Object tracking system and object tracking method in camera-distributed map

Abstract

The invention discloses an objective tracking system and an objective tracking method in a camera-distributed map. The object tracking system comprises a monitoring operation client and a video calculating server. The monitoring operation client inputs an image of a suspected object and sets a to-be-searched range through the camera-distributed map. The video calculating server performs processing on a video and an image which are obtained through sampling. The object tracking method comprises the steps of extracting color characteristic of the image of the suspected target, detecting and tracking the target in a video scene, recording motion information of the target, and then transmitting a corresponding calculating result to the monitoring operation client; on the map in which camera nodes are marked by the monitoring operation client, acquiring the path track of the suspected object on the map according to the camera nodes where the suspected object appears, and simultaneously collecting information such as advancing speed and state of the target, thereby facilitating analysis by safety monitoring personnel. The objective tracking system and the objective tracking method have advantages of greatly reducing work difficulty in observing a screen for searching, making personnel concentrate on effective video segments, and realizing relatively high application value at a scientific police improvement aspect.

Description

technical field [0001] The invention belongs to the technical field of video surveillance, and more specifically relates to a target tracking system and tracking method in a camera distribution map. Background technique [0002] With the improvement of the requirements for smart cities, people's demand for video surveillance is unprecedentedly high, and the cameras deployed in various places are becoming more and more dense. There are at least 10 million surveillance cameras used in urban surveillance and alarm systems in our country. Although the addition of cameras has brought benefits to large-scale prevention and the ability to obtain massive amounts of video data for real-time alarms and post-event inquiries, how to use massive amounts of video data manually has become a huge challenge. The Sandia National Laboratory in the United States conducted a special study, and the results showed that if a person stares intently at a large number of video images, after only 22 m...

AI Technical Summary

Problems solved by technology

Although this application can also achieve the purpose of intelligent monitoring to a certain extent, in view of the fact that the effective clips of the target appearing in the video only account for a small proportion of the monitoring staff's screen-browsing workload, and if it is necessary to rely on manual The camera monitoring node draws a path on the map and analyzes the corresponding motion information. The workload is huge and very complicated. Therefore, a technology for tracking suspicious targets in the camera distribution map is needed, and computer vision is used to automatically extract the location of suspicious targets. Video clips and motion information for targeted analysis by monitoring personnel

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