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http://dx.doi.org/10.3837/tiis.2019.06.022

Fast Algorithm for 360-degree Videos Based on the Prediction of Cu Depth Range and Fast Mode Decision  

Zhang, Mengmeng (North china university of technology)
Zhang, Jing (North china university of technology)
Liu, Zhi (North china university of technology)
Mao, Fuqi (North china university of technology)
Yue, Wen (China university of geosciences)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.6, 2019 , pp. 3165-3181 More about this Journal
Abstract
Spherical videos, which are also called 360-degree videos, have become increasingly popular due to the rapid development of virtual reality technology. However, the large amount of data in such videos is a huge challenge for existing transmission system. To use the existing encode framework, it should be converted into a 2D image plane by using a specific projection format, e.g. the equi-rectangular projection (ERP) format. The existing high-efficiency video coding standard (HEVC) can effectively compress video content, but its enormous computational complexity makes the time spent on compressing high-frame-rate and high-resolution 360-degree videos disproportionate to the benefits of compression. Focusing on the ERP format characteristics of 360-degree videos, this work develops a fast decision algorithm for predicting the coding unit depth interval and adaptive mode decision for intra prediction mode. The algorithm makes full use of the video characteristics of the ERP format by dealing with pole and equatorial areas separately. It sets different reference blocks and determination conditions according to the degree of stretching, which can reduce the coding time while ensuring the quality. Compared with the original reference software HM-16.16, the proposed algorithm can reduce time consumption by 39.3% in the all-intra configuration, and the BD-rate increases by only 0.84%.
Keywords
360-Degree Video; CU Partition; Fast Mode Selection; RMD Optimization;
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Times Cited By KSCI : 1  (Citation Analysis)
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