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.

Study on Optimization of Infrasound Filtering Method for Coal Sample Failure under Load

“…Some scholars have improved the signal acquisition instrument to control the signal frequency acquisition range, reducing the interference of unnecessary signals on the acquisition results (Fiala et al, 1965;Park and Robertson, 2009;Chen et al, 2020a;Zhou et al, 2020). Some scholars filtered the collected signals by constructing FIR filters, Butterworth filters, Kalman filters, and other band-pass filters to filter out the noise signals in the test results (Flandrin et al, 2004;Christov et al, 2017;Jianping et al, 2017;Jia et al, 2017b;Shibendu et al, 2020;Fang et al, 2021). Regardless of whether it is transforming a signal acquisition instrument or constructing a band-pass filter, it can only filter the noise signal in the non-target frequency band.…”