Detection of motorcyclists without helmet in videos using convolutional neural network

C, Vishnu and Singh, D and C, Krishna Mohan and Ch, Sobhan Babu (2017) Detection of motorcyclists without helmet in videos using convolutional neural network. In: International Joint Conference onNeural Networks (IJCNN), 14-19 May 2017, Anchorage, USA.

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In order to ensure the safety measures, the detection of traffic rule violators is a highly desirable but challenging task due to various difficulties such as occlusion, illumination, poor quality of surveillance video, varying whether conditions, etc. In this paper, we present a framework for automatic detection of motorcyclists driving without helmets in surveillance videos. In the proposed approach, first we use adaptive background subtraction on video frames to get moving objects. Later convolutional neural network (CNN) is used to select motorcyclists among the moving objects. Again, we apply CNN on upper one fourth part for further recognition of motorcyclists driving without a helmet. The performance of the proposed approach is evaluated on two datasets, IITH_Helmet_1 contains sparse traffic and IITH_Helmet_2 contains dense traffic, respectively. The experiments on real videos successfully detect 92.87% violators with a low false alarm rate of 0.5% on an average and thus shows the efficacy of the proposed approach.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Helmet Detection, Traffic Surveillance, Deep Learning, Convolutional Neural Network
Subjects: Computer science > Computer programming, programs, data
Computer science > Special computer methods
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 10 Jul 2017 04:51
Last Modified: 30 Aug 2017 11:02
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