Abstract: Detection and classification of vulnerable road users (VRUs) is one of the most crucial blocks in vision based navigation systems used in Advanced Driver Assistance Systems. This paper seeks to evaluate the performance of object classification algorithm, You Only Look Once i.e. YOLO v3 algorithm for the purpose of detection of a major subclass of VRUs i.e. cyclists and pedestrians using the Tsinghua – Daimler dataset. The YOLO v3 algorithm used here requires less computational resources and hence promises a real time performance when compared to its predecessors. The model has been trained using the training images in the mentioned benchmark and have been tested for the test images available for the same. The average IoU for all the truth objects is calculated and the precision recall graph for different thresholds was plotted.

Saranya K C and Arunkumar Thangavelu, “Vulnerable Road User Detection using YOLO v3” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101275

@article{C2019,
title = {Vulnerable Road User Detection using YOLO v3},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101275},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101275},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Saranya K C and Arunkumar Thangavelu}
}