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Vehicle queue length estimation using uncalibrated cameras

Puri, A and Krishnapuram, R (2020) Vehicle queue length estimation using uncalibrated cameras. In: 2019 IEEE 16th India Council International Conference, INDICON 2019 - Symposium Proceedings, December 2019, 13-15 Dec. 2019, Rajkot, India.

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Official URL: https://dx.doi.org/10.1109/INDICON47234.2019.90290...


Vehicle queue lengths at city road intersections are important parameters in designing intelligent transport systems, and are particularly useful in traffic modeling and in designing smart signals. In this paper, we propose a simple and scalable method for estimation of vehicle queue lengths that works in real time. The proposed solution is based on cameras (with unknown intrinsics) that are commonly found on most city roads, and does not require the installation of any sensors. The approach consists of three stages. In the first stage, we automatically identify the road region in the camera view. This is achieved through unsupervised segmentation that uses a convolutional neural network. In the second stage, we identify the presence of the queue by using low level features such as corners. In the third stage, we estimate the physical length (in metres) of the queue. Our experiments show that the proposed method is effective, with less than 10 error in the length estimates. © 2019 IEEE.

Item Type: Conference Paper
Publication: 2019 IEEE 16th India Council International Conference, INDICON 2019 - Symposium Proceedings
Publisher: Institute of Electrical and Electronics Engineers Inc. (IEEE)
Additional Information: cited By 0; Conference of 16th IEEE India Council International Conference, INDICON 2019 ; Conference Date: 13 December 2019 Through 15 December 2019; Conference Code:158465
Keywords: Cameras; Convolutional neural networks; Intelligent systems; Queueing theory; Roads and streets; Scalability; Traffic control, Estimation of vehicles; Intelligent transport systems; Low-level features; Physical length; Road intersections; Scalable methods; Un-calibrated camera; Unsupervised segmentation, Road vehicles
Department/Centre: Division of Interdisciplinary Sciences > Robert Bosch Centre for Cyber Physical Systems
Date Deposited: 22 Sep 2020 10:54
Last Modified: 22 Sep 2020 10:54
URI: http://eprints.iisc.ac.in/id/eprint/65207

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