Night working engineering machinery visual tracking method and deviceand storage medium

Abstract

The invention discloses a night working engineering machinery visual tracking method and device and a storage medium, and the method comprises the steps: repairing all frames of a night video through employing a global illumination perception and detail preserving network, and obtaining an illumination enhanced image; processing the illumination enhanced image by using a YOLO-v4 algorithm to generate a detection window; performing tracking detection on the illumination enhanced image by using a Kalman filtering tracker to generate a tracking window and a tracking ID; according to the position similarity and the CNN feature similarity, associating the detection window with the tracking window to construct an association matrix; according to the incidence matrix, judging whether the detection window is associated with the tracking window through a Hungary algorithm; if the detection window is associated with the tracking window, allocating the tracking ID to the detection window. The method can achieve the precise detection and recognition of an engineering machinery object during night work, and can be widely used in the technical field of visual tracking.

Description

technical field [0001] The invention relates to the technical field of visual tracking, in particular to a visual tracking method, device and storage medium for engineering machinery working at night. Background technique [0002] With the continuous development of computer technology, the computing power has been greatly improved, making the use of computers to realize human visual functions to become one of the most popular topics in the computer field. The problem of visual tracking (Visual tracking) is an important issue in the field of computer vision. The so-called visual tracking refers to the detection, extraction, identification and tracking of moving targets in image sequences, and the acquisition of moving parameters of moving targets, such as position and speed. , acceleration, etc., and motion trajectory, so as to further process and analyze, realize the behavioral understanding of the moving target, and complete higher-level tasks. [0003] In recent years, co...

AI Technical Summary

Problems solved by technology

However, the target detection frameworks are all focused on images with good light. However, in real life, night construction has been widely used in many construction scenarios, but the risk of night construction is also greater due to low light conditions and fatigue environments; night construction video There is an issue with low lighting conditions in . Insufficient lighting will affect the visual quality, which will reduce the performance of the object detection algorithm for identifying construction machinery from nighttime videos.

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