References [1] Ramanathan Palaniappan, Nitin Suresh and Nikil Jayant, “Objective measurement of transcoded video quality in mobile applications”,IEEE MoVID 2008 (workshop as a part of WoWMoM 2008), Newport Beach, CA, June Conclusion & Current Work MTBF estimates from AVQ scores : – show a wide range across transcoding bit rates and codecs. – are subjectively more meaningful. – better represent the slight variations in degraded visual quality. Our current focus (in a Cisco Research Project) : – the analysis of network artifacts (NA) on video quality – Using these automatic VQ measurements to enhance the streaming of IP video Today’s Video Delivery Scenario The Video Quality (VQ) Challenge Develop subjectively meaningful metrics Must be objective, enabling real time computation Zero Reference (ZR) nature – independent of source video Our Solution Mean Time Between failures (MTBF) – Failure refers to video artifacts deemed to be perceptually noticeable – Directly related to Mean Opinion Score (MOS) Automatic Video Quality (AVQ) – Objective estimate of MTBF for the transcoding experiments Metrics used in our work PSNR – Simple full Reference metric – Computes pixel by pixel difference per frame basis b/w source and processed video – Actual value not definitive but comparison b/w two values measures quality Automatic Video Quality (AVQ) – Zero Reference metric – Based on Spatio temporal algorithms and knowledge of Human Visual System AVQ Metric Computation based on output pixel values AVQ score shows excellent subjective attributes Our Transcoding Platform – VLC Flexible transcoding options like different codecs, variable bit rate, GOP size etc. 2 transcoding operations – MPEG 2 to H.264 – MPEG 2 to MPEG 4 SP Experimental Setup Results Sample Frames Objective Measurement of Transcoded Video Quality in Mobile Applications Ramanathan Palaniappan, Nitin Suresh and Nikil Jayant School of ECE, Georgia Institute of Technology, Atlanta, GA Network Video Server & Transcoder Projectors 3G Smart Phones HD TVs LaptopsLCD Displays MPEG 2 to H.264 Transcoder 384 – 192 Kbps MPEG 2 to MPEG 4 Transcoder 384 – 192 Kbps MPEG 2 Transrater 384 – 192 Kbps MPEG Kbps 72 sec (QCIF) H.264 MPEG 4 MPEG 2 Fig. 1 : (a) plots PSNR for the video transcoded into H.264, MPEG 4 and MPEG 2 at 192 Kbps. (b) plots AVQ compression artifact (CA) score for the same case (Range : 0 – best and 1 – worst). (a) (b) Fig. 2 : (a) plots PSNR for the same video transcoded at 192, 256 and 384 Kbps with the MPEG 4 transcoder. (b) plots AVQ compression artifact (CA) score for the same case. (a) (b) Bit rate192 kbps256 Kbps384 Kbps CodecMTBFPSNRMTBFPSNRMTBFPSNR H MPEG MPEG Table 1 : PSNR (dB) & estimated MTBF (sec) based on AVQ CA Score (a) (c) (b) Fig. 3 : Frame # 508 transcoded at 192 Kbps into (a) MPEG 2, (b) MPEG 4 & (c) H.264 Fig. 4 : Frame # 1469 transcoded into MPEG 4 at (a) 192 Kbps, (b) 256 Kbps & (c) 384 Kbps (a) (b) (c)