Pedestrain Motion Detection using YOLO v3 Algorithm

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Pedestrain Motion Detection using YOLO v3 Algorithm
Author(s):
Sethuselvi M, Dr.S.Kayalvizhi
Keywords:
PMD, YOLO, RCNN, CNN, IOU, NMS.
Abstract
Vehicular accidents claim millions around the world every year most of which that are caused due to human-error. The Autonomous Vehicles are believed to bring solution to the problem by automating the use of vehicles. The autonomous vehicles have a very important feature called pedestrian detection to detect pedestrians on the road and stop in the appropriate places. Many multi-person trackers have been proposed for real-time detection of pedestrians but due to inaccurate predictions and long training time they have not been efficient.In this paper pedestrians are detected using yolo v3 algorithm on the COCO dataset which consists of sequence of images.The images are trained and the output is identified with the help of convolutional neural networks in yolo architecture.
Article Details
Unique Paper ID: 151342 Publication Volume & Issue: Volume 7, Issue 12 Page(s): 441 - 445
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