Research on optimization methods for human–computer interaction interfaces based on 3D reconstruction and computer vision

To enhance the rationality of human-computer interface layouts and improve user satisfaction, this study investigates an optimization design method for human-computer interfaces based on visual communication technology. Utilizing three-dimensional spatial reconstruction techniques, the visual communication image is reconstructed in 3D starting from its central point, guided by the center of parallel curves and local ridge lines within the image. The visual communication index of each visual perception element is calculated from the 3D reconstruction results. An optimization model for the HMI is constructed with the objective of maximizing the visual communication index. The particle swarm optimization (PSO) algorithm is selected to solve this optimization model. A dynamic inertia weight is introduced to enhance the PSO algorithm, generating an optimized design solution for the HMI. Experimental results demonstrate that this method achieves efficient layout of visual perception elements within the HMI. The peak signal-to-noise ratio (SNR) of the optimized HMI design exceeds 30 dB.