NDLI: The Benefits of Dense Stereo for Pedestrian Detection

Content Provider	IEEE Xplore Digital Library
Author	Keller, C.G. Enzweiler, M. Rohrbach, M. Llorca, D.F. Schnorr, C. Gavrila, D.M.
Copyright Year	2000
Abstract	This paper presents a novel pedestrian detection system for intelligent vehicles. We propose the use of dense stereo for both the generation of regions of interest and pedestrian classification. Dense stereo allows the dynamic estimation of camera parameters and the road profile, which, in turn, provides strong scene constraints on possible pedestrian locations. For classification, we extract spatial features (gradient orientation histograms) directly from dense depth and intensity images. Both modalities are represented in terms of individual feature spaces, in which discriminative classifiers (linear support vector machines) are learned. We refrain from the construction of a joint feature space but instead employ a fusion of depth and intensity on the classifier level. Our experiments involve challenging image data captured in complex urban environments (i.e., undulating roads and speed bumps). Our results show a performance improvement by up to a factor of 7.5 at the classification level and up to a factor of 5 at the tracking level (reduction in false alarms at constant detection rates) over a system with static scene constraints and intensity-only classification.
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	1096
Ending Page	1106
Page Count	11
File Size	1217738
File Format	PDF
ISSN	15249050
Volume Number	12
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Feature extraction Stereo vision Intelligent vehicles Support vector machines pedestrian detection Active safety computer vision intelligent vehicles
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Combination of Feature Extraction Methods for SVM Pedestrian Detection

Vision-Based Nighttime Vehicle Detection Using CenSurE and SVM

Real-time dense stereo for intelligent vehicles

Integrating Off-Board Cameras and Vehicle On-Board Localization for Pedestrian Safety

Pedestrian detection and tracking with night vision

On Color-, Infrared-, and Multimodal-Stereo Approaches to Pedestrian Detection

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Pedestrian Detection in Video Images via Error Correcting Output Code Classification of Manifold Subclasses

Binocular Spherical Stereo

The Benefits of Dense Stereo for Pedestrian Detection

Similar Documents

Combination of Feature Extraction Methods for SVM Pedestrian Detection

Vision-Based Nighttime Vehicle Detection Using CenSurE and SVM

Real-time dense stereo for intelligent vehicles

Integrating Off-Board Cameras and Vehicle On-Board Localization for Pedestrian Safety

Pedestrian detection and tracking with night vision

On Color-, Infrared-, and Multimodal-Stereo Approaches to Pedestrian Detection

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Pedestrian Detection in Video Images via Error Correcting Output Code Classification of Manifold Subclasses

Binocular Spherical Stereo

The Benefits of Dense Stereo for Pedestrian Detection