Perceptually-motivated Real-time Temporal Upsampling of {3D} Content for High-refresh-rate Displays

High-refresh-rate displays (e.\,g.,~120\,Hz) have recently become available on the consumer market and quickly gain on popularity. One of their aims is to reduce the perceived blur created by moving objects that are tracked by the human eye. However, an improvement is only achieved if the video stream is produced at the same high refresh rate (i.\,e.~120\,Hz). Some devices, such as LCD~TVs, solve this problem by converting low-refresh-rate content (i.\,e.~50\,Hz~PAL) into a higher temporal resolution (i.\,e.~200\,Hz) based on two-dimensional optical flow. In our approach, we will show how rendered three-dimensional images produced by recent graphics hardware can be up-sampled more efficiently resulting in higher quality at the same time. Our algorithm relies on several perceptual findings and preserves the naturalness of the original sequence. A psychophysical study validates our approach and illustrates that temporally up-sampled video streams are preferred over the standard low-rate input by the majority of users. We show that our solution improves task performance on high-refresh-rate displays