In recent years there has been a predominant increase in multimedia services such as live streaming, Video on Demand (VoD), video conferencing, videos for the learning. Streaming of high quality videos has become a challenge for service providers to enhance the user’s watching experience. The service providers cannot guarantee the perceived quality. In order to enhance the user’s expectations, it is also important to estimate the quality of video perceived by the user. There are different video streaming protocols that are used to stream from server to client. In this research, we aren’t focused on the user’s experience. We are mainly focused on the performance behavior of the protocols. In this study, we investigate the performance of the HTTP, RTSP and WebRTC protocols when streaming is carried out for H.265 encoder. The study addresses for the objective assessment of different protocols over VoD streaming at the network and application layers. Packet loss and delay variations are altered at the network layer using network emulator NetEm when streaming from server to client. The metrics at the network layer and application layer are collected and analyzed. The video is streamed from server to a client, the quality of the video is checked by some of the users. The research method has been carried out using an experimental testbed. The metrics such as packet counts at network layer and stream bitrate at application layer are collected for HTTP, RTSP and WebRTC protocols. Variable delays and packet losses are injected into the network to emulate real world. Based on the results obtained, it was found at the application layer that, out of the three protocols, HTTP, RTSP and WebRTC, the stream bitrate of the video transmitted using HTTP was less when compared to the other. Hence, HTTP performs better in the application layer. At the network layer, the packet counts of the video transmitted were collected using TCP port for HTTP and UDP port for RTSP and WebRTC protocols. The performance of HTTP was found to be stable in most of the scenarios. On comparing RTSP and WebRTC, the number of packet counts collected were more in number for RTSP when compared to WebRTC. This is because, the protocol and also the streamer are using more resources to transmit the video. Hence, both the protocols RTSP and WebRTC are performing better relatively.

This semestral thesis describes the possibilities of source coding videos, the attributes of the videos and their recommended changes for test. Subjective methods of scores of quality and their division into metrics with references and without references are delineated. In this work, a draft of videos for test of comparison of set metrics is specified here. Further, the coding and options of attributes of videosequences for scoring of the quality of the picture is presented. The displaying system is described and quazicrowdsorcing system of collecting the datas was created.

Video transcoding is the process of converting compressed video signals to adapt video characteristics such as video bit rate, video resolution, or video codec, so as to meet the specifications of communication channels and endpoint devices. A straightforward transcoding solution is to fully decode and encode the video. However this method is computationally expensive and thus unsuitable in applications with tight resource constraints such as in software-based real-time environment. Therefore, efficient transcoding meth- ods are required to reduce the transcoding complexity while preserving video quality. Prior transcoding methods are suitable for video coding standards such as H.264/AVC and MPEG-2. H.265/HEVC has introduced new coding concepts, e.g., the quad-tree-based block structure, that are fundamentally different from those in prior standards. These concepts require existing transcoding methods to be adapted and novel solutions to be developed. This work primarily addressed the issue of efficient HEVC transcoding for bit rate adaptation (reduction). The goal is to understand the transcoding behaviour for some straightforward transcoding strategies, and to subsequently optimize the complexity/quality trade-off by providing heuristics to reduce the number of coding options to evaluate. A transcoder prototype is developed based on the HEVC reference software HM-8.2. The proposed transcoder reduces the transcoding time compared to full decoding and encoding by at least 80% while inducing a coding performance drop within a margin for 5%. The thesis has been carried out in collaboration with Ericsson Research in Stockholm / Video content is produced daily through variety of electronic devices, however, storing and transmitting video signals in raw format is impractical due to its excessive resource requirement. Today popular video coding standards such as MPEG-4 and H.264 are used to compress the video signals before storing and transmitting. Accordingly, efficient video coding plays an important role in video communications. While video applications become wide-spread, there is a need for high compression and low complexity video coding algorithms that preserve image quality. Standard organizations ISO, ITO, VCEG of ITU-T, and collaboration of many companies have developed video coding standards in the past to meet video coding requirements of the day. The Advanced Video Coding (AVC/H.264) standard is the most widely used video coding method. AVC is commonly known to be one of the major standards used in Blue Ray devices for video compression. It is also widely used by video streaming services, TV broadcasting, and video conferencing applications. Currently the most important development in this area is the introduction of H.265/HEVC standard which has been finalized in January 2013. The aim of standardization is to produce video compression specification that is capable of compression twice as effective as H.264/AVC standard in terms of coding complexity and quality. There is a wide range of platforms that receive digital video. TVs, personal computers, mobile phones, and tablets each have different computational, display, and connectivity capabilities, thus video has to be converted to meet the specifications of target platform. This conversion is achieved through video transcoding. For transcoding, straightforward solution is to decode the compressed video signal and re-encode it to the target compression format, but this process is computationally complex. Particularly in real-time applications, there is a need to exploit the information that is already available through the compressed video bit-stream to speed-up the conversion. The objective of this thesis is to investigate efficient transcoding methods for HEVC. Using decode/re-encode as the performance reference, methods for advanced transcoding will be investigated. / 0760609667 Bäckgårdsvägen 49, 14341 Stockholm

This diploma thesis deals with design of embedded computer vision system and transfer of existing computer vision application for 3D object detection from Windows OS to designed embedded system with Linux OS. Thesis focuses on design of communication interface for system control and camera video transfer through local network with video compression. Then, detection algorithm is enhanced by transferring computationally expensive functions to GPU using CUDA technology. Finally, a user application with graphical interface is designed for system control on Windows platform.

This diploma thesis deals with standard objective and subjective video quality assessments and with analysis of their applicability to HEVC. Also basic description of video compression standard H.265/HEVC is presented. The main focus of the thesis is a creation of the database of compressed video sequences. Important parameters and features of the reference encoder HM-12 are discussed. Selected methods of objective video quality assessments are implemented on the created database. A part of this thesis is also a suggestion of method for objective video quality assessment, application of this method and associated data collection. Final data is statistically analyzed and it’s correlation with objective tests is discussed.

In July 2014, the second version of the HEVC/H.265 video coding standard was announced, and it included the Scalable High efficiency Video Coding (SHVC) extension. SHVC is used for coding a video stream with subset streams of the same video with lower quality, and it supports spatial, temporal and SNR scalability among others. This is used to enable easy adaption of a video stream, by dropping or adding packages, to devices with different screen sizes, computing power and bandwidth. In this project SHVC has been implemented in Ericsson's research encoder C65. Some cross-layer optimizations have also been implemented and evaluated. The main goal of these optimizations are to make better decisions when choosing the reference layer's motion parameters and QP, by doing multi-pass coding and using the coded enhancement layer information from the first pass.