NDLI: Stereovision-Based Multiple Object Tracking in Traffic Scenarios Using Free-Form Obstacle Delimiters and Particle Filters

Content Provider	IEEE Xplore Digital Library
Author	Vatavu, A. Danescu, R. Nedevschi, S.
Copyright Year	2000
Description	In this paper we present a stereovision-based approach for tracking multiple objects in crowded environments where, typically, the road lane markings are not visible and the surrounding infrastructure is not known. The proposed technique relies on measurement data provided by an intermediate occupancy grid derived from processing a stereovision-based elevation map and on free-form object delimiters extracted from this grid. Unlike other existing methods that track rigid objects using also rigid representations, we present a particle filter-based solution for tracking visual appearance-based free-form obstacle representations. At each step, the particle state is described by two components, i.e., the object's dynamic parameters and its estimated geometry. In order to solve the high-dimensionality state–space problem, a Rao–Blackwellized particle filter is used. By accurately modeling the object geometry using the polygonal lines instead of a 3-D box and, at the same time, separating the position and speed tracking from the geometry tracking at the estimator level, the proposed solution combines the efficiency of the rigid model with the benefits of a flexible object model.
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	498
Ending Page	511
Page Count	14
File Size	2743265
File Format	PDF
ISSN	15249050
Volume Number	16
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Kalman filters Solid modeling Vehicle dynamics Shape Mathematical model Target tracking stereovision Object tracking particle filters polygonal models Rao–Blackwellization
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

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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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