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» Pedestrian detection by modeling local convex shape features
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AAAI
2008
13 years 7 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
ICCV
2011
IEEE
12 years 5 months ago
From Contours to 3D Object Detection and Pose Estimation
This paper addresses view-invariant object detection and pose estimation from a single image. While recent work focuses on object-centered representations of point-based object fe...
Nadia Payet, Sinisa Todorovic
CVPR
2008
IEEE
14 years 7 months ago
A mixed generative-discriminative framework for pedestrian classification
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
Markus Enzweiler, Dariu M. Gavrila
ISVC
2010
Springer
13 years 3 months ago
Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape
In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the de...
Kai Cordes, Oliver Müller, Bodo Rosenhahn, J&...
CVPR
2005
IEEE
14 years 7 months ago
Pedestrian Detection in Crowded Scenes
In this paper, we address the problem of detecting pedestrians in crowded real-world scenes with severe overlaps. Our basic premise is that this problem is too difficult for any t...
Bastian Leibe, Edgar Seemann, Bernt Schiele