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Multiple Vehicles Tracking in Intelligent Transportation System using Convolutional Neural Network and Kalman Filter

Bui, Ngoc Dung and Hoang, Xuan Tung (2019) Multiple Vehicles Tracking in Intelligent Transportation System using Convolutional Neural Network and Kalman Filter. In: The 5th International Conference on Next Generation Computing 2019, December 19~21, 2019, Chiang Mai, Thailand. (In Press)

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Abstract

Vehicles detection and tracking have become an important role to traffic management systems. Recently, many vehicles tracking approaches have already been proposed. However, these approaches were unable to adequately distinguish vehicles from each other when those vehicles look similar and involve in complex transportation conditions. In this paper, a method for tracking vehicles in surveillance cameras is presented. In our method, Convolutional Neural Networks is used to detect vehicles. Also, multiple Kalman filters are used to track those vehicles. The proposed method is designed for distinguishing and tracking multiple vehicles simultaneously. Our experiments show that the proposed mechanism achieves high accuracy even with real time constraints.

Item Type: Conference or Workshop Item (Paper)
Subjects: Information Technology (IT)
Transportation Technology
Divisions: Faculty of Information Technology (FIT)
Depositing User: Xuan-Tung Hoang
Date Deposited: 12 Dec 2019 09:38
Last Modified: 12 Dec 2019 09:38
URI: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/3838

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