Contactless interactive control technology with a switching system based on Butterworth filter and modified strong tracking Kalman filter

Abstract

In the human–computer interaction field, a contactless interaction with large screens through gestures is very representative, and the recognition and filtering of gesture images are very important tasks. Aiming at solving the problems of interference and positioning drift of three-dimensional lidar sensors, this article proposes a contactless interactive control system based on switching filtering algorithm, which selects the Butterworth filtering and the modified strong tracking Kalman filter to be used in the filtering process. The proposed interactive system extracts and optimizes user gestures, maps the gestures to the screen, simulates mouse operations, and enables operations such as selection, sliding, zooming in and out, and others. This switching filtering algorithm effectively solves the accuracy problem of a single filtering algorithm and the rapidity of complex filtering algorithms in the signal processing step, and greatly improves the interaction accuracy without sacrificing too much processing time. The experimental results show that by applying the proposed switching filtering algorithm to a contactless human–computer interaction system, the system can achieve smooth gesture interaction. The proposed system can perform real-time interaction with multiple people, which fully verifies the effectiveness and superiority of the proposed algorithm.