High-Level Traffic-Violation Detection for Embedded Traffic Analysis

Vijverberg, Julien A.; Koning, Nico; Han, Jungong; Cornelissen, D.

doi:10.1109/icassp.2007.366355

Cited by 18 publications

(7 citation statements)

References 3 publications

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“…Trajectory and movement data have been studied with various approaches, including visual analysis [3], machine vision [31], clustering [5], feature extraction [4] and movement pattern taxonomy [14]. Visual analysis tools enable interactive and intuitive data exploration.…”

Section: Related Workmentioning

confidence: 99%

TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection

Guo

Wang

et al. 2011

2011 IEEE Pacific Visualization Symposium

164

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Section: Related Workmentioning

confidence: 99%

TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection

Guo

Wang

et al. 2011

2011 IEEE Pacific Visualization Symposium

164

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“…In [141] behavior detection [168,169], as well as events based on group activities [170]. Transit surveillance involves many sub-problems, including classification of different types of vehicles [171,172,173], vehicle recognition [174], or discrimination between vehicles and other frequent objects [175 ], such as pedestrian, bicycles, buses, cars, pickups, trucks, and vans.…”

Section: Multiple Person Interactionsmentioning

confidence: 99%

Evaluation of Smart Video for Transit Event Detection

Goldgof¹

2009

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Transit agencies are increasingly using video cameras to fight crime and terrorism. As the volume of video data increases, the existing digital video surveillance systems provide the infrastructure only to capture, store and distribute video, while leaving the task of threat detection exclusively to human operators. The objective of this research project was to study and develop an evaluation framework for commercial video analytics systems. A state-of-the-art research literature survey was conducted. Identified strengths, weaknesses, future directions of research and state-of-the-art commercial video analytics products were surveyed. Product capabilities were identified by working together with vendors and analyzing the available literature offered by the providers. Use of analytic technology in transit agencies in Florida was analyzed. A technology survey among the largest agencies in the state indicates very low use of video analytics, significant skepticism, and poor general knowledge of the technology and its capabilities. Based on existing general evaluation frameworks, an evaluation framework for video analytics technology was developed, including annotation guidelines, scoring metrics, and implementation of the scoring metrics in the scoring software.

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“…In our scheme we use unidirectional image detectors and kirschedge detector for the feature extraction. We can extract these features at very much low cost by the help of computational techniques and get acceptable results for the character recognition [10][11][12][13]. This research is divided into five sections: I section gives the basic introduction, II section gives the literature review, III section gives information about problem formulation, IV section giver performance parameters and V section gives the result of this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Although these task are become easier for the human but its not practical to apply it at big scale. Till now we can not apply a fully automated transport system in non-ideal environmental conditions [10]. Generally, an LPR system consists of three subsystems.…”

Section: Introductionmentioning

confidence: 99%

Character Recognition of Vehicle License Plate using Feature Extraction: A Review Paper

Dagar¹

2018

IJRASET

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The License Plate Recognition (LPR) system is the most popular method for the mass surveillance of the automobiles now days. The LPR system is basically works into 3 steps , 1 st step is to recognize vehicle license plate and then extract numbers from that and third step is to character recognition means to read out the characters of an number plate. The LPR is also some face some difficulties due to no uniform structure of number plates and illumination is also cause some difficulties in some areas. I. INTRODUCTION From the past two decades there is an boom in the automobile industry which increase the number of vehicles on road and make the transportation faster and cheaper. Till now human are employed for monitoring and controlling the traffic related parameter which is very difficult and very complex. Thus the developed countries are now opting a intelligent transport system to monitor the traffic. The main aim to design these intelligent systems is to monitor the vehicle more accurately and to construct a applicable scheme to control the traffic [1,2]. License plate recognition system is an integral part of these intelligent transport systems, the license plate recognition techniques makes it possible to use image processing technique to extract the alphanumeric numbers from the vehicle license number plates and to read out the plate. This techniques makes possible to recognize the number plate numbers from an moving or an stationary vehicle which makes vehicle recognition more easier. This technique is employed for various kind of uses like to automatic charge the toll fees from the vehicle owner while he passing from a toll way and to recognize the vehicle who breaks the traffic rules and to recognize the drivers who breaks the traffic rules to punish them. This technique also uses to recognize the vehicles that are involved in any offenses like kidnapping etc. these all are the applications of a LPR technique [3][4][5]. To design a classifieds for the character recognition we mainly match the templates of different specifications. To match the template by a automatic method we first set some sample templates and then we obtain some character from these templates. Then the character obtained from these templates is compare with the sample templates and the template which is closely matching with the sample templates is consider as an result of character recognition. As if the license plates are standardized means there size and the font uses in character is fixed then it's become much easier to recognize the character but this process is slow and time consuming and this method is not feasible in real environment [6][7][8]. In the field of plate recognition, the most commonly used classifier is ANN [9]. To get the maximum efficient results from these neural networks we have to choose the appropriate number of hidden layers and number of neurons. Now a day's , various types of multilayer NN are being applied for the character recognition eg. RBF, Kohonen, ART etc. apart from all these types of mul...

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High-Level Traffic-Violation Detection for Embedded Traffic Analysis

Cited by 18 publications

References 3 publications

TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection

TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection

Evaluation of Smart Video for Transit Event Detection

Character Recognition of Vehicle License Plate using Feature Extraction: A Review Paper

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