SDK Developer Reference API Version 1.27 LEGAL DISCLAIMER INFORMATION in THIS DOCUMENT IS PROVIDED in CONNECTION with INTEL PRODUCTS
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Enabling Hardware Accelerated Video Decode on Intel® Atom™ Processor D2000 and N2000 Series Under Fedora 16
Enabling Hardware Accelerated Video Decode on Intel® Atom™ Processor D2000 and N2000 Series under Fedora 16 Application Note October 2012 Order Number: 509577-003US INFORMATIONLegal Lines and Disclaimers IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL'S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. A “Mission Critical Application” is any application in which failure of the Intel Product could result, directly or indirectly, in personal injury or death. SHOULD YOU PURCHASE OR USE INTEL'S PRODUCTS FOR ANY SUCH MISSION CRITICAL APPLICATION, YOU SHALL INDEMNIFY AND HOLD INTEL AND ITS SUBSIDIARIES, SUBCONTRACTORS AND AFFILIATES, AND THE DIRECTORS, OFFICERS, AND EMPLOYEES OF EACH, HARMLESS AGAINST ALL CLAIMS COSTS, DAMAGES, AND EXPENSES AND REASONABLE ATTORNEYS' FEES ARISING OUT OF, DIRECTLY OR INDIRECTLY, ANY CLAIM OF PRODUCT LIABILITY, PERSONAL INJURY, OR DEATH ARISING IN ANY WAY OUT OF SUCH MISSION CRITICAL APPLICATION, WHETHER OR NOT INTEL OR ITS SUBCONTRACTOR WAS NEGLIGENT IN THE DESIGN, MANUFACTURE, OR WARNING OF THE INTEL PRODUCT OR ANY OF ITS PARTS. Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions marked “reserved” or “undefined”. -
ROS Robotics by Example Second Edition
ROS Robotics By Example Second Edition Learning to control wheeled, limbed, and flying robots using ROS Kinetic Kame Carol Fairchild Dr. Thomas L. Harman BIRMINGHAM - MUMBAI ROS Robotics By Example Second Edition Copyright © 2017 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. First published: June 2016 Second edition: November 2017 Production reference: 1301117 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK. ISBN 978-1-78847-959-2 www.packtpub.com Credits Authors Copy Editor Carol Fairchild Safis Editing Dr. Thomas L. Harman Proofreader Reviewer Safis Editing Lentin Joseph Indexer Acquisition Editor Aishwarya Gangawane Frank Pohlmann Graphics Project Editor Kirk D'Penha Alish Firasta Production Coordinator Content Development Editor Nilesh Mohite Venugopal Commuri Technical Editor Bhagyashree Rai About the Authors Carol Fairchild is the owner and principal engineer of Fairchild Robotics, a robotics development and integration company. -
Release Notes for Debian 11 (Bullseye), 64-Bit PC
Release Notes for Debian 11 (bullseye), 64-bit PC The Debian Documentation Project (https://www.debian.org/doc/) October 1, 2021 Release Notes for Debian 11 (bullseye), 64-bit PC This document is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License, version 2, as published by the Free Software Foundation. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. The license text can also be found at https://www.gnu.org/licenses/gpl-2.0.html and /usr/ share/common-licenses/GPL-2 on Debian systems. ii Contents 1 Introduction 1 1.1 Reporting bugs on this document . 1 1.2 Contributing upgrade reports . 1 1.3 Sources for this document . 2 2 What’s new in Debian 11 3 2.1 Supported architectures . 3 2.2 What’s new in the distribution? . 3 2.2.1 Desktops and well known packages . 3 2.2.2 Driverless scanning and printing . 4 2.2.2.1 CUPS and driverless printing . 4 2.2.2.2 SANE and driverless scanning . 4 2.2.3 New generic open command . 5 2.2.4 Control groups v2 . 5 2.2.5 Persistent systemd journal . -
Video Denoising, Deblocking and Enhancement Through Separable
1 Video Denoising, Deblocking and Enhancement Through Separable 4-D Nonlocal Spatiotemporal Transforms Matteo Maggioni, Giacomo Boracchi, Alessandro Foi, Karen Egiazarian Abstract—We propose a powerful video filtering algorithm that the nonlocal similarity between patches at different locations exploits temporal and spatial redundancy characterizing natural within the data [5], [6]. Algorithms based on this approach video sequences. The algorithm implements the paradigm of have been proposed for various signal-processing problems, nonlocal grouping and collaborative filtering, where a higher- dimensional transform-domain representation of the observations and mainly for image denoising [4], [6], [7], [8], [9], [10], [11], is leveraged to enforce sparsity and thus regularize the data: [12], [13], [14], [15]. Specifically, in [7] has been introduced 3-D spatiotemporal volumes are constructed by tracking blocks an adaptive pointwise image filtering strategy, called non- along trajectories defined by the motion vectors. Mutually similar local means, where the estimate of each pixel xi is obtained volumes are then grouped together by stacking them along an as a weighted average of, in principle, all the pixels x of additional fourth dimension, thus producing a 4-D structure, j termed group, where different types of data correlation exist the noisy image, using a family of weights proportional to along the different dimensions: local correlation along the two the similarity between two neighborhoods centered at xi and dimensions of the blocks, temporal correlation along the motion xj. So far, the most effective image-denoising algorithm is trajectories, and nonlocal spatial correlation (i.e. self-similarity) BM3D [10], [6], which relies on the so-called grouping and along the fourth dimension of the group. -
ICIP 2007 Session Index
ICIP 2007 Session Index Monday Morning MA-L1: Video Coding for Next Generation Displays MA-L2: Image And Video Segmentation I MA-L3: Video Coding I MA-L4: Image and Video Restoration MA-L5: Biometrics I MA-L6: Image and Video Storage and Retrieval I MA-P1: Stereoscopic and 3D Processing I: Coding and Processing MA-P2: Active-Contour, Level-Set, and Cluster-Based Segmentation Methods MA-P3: Image and Video Denoising MA-P4: Biometrics II: Human Activity, Gait, Gaze Analysis MA-P5: Security I: Authentication and Steganography MA-P6: Image and Video Multiresolution Processing MA-P7: Motion Detection and Estimation I MA-P8: Image and Video Enhancement Monday Afternoon MP-L1: Distributed Source Coding I: Low Complexity Video Coding MP-L2: Image And Video Segmentation II: Texture Segmentation MP-L3: Interpolation and Superresolution I MP-L4: Image and Video Modeling I MP-L5: Security II MP-L6: Image Scanning, Display, Printing, Color and Multispectral Processing I MP-P1: Image and Video Storage and Retrieval II MP-P2: Morphological, Level-Set, and Edge or Color Image/Video Segmentation MP-P3: Scalable Video Coding MP-P4: Image Coding I MP-P5: Biometrics III: Fingerprints, Iris, Palmprints MP-P6: Biomedical Imaging I MP-P7: Motion Detection and Estimation II MP-P8: Stereoscopic and 3D Processing II: 3D Modeling & Synthesis Tuesday Morning TA-L1: Distributed Source Coding II: Distributed Image and Video Coding and Their Applications TA-L2: Image and Video Segmentation III: Edge or Color Segmentation TA-L3: Stereoscopic and 3D Processing III TA-L4: -
(12) United States Patent (10) Patent No.: US 8,654,842 B2 Ganesh Et Al
USOO8654842B2 (12) United States Patent (10) Patent No.: US 8,654,842 B2 Ganesh et al. (45) Date of Patent: Feb. 18, 2014 (54) ACCELERATED VIDEO ENCODING 6,044,408 A 3/2000 Engstrom et al. 6,101,276 A 8, 2000 Adiletta et al. 6,128,026 A 10/2000 Brothers, III (75) Inventors: SNESN RWSRS 6,252,905 B1 6/2001 Pokrinchak et al. onald J. Yunsil, Kirkland, (US); 6,434,196 B1* 8/2002 Sethuraman et al. ... 375/240. 12 Gary J. Sullivan, Redmond, WA (US); 6,721,359 B1 4/2004 Bist et al. Glenn F. Evans, Kirkland, WA (US); (Continued) Shyam Sadhwani, Bellevue, WA (US); Stephen J. Estrop, Carnation, WA (US) FOREIGN PATENT DOCUMENTS (73) Assignee: Microsoft Corporation, Redmond, WA EP 1347,650 9, 2003 (US) WO WOO2O7446 A2 1, 2001 WO WOO219095 3, 2002 (*) Notice: Subject to any disclaimer, the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 U.S.C. 154(b) by 1651 days. Rossi, “Multicore Signal Processing Platform with Heterogeneous Configurable Hardware Accelerators', 2013, IEEE, p. 1-14.* (21) Appl. No.: 11/673,423 (Continued) (22) Filed: Feb. 9, 2007 Primary Examiner — Taghi Arani (65) Prior Publication Data Assistant Examiner — Gregory Lane (74) Attorney, Agent, or Firm — Carole A Boelitz: Raghu US 2007/O2O1562 A1 Aug. 30, 2007 Chinagudabha; Micky Minhas Related U.S. Application Data (57) ABSTRACT (63) Continuation-in-part of application No. 1 1/276,336, A video encoding acceleration service to increase one or filed on Feb. 24, 2006. more of the speed and quality of video encoding is described. -
Universidad Politécnica De Valencia
Universidad Polit´ecnica de Valencia Departamento de Comunicaciones Tesis Doctoral T´ecnicasdean´alisis de secuencias de v´ıdeo. Aplicaci´on a la restauraci´on de pel´ıculas antiguas Presentada por: Valery Naranjo Ornedo Dirigida por: Dr. Antonio Albiol Colomer Valencia, 2002. ALuisyaFran “La mera formulaci´on de un problema suele ser m´as esencial que su soluci´on, la cual puede ser una simple cuesti´on de habilidad matem´atica o experimental. Plantear nuevas preguntas, nuevas posibilidades, contemplar viejos problemas des- de un nuevoangulo, ´ exige imaginaci´on creativa y marca adelantos reales en la ciencia.” Albert Einstein Agradecimientos Es muy dif´ıcil mostrar mi agradecimiento, con unas simples palabras, a todas aquellas personas que han hecho que haya llegado hasta aqu´ı, a´un as´ı, no quer´ıa dejar pasar la opor- tunidad de intentarlo. En primer lugar quiero mostrar mi agradecimiento a Antonio Albiol, que ha sido no s´olo mi director de tesis, sino tambi´en mi amigo, y mi maestro en todo lo que s´e de procesado de se˜nal. A mi familia y amigos por estar ah´ı siempre que los necesito, sin esperar nada a cambio, y sobre todo, por tener fe en m´ı. A Luis, mi marido, que siempre me apoya y me ayuda en todo, y hace que todos los esfuerzos tengan sentido. Amiscompa˜neros del Departamento de Comunicaciones que me han echado una mano en esta empresa: a Jos´e Manuel, por su paciencia, sus consejos y su ayuda desinteresada e inestimable; a Luis Vergara por tantas dudas de tratamiento de se˜nal resueltas, a Mar´ıa y Angel´ por sus observaciones y revisiones, a Paco y Pablo por sus consejos ling¨u´ısticos, y a Juan Carlos por sus consejos burocr´aticos. -
PC Hardware Contents
PC Hardware Contents 1 Computer hardware 1 1.1 Von Neumann architecture ...................................... 1 1.2 Sales .................................................. 1 1.3 Different systems ........................................... 2 1.3.1 Personal computer ...................................... 2 1.3.2 Mainframe computer ..................................... 3 1.3.3 Departmental computing ................................... 4 1.3.4 Supercomputer ........................................ 4 1.4 See also ................................................ 4 1.5 References ............................................... 4 1.6 External links ............................................. 4 2 Central processing unit 5 2.1 History ................................................. 5 2.1.1 Transistor and integrated circuit CPUs ............................ 6 2.1.2 Microprocessors ....................................... 7 2.2 Operation ............................................... 8 2.2.1 Fetch ............................................. 8 2.2.2 Decode ............................................ 8 2.2.3 Execute ............................................ 9 2.3 Design and implementation ...................................... 9 2.3.1 Control unit .......................................... 9 2.3.2 Arithmetic logic unit ..................................... 9 2.3.3 Integer range ......................................... 10 2.3.4 Clock rate ........................................... 10 2.3.5 Parallelism ......................................... -
HAIHAO XIANG ([email protected]) Hardware Acceleration Path Based on VA-API in Gstreamer
gfxmfx, gfxmsdk and MediaSDK Update HAIHAO XIANG ([email protected]) Hardware acceleration path based on VA-API in gstreamer Media Application based on Gstreamer GstMfx GstMsdk GstVaapi MediaMSDK Legend Non MSDK path Libva (vaapi) MSDK path iHD i965 Other vaapi back-end drivers MSDK & Non MSDK Intel Gen Graphics Other HWs VAAPI VAAPI (Video Acceleration API): API specific for hardware accelerated video decoding, encoding and processing. ◦ 10+ years, libva is the implementation (https://github.com/intel/libva) ◦ Back-end drivers for Intel Gen graphics: i965, iHD ◦ I965 (https://github.com/intel/intel-vaapi-driver/) supports legacy platforms only. ◦ iHD (https://github.com/intel/media-driver) was open sourced in 2017 and supports the new Intel platforms. It provides more features than i965, especially in VPP and video encoding. MSDK MediaSDK: Provides APIs to access hardware accelerated video decode, encode and filtering on Intel platform ◦ Open sourced in 2017 (https://github.com/Intel-Media- SDK/MediaSDK) ◦ On Linux, it is based on libva (VAAPI) ◦ Work well with iHD only GstMfx vs GstMsdk ◦ Two gstreamer plugins based on MediaSDK ◦ GstMfx is located at https://github.com/intel/gstreamer-media-SDK however GstMsdk is a plugin in gst- plugins-bad ◦ Different Licenses ◦ GstMfx: LGPL 2.1+ ◦ GstMsdk: BSD3 ◦ GstMfx and GstMsdk provide similar features, and the performance of GstMsdk is a little better than GstMfx for most cases. ◦ We will add more features, such as HEVC Main10, Main12 etc, fix the performance gaps for those failure cases in GstMsdk. GstMfx vs GstMsdk gstmfx gstmsdk H264/AVC decoder/encoder decoder/encoder H265/HEVC decoder/encoder decoder/encoder VP8 decoder decoder/encoder VP9 decoder decoder JPEG decoder/encoder decoder/encoder MPEG-2 decoder decoder/encoder VC-1 decoder decoder VPP Yes Yes Sink Yes N (*) (*): gstmsdk works well with glimagesink although gstmsdk doesn’t provide sink element. -
MSDK Driver Download BIOSLINUXMCSDK
MSDK Driver Download BIOSLINUXMCSDK. SYS/BIOS and Linux Multicore Software Development Kits (MCSDK) for C66x, C647x, C645x Processors. BIOSLINUXMCSDK. Overview. NOTE: K2x, C665x and C667x devices are now actively maintained on the Processor-SDK release stream. See links above. Our Multicore Software Development Kits (MCSDK) provide highly-optimized bundles of foundational, platform-specific drivers to enable development on selected TI ARM and DSP devices. The MCSDK gives developers the ability to evaluate hardware and software capabilities of the evaluation platform and to rapidly develop applications. The MCSDK enables applications to use SYS/BIOS and/or Linux on one platform. Individual cores can be assigned to operate Linux applications as a control plane while other cores are simultaneously assigned high-performance signal processing operations. This heterogeneous configuration provides flexibility for software developers to implement full solutions on TI’s multicore devices including DSP and ARM processors. Features. MCSDK Provides foundational software for ARM+DSP devices. It encapsulates a collection of software elements and tools intended to enable customer application development. The foundational components include: SYS/BIOS real-time embedded operating system on DSP cores Linux high-level operating system running on ARM (SMP mode for multicore ARM) DSP chip support libraries, DSP/ARM drivers, and basic platform utilities Interprocessor communication for communication across cores and devices SoC resource management Optimized application-specific (small cell, transport) and application non-specific algorithm libraries Trace debug and instrumentation Bootloaders and boot utilities, power-on self test Demonstrations and examples ARM software libraries available in Linux devkit or via Arago/Yocto Latest toolchain (ARM Linaro, DSP TI CodeGen) Host tools, integrated development environment. -
Baselight Software Flexibility, Power and Throughput
Baselight software Flexibility, power and throughput The world’s most powerful colour grading and finishing system for film, TV, commercials and broadcast. Power and capacity Start grading sooner Baselight is available on a range of hardware platforms Baselight is straightforward to use. The UI and control to deliver the power required for intensive grading. The panels are logically laid out so you become productive unique Baselight architecture can deliver real-time 4K quickly. FilmLight also provides bespoke training options, performance and up to a massive 204TB of storage, while together with highly qualified and responsive 24-hour its comprehensive GPU renderer handles all operations product support via web, email and phone. natively for the most accurate and efficient throughput. This power enables Baselight to perform complex, multi- Creative options layered grading operations in real time while carrying With Baselight, workspaces can be defined and saved for out intensive tasks such as ingest and rendering in the different tasks, such as grading, conforming or just personal background. preference. Even the control surfaces can be customised to your preferred way of working using our Chalk application. Extensive control Baselight is a full-featured grading suite—it can handle high- Blackboard 2 takes colour grading to the next level with end commercials and beauty spots as well as problem context-sensitive controls, high-resolution displays and footage and stereo productions with ease. But as business programmable, adaptive keys. There’s also our Slate needs change and technology advances, the system can panel, which uses the same technological advances as be upgraded and extended. -
Video Enhancement Techniques Employed Over the Decade for Reliable Communication
International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-11, September 2019 Video Enhancement Techniques Employed Over the Decade for Reliable Communication Padma Reddy A.M, Udaya Rani.V, S.Raj Barath Abstract - Traditional networks are designed to Recently, several resolution methods have been meet the needs of streaming video on the Internet. launched and are very useful for collecting information. The Relatively high standards of broadband connections purpose of the study is to analyze high definition videos and and video broadband services make the best effort for vague videos. This study includes an optimization method certain specific video information and transmission for creating online video source services. The program methods to appear at any time to reduce network constraints. Video quality is directly related to the focuses on application optimization, facilitating the basic ability of the phone to send and receive data recording of video clips between endpoints. The purpose of from time to time for playback. Record videos from each system is to overcome the overall quality of the user your mobile phone are facing various challenges that by using the default values. Although there are some have been overcome by a variety of methods. In an interesting challenges for data transfer law, the law on extremely robust and unpredictable environment, networks and migration, this study is based on network- transversal hardware provides adequate video. based networks, not networks. Conventional networks are designed to meet the needs of streaming video over the Internet. Relatively high standards of broadband connections and video II.