NDLI: Vehicle object observation using position based local gradient model

Content Provider	IEEE Xplore Digital Library
Author	Karpagalakshmi, R.C. Tensing, D.
Copyright Year	2012
Description	Author affiliation: Department of CSE, Tagore Institute of Engineering & Technology, Attur, Salem, Tamil Nadu, India (Karpagalakshmi, R.C.) \|\| A.S.L. Pauls College of Engineering & Technology, Solvampalayam, (Elur), Pollachi Taluk, Coimbatore, Tamil Nadu, India (Tensing, D.)
Abstract	The conception of traffic activities in urban framework is the major endeavor in the study of traffic troubles. This examination is chiefly processed on the maximization of traffic flow, and the minimization of traffic accidents, congestions and pollution. In common, network representations of transport systems are understood to be fixed, but these representations do not permit an exact recreation of seriously packed urban road networks. For this rationale, traffic engineers happened to judge some substitute models such as simple object recognition and localization of road vehicles based on the position and orientation of vehicle image data. But the drawback of the approach is that if the shape of the vehicle and its pose varies in multiple junction coordination, the model based recognition is an inefficient one. To enhance the process of traffic flow mechanism, in this paper, we are going to implement a surveillance image object recognition and localization using improved local gradient model. At first, the vehicle images are taken by camera which is taken on the junction board of the traffic coordination. Based on location, position, angle and height of the camera to be fixed on the junction board, the vehicle images are obtained clearly in an aerial view and extracted the entire road for identifying the vehicle densities and postures using ray traced templates. An experimental evaluation is carried out to estimate the performance of the proposed vehicle object observation using position based local gradient model in terms of vehicle density, acquired image clarity, pose recovery and compared with an existing model based on simple object recognition and localization.
Starting Page	293
Ending Page	298
File Size	564768
Page Count	6
File Format	PDF
ISBN	9781467327565
e-ISBN	9781467327589
DOI	10.1109/ICRCC.2012.6450598
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Roads Computational modeling Improved gradient model Cameras Road extraction Object localization Object recognition Junctions Vehicles Vehicle object recognition Ray traced templates
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
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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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