Ultra-HD Video Streaming in 5G Fixed Wireless Access Bottlenecks

5G Fixed Wireless Access (FWA) is an enabling technology in intelligent systems (IS) that may provide Ultra-HD (UHD) video streaming services with high Quality of Experience (QoE) in a small business use case setting. However, UHD streaming over 5G FWA is difficult in terms of latency and dependability due to numerous network factors. Due to this there may be multiple video players competing for network resources when streaming a UHD video. To date there has been very little work of 5G ‘last mile access’ streaming over bottleneck FWA Local Area Networks (LANs) under congested network conditions. The bottleneck link is the 5G FWA gateway. In these networks viewers may get sub-optimal QoE. Adaptive bitrate (ABR) algorithms are used to select the near optimal bitrates during a streaming session. To obtain the QoE of viewers in 5G FWA bottleneck networks we study the performance of four DASH-based adaptive video streaming algorithms (MPC, BOLA, Oboe and Pensive). BOLA performs the best and Pensive the worst. However, BOLA’s overall performance is sub-optimal. This work supports the need for developing new ABR algorithms for the 5G FWA environment.

Adaptive Video Caption Detection and Extraction Method Based on Color Filtering Principle

Based on the principle of color (RGB) filtering, an improved adaptive video caption detection and extraction method is proposed. Firstly, the principle of the color filtering algorithm used in the video caption detection and extraction method is analyzed, and then the algorithm is improved adaptively according to the caption pixel size to filter the noise. Finally, experiments verify the effect of this method in extracting subtitles from video. The experimental results show that the accuracy of detecting and extracting subtitles in color video is as high as 99.3%.