Kafa hareketleri sırasındaki 360-video deneyiminin geliştirilmesi

Efficient use of available bandwidth is vital when streaming 360-degree videos, as users rarely have enough bandwidth for a pleasant experience. The combination of viewport-dependent streaming (VDS) and rate adaptation is a promising solution to efficient bandwidth use. In VDS, the whole spherical video can be partitioned into several tiles encoded at various quality levels. The goal of this combination is to spend most of the available bandwidth on the viewport tiles. However, the direction and amount of the head motion can change the viewport tiles, resulting in low-quality content rendering until the new tiles can be replaced with high-quality versions. Moreover, head motions can influence the perception of the content to a human eye, where users can experience unfocused (blurry) content on fast head motions. First, the concept of Head-motion-aware Viewport Margins (HMAVM) was developed as a head motion-dependent safety area around the viewport and evaluated using a human head motions dataset. Later, this thesis studies how moving the head may impact the objective viewport quality assessment at short, medium and long timescales.