A 3D object tracking method and system based on point cloud sequence data

Abstract

The invention discloses a 3D target tracking method and system based on point cloud sequence data, which belongs to the field of digital image recognition, including: extracting and standardizing the search point cloud and the template point cloud containing the target frame respectively in the current frame and the previous frame , using the 3D target tracking model to predict the position and pose of the target frame in the current frame to determine the position of the 3D target in the current frame; in the 3D target tracking model, the feature extraction network is used to extract template point cloud features and search point cloud features , the correlation prediction network is used to predict the target score of each feature point in the search point cloud, the integrated regression network is used to perform point-by-point regression after the fusion of two features, and the position prediction network is used to search for each feature point according to the point cloud. The target score is weighted and multiplied by the distance and pose of each feature point in the fusion feature from the center of the target frame. The invention can make full use of the three-dimensional properties of objects, and at the same time improve the calculation efficiency and stability of 3D object tracking.

Description

technical field [0001] The invention belongs to the field of digital image recognition, and more particularly, relates to a 3D target tracking method and system based on point cloud sequence data. Background technique [0002] In the fields of autonomous driving and robot motion trajectory planning, it is usually necessary to perceive and understand the surrounding environment, detect the motion trajectory of surrounding target objects, and then plan the direction of its own motion. Among them, target tracking technology is required to detect the target motion trajectory. The traditional 2D target tracking technology has achieved remarkable results, but it can only track the movement of the target on the camera plane, so it cannot meet the requirements of obtaining the stereoscopic motion information of the target, such as automatic driving and robot motion trajectory planning. [0003] Compared with 2D target tracking technology, 3D target tracking technology can make good ...

AI Technical Summary

Problems solved by technology

Among them, the 3D target tracking method based on RGBD video sequences is very dependent on 2D target tracking technology, which uses depth map information for further processing on the basis of 2D target tracking results, and does not make full use of 3D object structure information; The 3D target tracking method performs overhead projection on the 3D point cloud data, and then uses the 2D target tracking method to track, which loses the target information in the height direction, and cannot effectively track the target with a large change in the height direction.

[0004] Compared with the 3D object tracking method based on RGBD video sequence and the 3D object tracking method based on bird's-eye view video sequence, the 3D object tracking method based on point cloud sequence data can make full use of the three-dimensional properties of the object, but the point cloud data has no The existing 3D target tracking method based on point cloud sequence data has a search space when predicting the position of the target frame in the current frame point cloud data based on the tracking results of the previous frame point cloud data. It is extremely large, so the calculation efficiency is low, and the prediction model cannot be trained end-to-end, and the stability of the tracking results cannot be guaranteed

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