Our novel metric of visual comfort for stereoscopic content takes into account disparity, motion in depth, motion on the screen plane, and the spatial frequency of luminance contrast. Based on our measured comfort function, we derive a metric to predict the degree of comfort for short stereoscopic videos. Left: Example slice of the comfort zone computed by our comfort function for a spatial frequency of 1cpd (bounded by comfort values of 3 and 4). Right: comfort maps computed using our metric on three representative frames of the bunny movie ( c Blender Foundation). From top to bottom, input frames, per-pixel results, and per-region results (brighter red indicates less comfort). Our metric predicts less comfort with faster movement (frame 23), in agreement with the perceptual experiments. We propose a novel metric of visual comfort for stereoscopic motion, based on a series of systematic perceptual experiments. We take into account disparity, motion in depth, motion on the screen plane, and the spatial frequency of luminance contrast. We further derive a comfort metric to predict the comfort of short stereoscopic videos. We validate it on both controlled scenes and real videos available on the internet, and show how all the factors we take into account, as well as their interactions, affect viewing comfort. Last, we propose various applications that can benefit from our comfort measurements and metric.
Du et al. REF proposed a comfort metric for motion which takes into account the interaction of motion components in multiple directions, and depths.
A metric of visual comfort for stereoscopic motion
TOGS
Computer Science