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» Pedestrian detection by modeling local convex shape features
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AAAI
2008
15 years 2 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
13 years 11 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
16 years 1 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
14 years 10 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
16 years 1 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