IP-Soc Shanghai 2017 ALLEGRO Presentation FINAL
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Microsoft Powerpoint
Development of Multimedia WebApp on Tizen Platform 1. HTML Multimedia 2. Multimedia Playing with HTML5 Tags (1) HTML5 Video (2) HTML5 Audio (3) HTML Pulg-ins (4) HTML YouTube (5) Accessing Media Streams and Playing (6) Multimedia Contents Mgmt (7) Capturing Images 3. Multimedia Processing Web Device API Multimedia WepApp on Tizen - 1 - 1. HTML Multimedia • What is Multimedia ? − Multimedia comes in many different formats. It can be almost anything you can hear or see. − Examples : Pictures, music, sound, videos, records, films, animations, and more. − Web pages often contain multimedia elements of different types and formats. • Multimedia Formats − Multimedia elements (like sounds or videos) are stored in media files. − The most common way to discover the type of a file, is to look at the file extension. ⇔ When a browser sees the file extension .htm or .html, it will treat the file as an HTML file. ⇔ The .xml extension indicates an XML file, and the .css extension indicates a style sheet file. ⇔ Pictures are recognized by extensions like .gif, .png and .jpg. − Multimedia files also have their own formats and different extensions like: .swf, .wav, .mp3, .mp4, .mpg, .wmv, and .avi. Multimedia WepApp on Tizen - 2 - 2. Multimedia Playing with HTML5 Tags (1) HTML5 Video • Some of the popular video container formats include the following: Audio Video Interleave (.avi) Flash Video (.flv) MPEG 4 (.mp4) Matroska (.mkv) Ogg (.ogv) • Browser Support Multimedia WepApp on Tizen - 3 - • Common Video Format Format File Description .mpg MPEG. Developed by the Moving Pictures Expert Group. The first popular video format on the MPEG .mpeg web. -
On Audio-Visual File Formats
On Audio-Visual File Formats Summary • digital audio and digital video • container, codec, raw data • different formats for different purposes Reto Kromer • AV Preservation by reto.ch • audio-visual data transformations Film Preservation and Restoration Hyderabad, India 8–15 December 2019 1 2 Digital Audio • sampling Digital Audio • quantisation 3 4 Sampling • 44.1 kHz • 48 kHz • 96 kHz • 192 kHz digitisation = sampling + quantisation 5 6 Quantisation • 16 bit (216 = 65 536) • 24 bit (224 = 16 777 216) • 32 bit (232 = 4 294 967 296) Digital Video 7 8 Digital Video Resolution • resolution • SD 480i / SD 576i • bit depth • HD 720p / HD 1080i • linear, power, logarithmic • 2K / HD 1080p • colour model • 4K / UHD-1 • chroma subsampling • 8K / UHD-2 • illuminant 9 10 Bit Depth Linear, Power, Logarithmic • 8 bit (28 = 256) «medium grey» • 10 bit (210 = 1 024) • linear: 18% • 12 bit (212 = 4 096) • power: 50% • 16 bit (216 = 65 536) • logarithmic: 50% • 24 bit (224 = 16 777 216) 11 12 Colour Model • XYZ, L*a*b* • RGB / R′G′B′ / CMY / C′M′Y′ • Y′IQ / Y′UV / Y′DBDR • Y′CBCR / Y′COCG • Y′PBPR 13 14 15 16 17 18 RGB24 00000000 11111111 00000000 00000000 00000000 00000000 11111111 00000000 00000000 00000000 00000000 11111111 00000000 11111111 11111111 11111111 11111111 00000000 11111111 11111111 11111111 11111111 00000000 11111111 19 20 Compression Uncompressed • uncompressed + data simpler to process • lossless compression + software runs faster • lossy compression – bigger files • chroma subsampling – slower writing, transmission and reading • born -
Amphion Video Codecs in an AI World
Video Codecs In An AI World Dr Doug Ridge Amphion Semiconductor The Proliferance of Video in Networks • Video produces huge volumes of data • According to Cisco “By 2021 video will make up 82% of network traffic” • Equals 3.3 zetabytes of data annually • 3.3 x 1021 bytes • 3.3 billion terabytes AI Engines Overview • Example AI network types include Artificial Neural Networks, Spiking Neural Networks and Self-Organizing Feature Maps • Learning and processing are automated • Processing • AI engines designed for processing huge amounts of data quickly • High degree of parallelism • Much greater performance and significantly lower power than CPU/GPU solutions • Learning and Inference • AI ‘learns’ from masses of data presented • Data presented as Input-Desired Output or as unmarked input for self-organization • AI network can start processing once initial training takes place Typical Applications of AI • Reduce data to be sorted manually • Example application in analysis of mammograms • 99% reduction in images send for analysis by specialist • Reduction in workload resulted in huge reduction in wrong diagnoses • Aid in decision making • Example application in traffic monitoring • Identify areas of interest in imagery to focus attention • No definitive decision made by AI engine • Perform decision making independently • Example application in security video surveillance • Alerts and alarms triggered by AI analysis of behaviours in imagery • Reduction in false alarms and more attention paid to alerts by security staff Typical Video Surveillance -
Realaudio and Realvideo Content Creation Guide
RealAudioâ and RealVideoâ Content Creation Guide Version 5.0 RealNetworks, Inc. Contents Contents Introduction......................................................................................................................... 1 Streaming and Real-Time Delivery................................................................................... 1 Performance Range .......................................................................................................... 1 Content Sources ............................................................................................................... 2 Web Page Creation and Publishing................................................................................... 2 Basic Steps to Adding Streaming Media to Your Web Site ............................................... 3 Using this Guide .............................................................................................................. 4 Overview ............................................................................................................................. 6 RealAudio and RealVideo Clips ....................................................................................... 6 Components of RealSystem 5.0 ........................................................................................ 6 RealAudio and RealVideo Files and Metafiles .................................................................. 8 Delivering a RealAudio or RealVideo Clip ...................................................................... -
(A/V Codecs) REDCODE RAW (.R3D) ARRIRAW
What is a Codec? Codec is a portmanteau of either "Compressor-Decompressor" or "Coder-Decoder," which describes a device or program capable of performing transformations on a data stream or signal. Codecs encode a stream or signal for transmission, storage or encryption and decode it for viewing or editing. Codecs are often used in videoconferencing and streaming media solutions. A video codec converts analog video signals from a video camera into digital signals for transmission. It then converts the digital signals back to analog for display. An audio codec converts analog audio signals from a microphone into digital signals for transmission. It then converts the digital signals back to analog for playing. The raw encoded form of audio and video data is often called essence, to distinguish it from the metadata information that together make up the information content of the stream and any "wrapper" data that is then added to aid access to or improve the robustness of the stream. Most codecs are lossy, in order to get a reasonably small file size. There are lossless codecs as well, but for most purposes the almost imperceptible increase in quality is not worth the considerable increase in data size. The main exception is if the data will undergo more processing in the future, in which case the repeated lossy encoding would damage the eventual quality too much. Many multimedia data streams need to contain both audio and video data, and often some form of metadata that permits synchronization of the audio and video. Each of these three streams may be handled by different programs, processes, or hardware; but for the multimedia data stream to be useful in stored or transmitted form, they must be encapsulated together in a container format. -
Encoding H.264 Video for Streaming and Progressive Download
W4: KEY ENCODING SKILLS, TECHNOLOGIES TECHNIQUES STREAMING MEDIA EAST - 2019 Jan Ozer www.streaminglearningcenter.com [email protected]/ 276-235-8542 @janozer Agenda • Introduction • Lesson 5: How to build encoding • Lesson 1: Delivering to Computers, ladder with objective quality metrics Mobile, OTT, and Smart TVs • Lesson 6: Current status of CMAF • Lesson 2: Codec review • Lesson 7: Delivering with dynamic • Lesson 3: Delivering HEVC over and static packaging HLS • Lesson 4: Per-title encoding Lesson 1: Delivering to Computers, Mobile, OTT, and Smart TVs • Computers • Mobile • OTT • Smart TVs Choosing an ABR Format for Computers • Can be DASH or HLS • Factors • Off-the-shelf player vendor (JW Player, Bitmovin, THEOPlayer, etc.) • Encoding/transcoding vendor Choosing an ABR Format for iOS • Native support (playback in the browser) • HTTP Live Streaming • Playback via an app • Any, including DASH, Smooth, HDS or RTMP Dynamic Streaming iOS Media Support Native App Codecs H.264 (High, Level 4.2), HEVC Any (Main10, Level 5 high) ABR formats HLS Any DRM FairPlay Any Captions CEA-608/708, WebVTT, IMSC1 Any HDR HDR10, DolbyVision ? http://bit.ly/hls_spec_2017 iOS Encoding Ladders H.264 HEVC http://bit.ly/hls_spec_2017 HEVC Hardware Support - iOS 3 % bit.ly/mobile_HEVC http://bit.ly/glob_med_2019 Android: Codec and ABR Format Support Codecs ABR VP8 (2.3+) • Multiple codecs and ABR H.264 (3+) HLS (3+) technologies • Serious cautions about HLS • DASH now close to 97% • HEVC VP9 (4.4+) DASH 4.4+ Via MSE • Main Profile Level 3 – mobile HEVC (5+) -
Compression for Great Video and Audio Master Tips and Common Sense
Compression for Great Video and Audio Master Tips and Common Sense 01_K81213_PRELIMS.indd i 10/24/2009 1:26:18 PM 01_K81213_PRELIMS.indd ii 10/24/2009 1:26:19 PM Compression for Great Video and Audio Master Tips and Common Sense Ben Waggoner AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Focal Press is an imprint of Elsevier 01_K81213_PRELIMS.indd iii 10/24/2009 1:26:19 PM Focal Press is an imprint of Elsevier 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA Linacre House, Jordan Hill, Oxford OX2 8DP, UK © 2010 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions . This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this fi eld are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. -
REALNETWORKS PRODUCTION GUIDE with Realone Player Last Update: 1 October 2002 Realnetworks, Inc
REALNETWORKS PRODUCTION GUIDE With RealOne Player Last Update: 1 October 2002 RealNetworks, Inc. PO Box 91123 Seattle, WA 98111-9223 U.S.A. http://www.real.com http://www.realnetworks.com ©2002 RealNetworks, Inc. All rights reserved. Information in this document is subject to change without notice. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of RealNetworks, Inc. Printed in the United States of America. Helix, The Helix Logo, RBN, the Real "bubble" (logo), Real Broadcast Network, RealAudio, Real.com, RealJukebox, RealMedia, RealNetworks, RealPlayer, RealOne, RealPresenter, RealSlideshow, RealSystem, RealText, RealVideo, SureStream, and Surreal.FX Design are trademarks or registered trademarks of RealNetworks, Inc. Other product and corporate names may be trademarks or registered trademarks of their respective companies. SUMMARY OF CONTENTS DOCUMENTATION RELEASE NOTE .......................................................................................1 INTRODUCTION.....................................................................................................................5 PART I: GETTING STARTED WITH STREAMING MEDIA 1 NEW FEATURES .........................................................................................................17 2 PRESENTATION PLANNING.......................................................................................27 PART II: PRODUCING CLIPS 3 AUDIO PRODUCTION ...............................................................................................59 -
Audio and Video Standards for Online Learning Kevin Reeve, Utah State University
... from the Dr. C Library Audio and Video Standards for Online Learning Kevin Reeve, Utah State University Introduction Digital media is a powerful tool that can enhance your online course. Recent devel- opments and market trends have changed the rules and media formats that need to be considered when creating media for your course. Choosing the correct video and audio format is the first step to insuring a successful experience for both instructor and student. Podcasts, a form of digital media meant for downloading to a portable media device are included in this discussion. Video and Audio Formats Popular media formats for audio and video include RealAudio® and RealVideo®, Win- dows Media®, MPEG 3, and MPEG 4. Each requires software that will encode video/ audio to that format, and also a player that will decode the video/audio for playback. All these formats are currently being used in e-learning with great success. The latest market trends are now suggesting that MPEG 4 for video and audio and MPEG 3 for audio only are “the” standards for digital media. Why MPEG 4 and MPEG 3? MPEG 4 and MPEG 3 are the standard because of consumer response. Apple ad- opted MPEG 4 early on as the video format for playback on their iPod®s that support video. Apple and YouTube worked together to allow YouTube video to be accessed by an Apple TV®, iPhones®, and the iPod® Touch. YouTube moved from Flash Video to MPEG 4 to accommodate these devices, and Adobe soon followed by updating its Flash Player to play MPEG 4 video and audio. -
Codec Is a Portmanteau of Either
What is a Codec? Codec is a portmanteau of either "Compressor-Decompressor" or "Coder-Decoder," which describes a device or program capable of performing transformations on a data stream or signal. Codecs encode a stream or signal for transmission, storage or encryption and decode it for viewing or editing. Codecs are often used in videoconferencing and streaming media solutions. A video codec converts analog video signals from a video camera into digital signals for transmission. It then converts the digital signals back to analog for display. An audio codec converts analog audio signals from a microphone into digital signals for transmission. It then converts the digital signals back to analog for playing. The raw encoded form of audio and video data is often called essence, to distinguish it from the metadata information that together make up the information content of the stream and any "wrapper" data that is then added to aid access to or improve the robustness of the stream. Most codecs are lossy, in order to get a reasonably small file size. There are lossless codecs as well, but for most purposes the almost imperceptible increase in quality is not worth the considerable increase in data size. The main exception is if the data will undergo more processing in the future, in which case the repeated lossy encoding would damage the eventual quality too much. Many multimedia data streams need to contain both audio and video data, and often some form of metadata that permits synchronization of the audio and video. Each of these three streams may be handled by different programs, processes, or hardware; but for the multimedia data stream to be useful in stored or transmitted form, they must be encapsulated together in a container format. -
PVQ Applied Outside of Daala (IETF 97 Draft)
PVQ Applied outside of Daala (IETF 97 Draft) Yushin Cho Mozilla Corporation November, 2016 Introduction ● Perceptual Vector Quantization (PVQ) – Proposed as a quantization and coefficient coding tool for NETVC – Originally developed for the Daala video codec – Does a gain-shape coding of transform coefficients ● The most distinguishing idea of PVQ is the way it references a predictor. – PVQ does not subtract the predictor from the input to produce a residual Mozilla Corporation 2 Integrating PVQ into AV1 ● Introduction of a transformed predictors both in encoder and decoder – Because PVQ references the predictor in the transform domain, instead of using a pixel-domain residual as in traditional scalar quantization ● Activity masking, the major benefit of PVQ, is not enabled yet – Encoding RDO is solely based on PSNR Mozilla Corporation 3 Traditional Architecture Input X residue Subtraction Transform T signal R predictor P + decoded X Inverse Inverse Scalar decoded R Transform Quantizer Quantizer Coefficient bitstream of Coder coded T(X) Mozilla Corporation 4 AV1 with PVQ Input X Transform T T(X) PVQ Quantizer PVQ Coefficient predictor P Transform T T(X) Coder PVQ Inverse Quantizer Inverse dequantized bitstream of decoded X Transform T(X) coded T(X) Mozilla Corporation 5 Coding Gain Change Metric AV1 --> AV1 with PVQ PSNR Y -0.17 PSNR-HVS 0.27 SSIM 0.93 MS-SSIM 0.14 CIEDE2000 -0.28 ● For the IETF test sequence set, "objective-1-fast". ● IETF and AOM for high latency encoding options are used. Mozilla Corporation 6 Speed ● Increase in total encoding time due to PVQ's search for best codepoint – PVQ's time complexity is close to O(n*n) for n coefficients, while scalar quantization has O(n) ● Compared to Daala, the search space for a RDO decision in AV1 is far larger – For the 1st frame of grandma_qcif (176x144) in intra frame mode, Daala calls PVQ 3843 times, while AV1 calls 632,520 times, that is ~165x. -
Efficient Multi-Codec Support for OTT Services: HEVC/H.265 And/Or AV1?
Efficient Multi-Codec Support for OTT Services: HEVC/H.265 and/or AV1? Christian Timmerer†,‡, Martin Smole‡, and Christopher Mueller‡ ‡Bitmovin Inc., †Alpen-Adria-Universität San Francisco, CA, USA and Klagenfurt, Austria, EU ‡{firstname.lastname}@bitmovin.com, †{firstname.lastname}@itec.aau.at Abstract – The success of HTTP adaptive streaming is un- multiple versions (e.g., different resolutions and bitrates) and disputed and technical standards begin to converge to com- each version is divided into predefined pieces of a few sec- mon formats reducing market fragmentation. However, other onds (typically 2-10s). A client first receives a manifest de- obstacles appear in form of multiple video codecs to be sup- scribing the available content on a server, and then, the client ported in the future, which calls for an efficient multi-codec requests pieces based on its context (e.g., observed available support for over-the-top services. In this paper, we review the bandwidth, buffer status, decoding capabilities). Thus, it is state of the art of HTTP adaptive streaming formats with re- able to adapt the media presentation in a dynamic, adaptive spect to new services and video codecs from a deployment way. perspective. Our findings reveal that multi-codec support is The existing different formats use slightly different ter- inevitable for a successful deployment of today's and future minology. Adopting DASH terminology, the versions are re- services and applications. ferred to as representations and pieces are called segments, which we will use henceforth. The major differences between INTRODUCTION these formats are shown in Table 1. We note a strong differ- entiation in the manifest format and it is expected that both Today's over-the-top (OTT) services account for more than MPEG's media presentation description (MPD) and HLS's 70 percent of the internet traffic and this number is expected playlist (m3u8) will coexist at least for some time.