Multi-point touch tracking identification method and system

Abstract

The invention provides a multi-point touch tracking identification method and a multi-point touch tracking identification system. The method comprises the following steps of: acquiring touch point positions in two adjacent frames of images respectively; calculating the distance between the touch points of the images of the front frame and the rear frame according to the touch point positions; screening actual association between the touch points according to the distance, and gradually searching the association modes of the touch points of the images of the front frame and the rear frame according to the sequence of the distance of the touch points; and calculating the touch point dispersion degree of the association mode searched every time, and judging that the previous association modeis an optimal association mode when the touch point dispersion degree of the later association mode is greater than the touch point dispersion degree of the previous association mode for the first time. According to the multi-point touch tracking identification method and the multi-point touch tracking identification system, accuracy and robustness of the association of the touch points in the front frame and the rear frame are ensured by global analysis. By screening the actual association between the touch points, the tracking identification efficiency is improved.

Description

A multi-touch tracking recognition method and system thereof technical field The invention relates to the technical field of touch control, in particular to a multi-touch tracking identification method and system thereof. Background technique With the wide application of touch control products, touch control technology has become a hot technology in today's human-computer interaction. The control of many products is gradually replaced by touch control technology, while touch control technology is constantly challenging new application environments and fields. In the application environment of touch control based on optical images, users generally hope that the machine can support more touch point operations to meet different application requirements, and also hope that the machine can understand user intentions more intelligently, and then provide users with more natural and intelligent services . In the current touch control system, the machine judges the operation tha...

AI Technical Summary

Problems solved by technology

This method is simple and has very good real-time performance, and there are many improved versions of the algorithm at present, but this method still cannot avoid the essential defect of the misunderstanding that the closest Euclidean distance is the optimal association; another method is to use the K nearest neighbor algorithm, This method searches for K touch points with the smallest Euclidean distance in the next frame for each touch point in the previous frame, and sorts them according to the distance value, and then associates each touch point with the touch point with the smallest distance in the previous frame, If a touch point in the next frame is in the K-nearest neighbors of multiple touch points in the previous frame, the idea of ​​"minimum distance takes all" is used for priority matching. This algorithm has good real-time performance and better tracking accuracy than the former, but still It is a local optimal method, which does not consider the optimal association as a whole, that is, it still does not judge whether the current association method is optimal from a global perspective.

Images