This paper is published in Volume-7, Issue-5, 2021
Area
Computer Science
Author
Shakthi T.
Org/Univ
Vellore Institute of Technology, Vellore, Tamil Nadu, India
Pub. Date
29 October, 2021
Paper ID
V7I5-1381
Publisher
Keywords
Video Shot Segmentation, Video Object Detection, Boundary Detection, Object Tracking, Yolov4, Deepsort, Etc.

Citationsacebook

IEEE
Shakthi T.. Video Shot Segmentation: Hybrid Approach using YOLOv4 and Deep Sort Algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Shakthi T. (2021). Video Shot Segmentation: Hybrid Approach using YOLOv4 and Deep Sort Algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 7(5) www.IJARIIT.com.

MLA
Shakthi T.. "Video Shot Segmentation: Hybrid Approach using YOLOv4 and Deep Sort Algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 7.5 (2021). www.IJARIIT.com.

Abstract

A shot is a sequence frame in an edited video taken by a single camera. Shot Segmentation is the process of splitting video and finding the boundaries of video data. In this paper, we study the method in content-based video retrieval which uses object detection and tracking for video segmentation. Data collected via segmenting can be categorized in a hierarchy manner as scene layer, camera shot layer, and the frame in their accordance. The data collected is used for segmentation. YOLOv4 is used to enhance the accuracy and the process of tracking and detection much faster.