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Object Tracking by Detection using YOLO and SORT

Author

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  • Heet Thakkar
  • Noopur Tambe
  • Sanjana Thamke
  • Vaishali K. Gaidhane

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.

Suggested Citation

  • Heet Thakkar & Noopur Tambe & Sanjana Thamke & Vaishali K. Gaidhane, 2020. "Object Tracking by Detection using YOLO and SORT," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 6(2), pages 224-229, April.
    • Handle: RePEc:jbh:ijsrcs:v6:y2020:i2:id:hcseit206256
    DOI: 10.32628/CSEIT206256
    Note: Article URL: https://ijsrcseit.com/CSEIT206256
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