Method and device for obtaining feature information of target object and electronic equipment

Abstract

The embodiment of the invention discloses a method and device for obtaining feature information of a target object and electronic equipment. The method comprises the steps that a client obtains size information of at least one available template, wherein the size information comprises width information of the available template and height information of the available template; obtaining a corresponding search area of a to-be-tracked target object in the current frame image, creating a corresponding storage area for the search area, and storing image information associated with the search areain the storage area; determining a target template, and scaling the image information in the storage area according to the size information of the target template to generate a template image; and extracting feature information related to the target object from the template image so as to perform target tracking on the target object in the next frame of image according to the feature information.According to the scheme, the time complexity of the algorithm is reduced while the tracking effect of the algorithm is influenced as little as possible.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to a method, device and electronic equipment for obtaining feature information of a target object. Background technique [0002] Target tracking technology is a research hotspot in the field of computer vision, widely used in security (for example, road traffic scene), monitoring (for example, face recognition scene), inspection (for example, UAV tracking scene), etc. The specific target object in the video sequence is tracked, and the target object is associated in the space-time domain to obtain the motion trajectory of the target object. That is to say, after the position information of the target object to be tracked is determined in the initial frame image of the video sequence, the target object can be automatically positioned in the subsequent frame image through the target tracking technology, and the target object is predicted to be in the subsequent ...

AI Technical Summary

Problems solved by technology

[0004] The algorithms of the correlation filter series have developed rapidly, from MOSSE (Minimum Output Sum of SquaredError Filter) to CSK (Circulant Structure of Tracking-bydetection with Kernels), CN (Color Name), KCF (Kernelized Correlation Filters), DCF (DiscriminativeCorrelation Filters ) and other algorithms, the extracted feature information is becoming more and more abundant, and the positioning effect is getting better and better, but the time complexity of the algorithm is gradually increasing, and the response speed is getting slower and slower.

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