Abstract
For autonomous vehicles to navigate safely through traffic, it is necessary to understand the status of the surrounding environment such as traffic lights and traffic signs present. The traffic sign detection algorithms designed miss to recognize the signs under occlusion scenarios. Therefore, including tracking along with the detection algorithm helps in increasing the detection rate and safe manoeuvring. The paper presents tracking by detection method for tracking multiple traffic signs in image coordinates with no ego motion information present. The existing tracking methods such as the Kalman filter fails to track multiple traffic signs in image coordinates due to camera perspective projection. Assuming the movement of the camera mounted on the vehicle is linear, the prediction of traffic sign location is made robustly by modeling the motion and using Mahalanobis distance measure and Hungarian Association algorithm the predictions and detections are associated. The proposed tracking method achieved a decent accuracy of 92.3%, and a precision of 96.4% when compared with other State-of-the-art methods.
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Hegde, K, S., Kannan, S. (2022). Real Time Tracking of Traffic Signs for Autonomous Driving Using Monocular Camera Images. In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_66
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