Affine motion target tracing algorithm based on fast robust feature matching

Abstract

The invention belongs to the field of computer vision and aims at solving the problem that the continuous self-adapting mean shift algorithm is apt to be interfered by color close backgrounds and achieving real-time steady tracing of affine motion targets in complex backgrounds. The technical scheme is that an affine motion target tracing algorithm based on fast robust feature matching includes the following steps: (1) enabling a target area determined in video flowing to be switched from a red, green and blue (RGB) color space to a hue, saturation and value (HSV) color space; (2) detecting fast robust feature points of an H channel, an S channel and a V channel of a current frame target area; (3) obtaining a minimum external interesting area through the position of matched and purified feature points; (4) determining the mass center of a target probability distribution map, namely the search window position, by aid of the mean shift iterative algorithm; (5) performing updating and restraining; and (6) finishing single-step tracing if iteration is converged and entering the step 2 for continuing operating otherwise. The affine motion target tracing algorithm is mainly applied to image processing.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to an affine moving target tracking algorithm based on fast and robust feature matching, which can be applied to the field of intelligent security. Specifically, it involves an affine moving target tracking algorithm based on fast and robust feature matching. Background technique [0002] Moving object tracking is one of the core technologies for object detection, and it is also the basis for subsequent high-level processing, such as behavior understanding. As the key to the automation of intelligent video surveillance technology, target tracking is widely used in the fields of traffic monitoring and public security. [0003] In information theory, object tracking can be defined as estimating the state of a system given a set of observations. In visual tracking, the target of tracking is the target feature extracted from the image. If the position and shape of the feature can be accura...

AI Technical Summary

Problems solved by technology

However, when the appearance of the target changes greatly, it often causes tracking failure

For example, combining the feature matching of scale-invariant feature transformation with the mean shift algorithm improves the accuracy of the mean shift algorithm, but the calculation amount is large, which is not suitable for real-time tracking systems

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