Dynamic Stereoscopic 3D Parameter Adjustments For Enhanced Depth Discrimination

Most modern stereoscopic 3D applications use fixed stereoscopic 3D parameters (separation and convergence) to render the scene on a 3D display. But, keeping these parameters fixed during usage does not always provide the best experience since it can reduce the amount of depth perception possible in some applications which have large variability in object distances. We developed two stereoscopic rendering techniques which actively vary the stereo parameters based on the scene content. Our first algorithm calculates a low resolution depth map of the scene and chooses ideal stereo parameters based on that depth map. Our second algorithm uses eye tracking data to get the gaze direction of the user and chooses ideal stereo parameters based on the distance of the gazed object. We evaluated our techniques in an experiment that uses three depth judgment tasks: depth ranking, relative depth judgment and path tracing. Our results indicate that variable stereo parameters provide enhanced depth discrimination compared to static parameters and were preferred by our participants over the traditional fixed parameter approach. We discuss our findings and possible implications on the design of future stereoscopic 3D applications