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» A Boosting Approach to Multiple Instance Learning
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148
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IJRR
2010
137views more  IJRR 2010»
15 years 1 months ago
Multiclass Multimodal Detection and Tracking in Urban Environments
This paper presents a novel approach to detect and track pedestrians and cars based on the combined information retrieved from a camera and a laser range scanner. Laser data points...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
133
Voted
ICCV
2011
IEEE
14 years 2 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
119
Voted
CVPR
2001
IEEE
16 years 4 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
141
Voted
CVPR
2012
IEEE
13 years 5 months ago
Multi-target tracking by online learning of non-linear motion patterns and robust appearance models
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
Bo Yang, Ram Nevatia
ECCV
2010
Springer
15 years 5 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...