Abstract360-degree videos have become increasingly popular with the application of virtual reality (VR) technology. To encode such kind of videos with ultra-high resolution, an efficient and real-time video encoder becomes a key requirement. The Versatile Video Coding (VVC) standard has good coding performance. However, it has pretty high computational complexity which increasing the application cost of 360-degree videos. Among them, the decision of the quadtree with nested multi-type tree (QTMT) partitioning structure is one of the time-consuming procedures. In this paper, based on the characteristics of 360-degree video with Equirectangular projection (ERP) format, the empirical variogram combined with Mahalanobis distance is introduced to measure the difference between the horizontal and vertical directions of the CU, and a fast partition algorithm is proposed. The experimental results show that the algorithm saves 32.13% of the coding time with only an increase of 0.66% in BDBR.

In order to overcome the issues that Support Vector Machine is sensitive to the outlier and noise points, Fuzzy Support Vector Machine (FSVM) is proposed. The key issue to solve the FSVM is determinate the fuzzy membership. This paper gives an overview of construction algorithm of the fuzzy membership. We also give an algorithm to solve FSVM that is derived from improved-SMO algorithm.

360-degree videos have become increasingly popular with the development of virtual reality (VR) technology. These videos are converted to a 2D image plane format before being encoded with standard encoders. To improve coding efficiency, a new generation video coding standard has been launched to be known as Versatile Video Coding (VVC). However, the computational complexity of VVC makes it time-consuming to compress 360-degree videos of high resolution. The diversity of CU partitioning modes of VVC greatly increases the computational complexity. Through statistical experiments on ERP videos, it is found that the probability of using horizontal partitioning for such videos is greater than that of vertical partitioning. The empirical variogram combined with Mahalanobis distance is proposed to measure texture orientation information. The experimental results show that the algorithm saves 32.13% of the coding time with only 0.66% BDBR increasing.