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» Local Boosted Features for Pedestrian Detection
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ICPR
2010
IEEE
14 years 7 months ago
A Re-evaluation of Pedestrian Detection on Riemannian Manifolds
Abstract--Boosting covariance data on Riemannian manifolds has proven to be a convenient strategy in a pedestrian detection context. In this paper we show that the detection perfor...
Diego Tosato, Michela Farenzena, Marco Cristani, V...
174
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AAAI
2008
14 years 11 months ago
Multimodal People Detection and Tracking in Crowded Scenes
This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
DAGM
2009
Springer
15 years 4 months ago
Pedestrian Detection by Probabilistic Component Assembly
We present a novel pedestrian detection system based on probabilistic component assembly. A part-based model is proposed which uses three parts consisting of head-shoulder, torso a...
Martin Rapus, Stefan Munder, Gregory Baratoff, Joa...
ICPR
2010
IEEE
14 years 7 months ago
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations
Classifying images using features extracted from densely sampled local patches has enjoyed significant success in many detection and recognition tasks. It is also well known that ...
Mert Dikmen, Thomas S. Huang
NIPS
2008
14 years 11 months ago
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features
We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-c...
Tae-Kyun Kim, Roberto Cipolla