Abstract
This paper proposes a new method of target localization and tracking. The method consists of four parts. The first part is to divide the scene into multiple cells based on the camera’s parameters and calibrate the position and error of each vertex. The second part mainly uses the bounding box detection algorithm, YOLOv4, based on deep learning to detect and recognize the scene image sequence and obtain the type, length, width, and position of the target to be tracked. The third part is to match each vertex of the cell in the image and the cell in the scene, generate a homography matrix, and then use the PnP model to calculate the precise world coordinates of the target in the image. In this process, a cell-based accuracy positioning method is proposed for the first time. The fourth part uses the proposed PTH model to convert the obtained world coordinates into P, T, and H values for the purpose of actively tracking and observing the target in the scene with a PTZ camera. The proposed method achieved precise target positioning and tracking in a 50 cm ∗ 250 cm horizontal channel and a vertical channel. The experimental results show that the method can accurately identify the target to be tracked in the scene, can actively track the moving target in the observation scene, and can obtain a clear image and accurate trajectory of the target. It is verified that the maximum positioning error of the proposed cell-based positioning method is 2.31 cm, and the average positioning error is 1.245 cm. The maximum error of the proposed tracking method based on the PTZ camera is 1.78 degrees, and the average error is 0.656 degrees.
Highlights
Publisher’s Note: MDPI stays neutralWith the continuous advancement of science and technology and the continuous improvement of people’s living standards, video surveillance has played an increasingly important role in people’s lives [1–4]
To use the PTZ camera to obtain accurate target information such as type, position, etc., we propose a target localization and tracking method based on cell and active cameras
Based on the target’s world coordinates, the PTH model is used to calculate the P and T values of the PTZ camera, in order to achieve the purpose of tracking and observing the target
Summary
With the continuous advancement of science and technology and the continuous improvement of people’s living standards, video surveillance has played an increasingly important role in people’s lives [1–4]. To use the PTZ camera to obtain accurate target information such as type, position (speed), etc., we propose a target localization and tracking method based on cell and active cameras. Based on the target’s world coordinates, the PTH model is used to calculate the P and T values of the PTZ camera, in order to achieve the purpose of tracking and observing the target. This experiment was conducted with a wireless remote-control Jeep (hereafter referred to as “WRC-Jeep”) as the target and it was compared with other target tracking methods.
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