Applications Analysis of Video Streaming in Industrial
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Capturejayhx Release Notes
CapturejayHX release notes - Version 2.3.7 - 1.7.17.10600 – 09/01/2019 - capturejayHX adds support for streaming and network playback of Secure Reliable Transport (SRT) feeds. SRT is a protocol designed for live video streaming over the public internet and provides reliable transmission similar to TCP, however, it does so at the application layer, using UDP protocol as an underlying transport layer. It supports packet recovery while maintaining low latency (default: 120 ms). SRT also supports encryption using AES. - Added RTP streaming support - Added RTP Pro-MPEG streaming support - Added MJPEG encoder for UDP streaming - Updated FFmpeg to version 4.0.2 - Added QuickSync H.264 video encoding and multichannel audio support (up to 16 channels) for WebRTC - Improved playback of RTSP streams. - Updated NDI to 3.5 version. - Updated NVIDIA components to Video_Codec_SDK_8.1.24 - Lots of other improvements and fixes in the capture/playback engine. Winjay S.r.l. Via Enrico Dandolo, 73 - 76123 ANDRIA (BT) – VAT ID: IT-05652830729 Infoline / Fax: 0883-55.34.10 / http://www.winjay.it - [email protected] - Version 2.3.6 - 1.7.12.9930 – 03/12/2018 - Added QuickSync H.264 video encoding and multichannel audio support (up to 16 channels) for WebRTC - Improved playback of RTSP streams. - Core FFmpeg components updated to release 3.4.2 version - Updated NVIDIA components to Video_Codec_SDK_8.1.24 - Fixed correct frame order in UDP streams playback - Fixed audio/video synchronization issue after temporary loss of an input signal - Fixed RTSP/RTMP streams reconnect problem on network failure - Lots of other improvements and fixes in the capture/playback engine. -
Ffmpeg Command Android Studio
Ffmpeg command android studio Continue FFMpeg/FFprobe is designed for Android. Run the FFmpeg and FFprobe commands with ease in your Android project. About this project is a continuation of the FFmpeg Android Java fork by WritingMinds. This plug captures the CAN LINK EXECUTABLE ffmpeg: it has the issue of text movement on x86 devices along with some other bugfixes, new features and the latest FFmpeg builds. Bravobit FFmpeg-Android architecture works on the following architectures: armv7-neon armv8 x86 x86_64 FFmpeg assemblage FFmpeg in this project was built with the following libraries: x264 r2851 ba24899 libpng 1.6.0 21 free type2 2.8.1 libmp3lame 3.100 libvorbis 1.3.5 libvpx v1.6.1-1456-g7d1bf5d libopus 1.2.1 fontconfig 2.11.11.294 libass 0.14.0 fribidi 0.19.7 Expat 2.1.0 fdk-aac 0.1.6 Features Uses the newest FFmpeg release n4.0-39-gda39990 Uses the native capabilities of the processor on the ARM FFprobe architecture bundled in this library too included the Network Features Multithreading Use Start To Enable Dependency Dependencies 'implementation':nl.bravobit:android-ffmpeg:1.1.7' Check if FFmpeg is supported To check Whether FFmpeg is available on your device you can use the following method. if (FFmpeg.getInstance (this) you will run the FFmpeg command In this code example we will run the ffmpeg version team. FFmpeg ffmpeg - FFmpeg.getInstance (context); to run the ffmpeg-version command you just need to go through the version of ffmpeg.execute (cmd, the new ExecuteBinaryResponseHandler () - @Override public void onStart () @Override public void on Progress (String message) @Override public void on The Mail (String message) @Override public emptiness onSuccess (String message) @Override public emptiness onFinish () Stop (or leave) FFmp to stop the FFmpeg process running, just call .send'ytSignal () at FFtask, which works: FFmpeg ffmpeg and FFmpeg.getInstance (context); FFtask ffTask - ffmpeg.execute (.. -
High Efficiency, Moderate Complexity Video Codec Using Only RF IPR
Thor High Efficiency, Moderate Complexity Video Codec using only RF IPR draft-fuldseth-netvc-thor-00 Arild Fuldseth, Gisle Bjontegaard (Cisco) IETF 93 – Prague, CZ – July 2015 1 Design principles • Moderate complexity to allow real-time implementation in SW on common HW, as well as new HW designs • Basic building blocks from well-known hybrid approach (motion compensated prediction and transform coding) • Common design elements in modern codecs – Larger block sizes and transforms, up to 64x64 – Quarter pixel interpolation, motion vector prediction, etc. • Cisco RF IPR (note well: declaration filed on draft) – Deblocking, transforms, etc. (some also essential in H.265/4) • Avoid non-RF IPR – If/when others offer RF IPR, design/performance will improve 2 Encoder Architecture Input Transform Quantizer Entropy Output video Coding bitstream - Inverse Transform Intra Frame Prediction Loop filters Inter Frame Prediction Reconstructed Motion Frame Estimation Memory 3 Decoder Architecture Input Entropy Inverse Bitstream Decoding Transform Intra Frame Prediction Loop filters Inter Frame Prediction Output video Reconstructed Frame Memory 4 Block Structure • Super block (SB) 64x64 • Quad-tree split into coding blocks (CB) >= 8x8 • Multiple prediction blocks (PB) per CB • Intra: 1 PB per CB • Inter: 1, 2 (rectangular) or 4 (square) PBs per CB • 1 or 4 transform blocks (TB) per CB 5 Coding-block modes • Intra • Inter0 MV index, no residual information • Inter1 MV index, residual information • Inter2 Explicit motion vector information, residual information -
Hardware for Speech and Audio Coding
Linköping Studies in Science and Technology Thesis No. 1093 Hardware for Speech and Audio Coding Mikael Olausson LiU-TEK-LIC-2004:22 Department of Electrical Engineering Linköpings universitet, SE-581 83 Linköping, Sweden Linköping 2004 Linköping Studies in Science and Technology Thesis No. 1093 Hardware for Speech and Audio Coding Mikael Olausson LiU-TEK-LIC-2004:22 Department of Electrical Engineering Linköpings universitet, SE-581 83 Linköping, Sweden Linköping 2004 ISBN 91-7373-953-7 ISSN 0280-7971 ii Abstract While the Micro Processors (MPUs) as a general purpose CPU are converging (into Intel Pentium), the DSP processors are diverging. In 1995, approximately 50% of the DSP processors on the market were general purpose processors, but last year only 15% were general purpose DSP processors on the market. The reason general purpose DSP processors fall short to the application specific DSP processors is that most users want to achieve highest performance under mini- mized power consumption and minimized silicon costs. Therefore, a DSP proces- sor must be an Application Specific Instruction set Processor (ASIP) for a group of domain specific applications. An essential feature of the ASIP is its functional acceleration on instruction level, which gives the specific instruction set architecture for a group of appli- cations. Hardware acceleration for digital signal processing in DSP processors is essential to enhance the performance while keeping enough flexibility. In the last 20 years, researchers and DSP semiconductor companies have been working on different kinds of accelerations for digital signal processing. The trade-off be- tween the performance and the flexibility is always an interesting question because all DSP algorithms are "application specific"; the acceleration for audio may not be suitable for the acceleration of baseband signal processing. -
On Engagement with ICT Standards and Their Implementations in Open Source Software Projects: Experiences and Insights from the Multimedia Field
International Journal of Standardization Research Volume 19 • Issue 1 On Engagement With ICT Standards and Their Implementations in Open Source Software Projects: Experiences and Insights From the Multimedia Field Jonas Gamalielsson, University of Skövde, Sweden Björn Lundell, University of Skövde, Sweden ABSTRACT The overarching goal in this paper is to investigate organisational engagement with an ICT standard and open source software (OSS) projects that implement the standard, with a specific focus on the multimedia field, which is relevant in light of the wide deployment of standards and different legal challenges in this field. The first part reports on experiences and insights from engagement with standards in the multimedia field and from implementation of such standards in OSS projects. The second part focuses on the case of the ITU-T H.264 standard and the two OSS projects OpenH264 and x264 that implement the standard, and reports on a characterisation of organisations that engage with and control the H.264 standard, and organisations that engage with and control OSS projects implementing the H.264 standard. Further, projects for standardisation and implementation of H.264 are contrasted with respect to mix of contributing organisations, and findings are related to organisational strategies of contributing organisations and previous research. KEywordS AVC, H.264, Involvement, ISO, ITU-T, OpenH264, Participation, x264 1 INTROdUCTION There are a number of different challenges related to provision of standards in the software sector, that can impact on the extent to which it is possible to faithfully implement the specification of a standard in software systems (Blind and Böhm, 2019; Gamalielsson and Lundell, 2013; Lundell et al., 2019; UK, 2015). -
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. -
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter Prediction using Binary classification techniques A graduate project submitted in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering by Alex Kit Romero May 2020 The graduate project of Alex Kit Romero is approved: ____________________________________ ____________ Dr. Katya Mkrtchyan Date ____________________________________ ____________ Dr. Kyle Dewey Date ____________________________________ ____________ Dr. John J. Noga, Chair Date California State University, Northridge ii Dedication This project is dedicated to all of the Computer Science professors that I have come in contact with other the years who have inspired and encouraged me to pursue a career in computer science. The words and wisdom of these professors are what pushed me to try harder and accomplish more than I ever thought possible. I would like to give a big thanks to the open source community and my fellow cohort of computer science co-workers for always being there with answers to my numerous questions and inquiries. Without their guidance and expertise, I could not have been successful. Lastly, I would like to thank my friends and family who have supported and uplifted me throughout the years. Thank you for believing in me and always telling me to never give up. iii Table of Contents Signature Page ................................................................................................................................ ii Dedication ..................................................................................................................................... -
Arxiv:2002.01657V1 [Eess.IV] 5 Feb 2020 Port Lossless Model to Compress Images Lossless
LEARNED LOSSLESS IMAGE COMPRESSION WITH A HYPERPRIOR AND DISCRETIZED GAUSSIAN MIXTURE LIKELIHOODS Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto Department of Computer Science and Communications Engineering, Waseda University, Tokyo, Japan. ABSTRACT effectively in [12, 13, 14]. Some methods decorrelate each Lossless image compression is an important task in the field channel of latent codes and apply deep residual learning to of multimedia communication. Traditional image codecs improve the performance as [15, 16, 17]. However, deep typically support lossless mode, such as WebP, JPEG2000, learning based lossless compression has rarely discussed. FLIF. Recently, deep learning based approaches have started One related work is L3C [18] to propose a hierarchical archi- to show the potential at this point. HyperPrior is an effective tecture with 3 scales to compress images lossless. technique proposed for lossy image compression. This paper In this paper, we propose a learned lossless image com- generalizes the hyperprior from lossy model to lossless com- pression using a hyperprior and discretized Gaussian mixture pression, and proposes a L2-norm term into the loss function likelihoods. Our contributions mainly consist of two aspects. to speed up training procedure. Besides, this paper also in- First, we generalize the hyperprior from lossy model to loss- vestigated different parameterized models for latent codes, less compression model, and propose a loss function with L2- and propose to use Gaussian mixture likelihoods to achieve norm for lossless compression to speed up training. Second, adaptive and flexible context models. Experimental results we investigate four parameterized distributions and propose validate our method can outperform existing deep learning to use Gaussian mixture likelihoods for the context model. -
Ffmpeg Codecs Documentation Table of Contents
FFmpeg Codecs Documentation Table of Contents 1 Description 2 Codec Options 3 Decoders 4 Video Decoders 4.1 hevc 4.2 rawvideo 4.2.1 Options 5 Audio Decoders 5.1 ac3 5.1.1 AC-3 Decoder Options 5.2 flac 5.2.1 FLAC Decoder options 5.3 ffwavesynth 5.4 libcelt 5.5 libgsm 5.6 libilbc 5.6.1 Options 5.7 libopencore-amrnb 5.8 libopencore-amrwb 5.9 libopus 6 Subtitles Decoders 6.1 dvbsub 6.1.1 Options 6.2 dvdsub 6.2.1 Options 6.3 libzvbi-teletext 6.3.1 Options 7 Encoders 8 Audio Encoders 8.1 aac 8.1.1 Options 8.2 ac3 and ac3_fixed 8.2.1 AC-3 Metadata 8.2.1.1 Metadata Control Options 8.2.1.2 Downmix Levels 8.2.1.3 Audio Production Information 8.2.1.4 Other Metadata Options 8.2.2 Extended Bitstream Information 8.2.2.1 Extended Bitstream Information - Part 1 8.2.2.2 Extended Bitstream Information - Part 2 8.2.3 Other AC-3 Encoding Options 8.2.4 Floating-Point-Only AC-3 Encoding Options 8.3 flac 8.3.1 Options 8.4 opus 8.4.1 Options 8.5 libfdk_aac 8.5.1 Options 8.5.2 Examples 8.6 libmp3lame 8.6.1 Options 8.7 libopencore-amrnb 8.7.1 Options 8.8 libopus 8.8.1 Option Mapping 8.9 libshine 8.9.1 Options 8.10 libtwolame 8.10.1 Options 8.11 libvo-amrwbenc 8.11.1 Options 8.12 libvorbis 8.12.1 Options 8.13 libwavpack 8.13.1 Options 8.14 mjpeg 8.14.1 Options 8.15 wavpack 8.15.1 Options 8.15.1.1 Shared options 8.15.1.2 Private options 9 Video Encoders 9.1 Hap 9.1.1 Options 9.2 jpeg2000 9.2.1 Options 9.3 libkvazaar 9.3.1 Options 9.4 libopenh264 9.4.1 Options 9.5 libtheora 9.5.1 Options 9.5.2 Examples 9.6 libvpx 9.6.1 Options 9.7 libwebp 9.7.1 Pixel Format 9.7.2 Options 9.8 libx264, libx264rgb 9.8.1 Supported Pixel Formats 9.8.2 Options 9.9 libx265 9.9.1 Options 9.10 libxvid 9.10.1 Options 9.11 mpeg2 9.11.1 Options 9.12 png 9.12.1 Private options 9.13 ProRes 9.13.1 Private Options for prores-ks 9.13.2 Speed considerations 9.14 QSV encoders 9.15 snow 9.15.1 Options 9.16 vc2 9.16.1 Options 10 Subtitles Encoders 10.1 dvdsub 10.1.1 Options 11 See Also 12 Authors 1 Description# TOC This document describes the codecs (decoders and encoders) provided by the libavcodec library. -
Course Outline & Schedule
Course Outline & Schedule Call US 408-759-5074 or UK +44 20 7620 0033 Open Media Encoding Techniques Course Code PWL396 Duration 3 Day Course Price $2,815 Course Description Video, TV and Image technology today dominates Internet Services. Whether it be for live TV, Streamed movies or video clips within social media video images are everywhere. The long-term efficiency of services depends upon the methods and mechanisms used to encode these services. We have relied upon the developments from the Digital Video Broadcast industry, ISO, MPEG and the ITU to provide us with standard ways to achieve this. However the patent royalty cost is now considered to be holding back this efficient development. All commercial users of the normal encoding used such as H.264, H.265, HEVC and other standardised codecs are required to pay royalties for using this technology through a firm of US patent Lawyers known as MPEG-LA. Each new ITU- T standard encoding requires new and increased payments. The Alliance for Open Media is founded by leading Internet companies focused on developing next-generation media formats, codecs and technologies in the public interest. The new Alliance is committing its collective technology and expertise to meet growing Internet demand for top-quality video, audio, imagery and streaming across devices of all kinds and for users worldwide. The aim is to develop royalty free standardized encoding based upon the technology contributed by its members. This course provides a technical study of Video Coding and the technologies which the developing Open Media implementations are based upon. -
Globalmeet Collaboration Deployment Guide
1. Deployment Guide GlobalMeet® Collaboration December 2020 Table of Contents Introduction 3 Contents of this guide 3 Intended audience 3 Version information 3 What’s new in this guide 4 About GlobalMeet Collaboration 5 Meeting features 5 Restricting meeting features 6 Desktop apps 6 Mobile apps 7 GlobalMeet for Outlook 8 File library 8 Storage 8 Supported file formats 8 Video file formats and codecs 9 Integrations 9 Google and Outlook calendars 9 GlobalMeet for Microsoft Teams 10 Language support 10 GlobalMeet meeting room, desktop and mobile apps 10 GlobalMeet for Outlook 10 Administrative portals 10 Branding and customization 11 Logo specs 11 Upload custom logos 12 System requirements 13 Web 13 GlobalMeet desktop apps 13 GlobalMeet mobile apps 14 GlobalMeet for Outlook 15 Network considerations 16 Network traffic 16 Note about network quality 16 Ports and protocols 17 Browser and proxy considerations 17 December 2020 GlobalMeet® Collaboration Deployment Guide | 1 Table of Contents Firewall transversal 17 Required domains 18 GlobalMeet Outlook add-in 18 Bandwidth considerations 19 Bandwidth estimating notes 20 GlobalMeet VRC implementation considerations 21 IP whitelisting (all systems) 21 Supported endpoints 21 H.323 and SIP firewall ports 22 Bandwidth considerations 22 Single sign-on (SAML) 23 Overview of the setup process 23 Required information 24 GlobalMeet login details 24 Data required by GlobalMeet 24 Application installers 25 GlobalMeet desktop apps 25 GlobalMeet mobile apps 25 GlobalMeet browser plugin 25 GlobalMeet for Outlook -
Video Compression Optimized for Racing Drones
Video compression optimized for racing drones Henrik Theolin Computer Science and Engineering, master's level 2018 Luleå University of Technology Department of Computer Science, Electrical and Space Engineering Video compression optimized for racing drones November 10, 2018 Preface To my wife and son always! Without you I'd never try to become smarter. Thanks to my supervisor Staffan Johansson at Neava for providing room, tools and the guidance needed to perform this thesis. To my examiner Rickard Nilsson for helping me focus on the task and reminding me of the time-limit to complete the report. i of ii Video compression optimized for racing drones November 10, 2018 Abstract This thesis is a report on the findings of different video coding tech- niques and their suitability for a low powered lightweight system mounted on a racing drone. Low latency, high consistency and a robust video stream is of the utmost importance. The literature consists of multiple comparisons and reports on the efficiency for the most commonly used video compression algorithms. These reports and findings are mainly not used on a low latency system but are testing in a laboratory environment with settings unusable for a real-time system. The literature that deals with low latency video streaming and network instability shows that only a limited set of each compression algorithms are available to ensure low complexity and no added delay to the coding process. The findings re- sulted in that AVC/H.264 was the most suited compression algorithm and more precise the x264 implementation was the most optimized to be able to perform well on the low powered system.