Transcoding based optimum quality video streaming under limited bandwidth *Michael Medagama, **Dileeka Dias, ***Shantha Fernando *Dialog-University of Moratuwa Mobile Communications Research Laboratory **Department of Electronics and Telecommunication Engineering ***Department of Computer Science and Engineering University of Moratuwa 報告者 : 饒展榕

Outline Introduction Transcoding-based streaming Video quality measurement Test environment Results

I. INTRODUCTION Multimedia applications play a major role in data communication. Applications such as YouTube® and metacafe® are some of the most popular internet applications that are accessed not only through internet-based PCs, but also through mobile networks.

Despite development of broadband technologies,limitations exist still in rich video streaming. Especially the allowable data rate per user decreases as the number of users that share the network increases. The data rate perceived by the user decreases as the user’s distance to the base station increases in the mobile environment. Therefore users will experience interruption of the video.

This paper addresses the study of adaptive video streaming through transcoding with the data rate/data volume and video quality measurement calculated though objective measurement techniques. Linux based Video LAN Client(VLC)/ffmpeg environment was set up to stream the video in a local area network. Netlimiter is used to observe the instantaneous data rate perceived.

II. TRANSCODING-BASED STREAMING a. Transcoding b. Quantization factor c. Frame rate

The video encoding process comprises of converting raw video data into discrete cosine transformed data, quantization and finally the process of run length coding to compress the quantized DCT coefficients. Such data blocks are transmitted via the network so that the receiver decodes the data which is the inverse process of above to reproduce the data using a media player.

a. Transcoding Transcoding is the process of converting one form of video to another in the compression domain. it is possible to stream the multimedia content with different video parameters using transcoding where the video information is scaled down. high resolution video requires a high data rate while lower resolution video may require less. In that case resolution of the video might become a transcoding parameter to be appropriately selected before streaming to meet the available network bandwidth.

Transcoding, or in general, video adaptation for scalability could be in the form of temporal scaling, spatial scaling or both. The frame rate is the key parameter that could be changed to achieve temporal scaling. Spatial scaling is achieved by varying the quantization of the encoding process.

The quantization level defines how much information is stored in a block of a frame in terms of bits. There is more information in each block when the level of quantization is high, which leads to the requirement of high data rate in the transmission and hence provides higher quality.

b. Quantization factor (DCT) coefficients shall be quantized in many different levels in the quantization process. The level of quantization or the resolution of the quantization reflects the amount of information and the quality of a video block of the frame being quantized. DCT coefficients in a block of the frame shall have certain amount of information which is part of the total video sequence. Information in the continuous domain gathered as DCT coefficients are transformed into the discrete domain with the DCT quantization.

The“quantization factor” that comes with the ffmpeg video library which used in this study maps to the level of quantization that also directly relates to the quality. It is simply an integer index that map to the resolution of the quantization when quantizing the DCT coefficients. Lower quantization factors reflect higher resolution leading to higher data volume and better quality. Data volume and quality drops as the quantization factor increases.

c. Frame rate The frame rate is the number of frames being processed for streaming. The amount of the information in the video will vary with varying the frame rate to achieve temporal scalability. In a limited bandwidth situation, even a poorer quality video at a lower frame rate may be perceived to be of a better quality compared to the same video with interruptions. It was observed that videos having frame rates of give poor quality of perception. Frame rate above 15 gives an acceptable level of quality.

III. VIDEO QUALITY MEASUREMENT This is called the Mean opinion score (MOS) and has values ranging from 5 for best to 1 for poor. The average of the opinions of those polled will be the quality of the video.

IV. TEST ENVIRONMENT

V. RESULTS

VI. CONCLUSION Comparison of video quality and data rate/data volume with the change of transcoding parameters is carried out in this study. With low frame rate and low quantized resolution the data volume of the video can be reduced to a great extent. Since the data volume is less, the required bandwidth also less. In low bandwidth situations, transcoding can be appliedto meet the available resources.