NDLI: Predictive and Probabilistic Tracking to Detect Stopped Vehicles

Content Provider	IEEE Xplore Digital Library
Author	Melli, R. Prati, A. Cucchiara, R. de Cock, L.
Copyright Year	2005
Description	Author affiliation: Univ. of Modena & Reggio Emilia (Melli, R.; Prati, A.; Cucchiara, R.)
Abstract	Many techniques and models have been proposed for vehicles surveillance in highways. In the past, tracking algorithms based on Kalman filter have been largely used for their efficiency in the prediction and low computational cost. However, predictive filters cannot solve long-lasting occlusions. In this paper, we propose a new mixed predictive and probabilistic tracking that exploits the advantages of predictive filters for moving vehicles and adopts probabilistic and appearance-based tracking for stopped vehicles. The proposed tracking is part of a complete video surveillance system, oriented to control tunnels and highways from cluttered views, that is implemented in an embedded DSP platform and provides background suppression, a novel shadow detection algorithm, tracking, and scene recognition module. The experimental results are obtained over several hours of videos acquired in pre-existing platforms of CCTV surveillance systems
Starting Page	388
Ending Page	393
File Size	4566073
Page Count	6
File Format	PDF
ISBN	0769522718
DOI	10.1109/ACVMOT.2005.96
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-01-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicle detection Road transportation Filters Road vehicles Computational efficiency Video surveillance Control systems Digital signal processing Detection algorithms Layout
Content Type	Text
Resource Type	Article

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