| Computer vision has always been a popular research field.The target tracking is an important research field of computer vision.Target tracking and target track recording have a very important value in the traffic monitoring,pedestrian flow,astronomical observation,navigation,equipment development and other fields.KCF tracking algorithm is a new type of high-speed tracking algorithm.By constructing a classifier between the target and the background to determine the target,it is a high-speed algorithm with fast training and fast detection.Therefore,in the real-time requirements or fast moving target tracking applications,KCF tracking algorithm has broad prospects.In the paper,KCF and tracking algorithm is analyzed.This tracking algorithm is used in a system to track fast moving targets.A variety of fast matching algorithms are studied.ORB(oriented FAST and rotated BRIEF)algorithm,which is a feature point extraction algorithm,is used.Then the PROSAC(Progressive Sample Consensus)algorithm is a good way in the matching optimization.Using the fuzzy recognition to fit the coordinate points get the target trajectory.This system contact ORB and PROSAC algorithm.In terms of accuracy and real-time,experiments show that the system can meet the practical needs.Using the algorithm mentioned in this article in the OpenCV environment to complete: 1.completed the high-speed target tracking algorithm,which solves the problem in tracking speed and precision can meet the demand;2.Improve the KCF algorithm to enable it to track the target we need;3.Combining the fast feature extraction and matching algorithm to solve the problem of the calculation of the corresponding points in binocular range distance,which is not accurate and the matching is not accurate;4.Fit the target coordinates in each frame by the nonlinear fitting algorithm to get the exact trajectory of the target.It solves the problem that the target trajectory is not precise enough. |
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