Invariant Approach for Crowd Counting
This paper describes a viewpoint invariant learningbased method for counting people in crowds from a single camera. Our method takes into account feature normalization to deal wit...
Dan Kong, Douglas Gray, Hai Tao
ICMCS
2005
IEEE
182views Multimedia» more  ICMCS 2005»
14 years 1 months ago
An integrated approach for generic object detection using kernel PCA and boosting
In this paper we present a novel framework for generic object class detection by integrating Kernel PCA with AdaBoost. The classifier obtained in this way is invariant to changes...
Saad Ali, Mubarak Shah