A novel approach of surveillance video indexing and retrieval using object detection and tracking

Abstract

The problem of searching videos in large databases i.e. multimedia applications is a major challenge. Therefore, video indexing is used to search the location of the particular video in a large database quickly. Quickly locating the video in the large database is the good quality of indexing. Still, there is a scope of improvement in quickly searching a video in a large database in terms of assigning labels to video. In computer vision, real-time object detection and tracking is a gigantic, vibrant yet indecisive and intricate area. You only look once (YOLO) algorithm is used to detect the object and background subtraction is used to track the object. In this paper, video indexing using object detection / tracking can be performed on single object in a video. In future, video indexing can be performed on multiple objects in a video.