Suspicious Object Tracking With Yolov3 with Python Using Open-CV

Object tracking system is essential for the surveillance of the suspicious abandoned objects. Tracking of the suspicious abandoned object is widely used in many areas such as airports, railway station and on its track, parking lots and public transportations to prevent terrorism and avoid the incident related to it. Precise recognition of the abandoned objects in an image arena can detect many applications using different vision algorithms. In this research paper, we present a multi-object tracking model along with left over baggage detection in a real time environment. In this article, we present the analysis of track-by-track methods, including the YOLO track and the SORT algorithm track. This article contains details about a procedure dataset of image edify with YOLO for 6 specific category, which is cumulated in videos for detection by the SORT algorithm. Identifying vehicles or pedestrians in continuous videos is useful for congestion survey. The purpose of this article is to analyze and understand the province.