Multi-target rapid capturing and tracking method in binocular vision measurement

Abstract

The invention provides a multi-target rapid capturing and tracking method in binocular vision measurement, and belongs to the field of computer vision measurement. The multi-target rapid capturing andtracking method comprises the steps of image preprocessing under a strong clutter background condition, target capturing, multi-target recognition and multi-target tracking. Real-time processing of mass data can be realized. Meanwhile, a plurality of beacon points on an object can be stably captured and tracked under strong clutter conditions such as sun illumination, sky cloud, imaging noise andsea level reflection, and each beacon point in the image is correspondingly matched with the spatial position of the beacon point, so that the stability and robustness of multi-target identificationand tracking in binocular vision measurement can be improved.

Description

technical field [0001] The invention relates to a method for fast capturing and tracking of multiple weak and small targets in a complex background, in particular to a method for capturing and tracking multiple cooperative target sources (beacons referred to below) in binocular vision measurement. It belongs to the fields of image processing and computer vision measurement. Background technique [0002] With the development of optoelectronic technology and the integration of cross-disciplines, the use of computer vision measurement methods for non-contact measurement is becoming an important measurement method. Vision measurement technology can not only measure the distance of the object but also measure the three-dimensional space position and attitude angle of the object. Visual measurement technology has the characteristics of low cost and long working distance. As long as the measurement camera can effectively extract a certain number of feature points on the object, it...

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Problems solved by technology

[0005] Most of the target capture and tracking devices in binocular vision measurement systems are based on PCs. However, PCs are large in size, high in power consumption, and poor in stability, which is difficult to meet engineering applications. It is urgent to develop a stable high-speed embedded processing platform for dual-camera Real-time processing of large amounts of data; traditional multi-target acquisition and tracking methods mostly process each beacon in isolation, without considering the rigid connection between different beacon points on both sides of the same object in binocular vision measurement, and the effective use of binocular The result data unique to the eye measurement system, that is, the position and attitude information of the measured object, to improve the stability of target acquisition and tracking

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