An Approach to Video Compression Using Saliency Based Foveation
Adam Polakovič, Radoslav Vargic, Gregor Rozinaj, Gabriel‐Miro Muntean · 2018
This research aims to increase quality of experience for video consumers by introducing an approach with saliency-based video foveation coupled with compression algorithm. This approach uses eye tracking information to build the saliency map and allows multiple usage scenarios. The approach can be used in single or multiple viewer environments. We evaluate the approach and provide results based on subjective measurements. The results confirm that the proposed approach for video compression is competitive and can deliver better quality of experience than standard video compression algorithms.