Interacting with autostereograms

Abstract

Autostereograms are 2D images that can reveal 3D content when viewed with a specific eye convergence, without using extra-apparatus. We contribute to autostereogram studies from an HCI perspective. We explore touch inputs and output design options when interacting with autostereograms on smartphones. We found that an interactive help (i.e. to control the autostereogram stereo-separation), a color-based feedback (i.e. highlight of the screen), and a direct touch input can provide support for faster and more accurate interaction than a static help (i.e. static dots indicating the stereo-separation), an animated feedback (i.e., a 'pressed' effect), and an indirect input. In addition, results reveal that participants learn to perceive smaller and smaller autostereogram content faster with practice. This learning effect transfers across display devices (smartphone to desktop screen).