Object Tracking by Detection using YOLO and SORT

Authors

  • Heet Thakkar  BE Scholar, Department of Computer Engineering Datta Meghe College of Engineering New Mumbai, Maharashtra, India
  • Noopur Tambe  BE Scholar, Department of Computer Engineering Datta Meghe College of Engineering New Mumbai, Maharashtra, India
  • Sanjana Thamke  BE Scholar, Department of Computer Engineering Datta Meghe College of Engineering New Mumbai, Maharashtra, India
  • Prof. Vaishali K. Gaidhane  Assistant Professor, Department of Computer Engineering Datta Meghe College of Engineering New Mumbai, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT206256

Keywords:

Tracking-by-detection, You Only Look Once (YOLO), Simple Online and Realtime Tracking (SORT), visual tracking.

Abstract

Over the past two decades, computer vision has received a great deal of coverage. Visual object tracking is one of the most important areas of computer vision. Tracking objects is the process of tracking over time a moving object (or several objects). The purpose of visual object tracking in consecutive video frames is to detect or connect target objects. In this paper, we present analysis of tracking-by-detection approach which include detection by YOLO and tracking by SORT algorithm. This paper has information about custom image dataset being trained for 6 specific classes using YOLO and this model is being used in videos for tracking by SORT algorithm. Recognizing a vehicle or pedestrian in an ongoing video is helpful for traffic analysis. The goal of this paper is for analysis and knowledge of the domain.

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Published

2020-04-30

Issue

Section

Research Articles

How to Cite

[1]
Heet Thakkar, Noopur Tambe, Sanjana Thamke, Prof. Vaishali K. Gaidhane, " Object Tracking by Detection using YOLO and SORT, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.224-229, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT206256