NDLI: Night-time vehicle classification with an embedded, vision system

Content Provider	IEEE Xplore Digital Library
Author	Gritsch, G. Donath, N. Kohn, B. Litzenberger, M.
Copyright Year	2009
Description	Author affiliation: Department Safety & Security, Business Unit Neuroinformatics, AIT - Austrian Institute of Technology GmbH, Vienna, Austria (Gritsch, G.; Donath, N.; Kohn, B.; Litzenberger, M.)
Abstract	The paper presents night-time vehicle classification using an embedded vision system based on an optical transient sensor. This neuromorphic sensor features an array of 128×128 pixels that respond to relative light intensity changes with low latency and high dynamic range. The proposed algorithm exploits the temporal resolution and sparse representation of the data, delivered by the sensor in the data-driven Address-Event Representation (AER) format, to efficiently implement a robust classification of vehicles into two classes, car-like and truck-like, during night-time operation. The classification is based on the extraction of the positions and distances of the vehicles head lights to estimate vehicle width. We present the algorithm, test data and an evaluation of the classification accuracy by comparison of the test data with ground truth from video annotation and reference results from a state-of-the-art ultrasonic/radar-combination reference detector. The results show that the difference in total truck counts with respect to a reference detector and to manually annotated video during nighttime operation under dry and wet road conditions is typically below 6%.
Starting Page	1
Ending Page	6
File Size	425492
Page Count	6
File Format	PDF
ISBN	9781424455195
DOI	10.1109/ITSC.2009.5309875
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Machine vision Sensor arrays Optical sensors Testing Radar detection Detectors Sensor systems Neuromorphics Sensor phenomena and characterization Imaging and Image Analysis Traffic Control Public Transportation Management
Content Type	Text
Resource Type	Article

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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
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