KCF-based improved anti-shielding target tracking method

Abstract

The invention discloses a KCF-based improved anti-shielding target tracking method. The KCF-based improved anti-shielding target tracking method is based on a KCF algorithm and combined with a Kalmanfilter. The KCF algorithm has the advantages of fast tracking speed, high tracking precision and wide application in the target tracking field, but cannot cope with situations of scale changes and target large-area shielding. The KCF-based improved anti-shielding target tracking method adopts parallel computing to realize multi-scale target detection of a KCF, and designs an effective algorithm for determining target shielding. When determining that the target is severely shielded, the KCF-based improved anti-shielding target tracking method adopts a prediction result of the Kalman filter as acurrent frame target position. Experiments prove that the KCF-based improved anti-shielding target tracking method can effectively cope with the occurrence of tracking drift situation when the KCF algorithm encounters target large-area shielding, so that the KCF algorithm can track the target more precisely when encountering the shielding.

Description

technical field [0001] The invention belongs to the technical field of image processing target tracking, and in particular relates to an improved anti-occlusion target tracking method based on KCF. Background technique [0002] With the vigorous development of machine vision and artificial intelligence, video tracking technology, as the basis of cutting-edge technologies such as human-computer interaction and unmanned driving, has been widely concerned and researched. Many algorithms have been proposed so far, but none of them can completely solve problems such as tracking speed, illumination change, scale change, complex background and target occlusion. [0003] The KCF algorithm is a detection-based tracking algorithm, which cleverly uses the properties of the cyclic matrix to make the detection process very fast and accurate, and is a widely used tracking technology. But the algorithm itself does not deal with scale changes and occlusions; the Kalman filter is a widely u...

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Problems solved by technology

[0004] The technical problem to be solved in the present invention is to solve the problem that the KCF algorithm does not cope with scale changes, and proposes to use parallel technology for multi-scale detection, which can cope with scale changes without increasing the time consumption of the algorithm; for it cannot effectively deal with occlusion, and is blocked by obstacles Drift is prone to occur when objects are occluded in a large area. It is proposed to use the Kalman filter combined with the KCF algorithm to effectively deal with occlusion and reduce the occurrence of tracking drift.

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