Mozilla announced a new development program for Mixed Reality that will expand its work in Virtual Reality (VR) and Augmented Reality (AR) for the web. There is a draft WebXR API proposal, which uses WebGL, for providing access to both augmented and virtual reality devices.
On September 14th The Khronos Group held an online overview webinar on OpenVX 1.2. If you missed the webinar or wish to watch it again, the video and slides are now online. Be sure to register for the next Khronos Webinar "Mastering the Khronos Blender glTF 2.0 Exporter" on October 24th.
The Khronos Group is holding another Webinar on September 14th at 9:30AM PT. Engineers and managers interested in developing neural network inference engines and portable application that need portability across platforms and hardware should join in this free webinar. Speaking will be Radhakrishna (Radha) Giduthuri, a software architect at Advanced Micro Devices (AMD), Tomer Schwartz from Intel and Frank Brill, OpenVX Working Group Chair.
CVPR is soliciting proposals for workshops to be held together with the 2018 Computer Vision and Pattern Recognition Conference (CVPR 2018). The workshops will take place on June 18 and June 22 at the same venue as the main conference. Deadline is October 20th 2017. CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
The landscape of APIs for accelerating vision and neural network software using specialized processors continues to rapidly evolve. Many industry-standard APIs, such as OpenCL and OpenVX, are being upgraded to increasingly focus on deep learning, and the industry is rapidly adopting the new generation of low-level, explicit GPU APIs, such as Vulkan, that tightly integrate graphics and compute. Neil Trevett presented the "Vision Acceleration API Landscape: Options and Trade-offs" tutorial at the May 2017 Embedded Vision Summit.
The Khronos Group held their annual BOF-Blitz at SIGGRAPH today. There were five BOFs in all, and they were all a huge success. If you were not able to get to SIGGRAPH and you missed the live stream, you can now watch the video online here.
Synopsys announced that it has enhanced the convolutional neural network (CNN) engine in its DesignWare EV6x Vision Processors to address the increasing video resolution and frame rate requirements of high-performance embedded vision applications. To simplify software application development, the EV6x processors are supported by a comprehensive suite of tools and software. Combined with software development tools based on OpenVX, OpenCV and OpenCL C embedded vision standards, the MetaWare EV Development Toolkit offers a full suite of tools needed to accelerate embedded software development.
Frank Brill, Design Engineering Director at Cadence and Chairperson of the Khronos Group's OpenVX Working Group, presents the "OpenVX Computer Vision Library Standard for Portable, Efficient Code" tutorial at the May 2017 Embedded Vision Summit.
Imagination Technologies announces the first GPU IP core based on its new PowerVR Furian architecture, the Series8XT GT8525. Says Tatiana Solokhina, CTO, RnD Center ELVEES, a Khronos member: “As a provider of SoCs for a wide range of global video analytics applications, we require a GPU that offers the best compute performance in a power constrained footprint. The new PowerVR Furian 8XT family from Imagination provides us an industry-leading GPU with new ALU for increased performance density and efficiency. In addition, support for standard compute APIs such as OpenVX enables easy implementation of real world vision processing applications.” Furian is designed to address the increasing compute requirements across multiple applications and market segments with efficient use of compute APIs including OpenCL 2.0, Vulkan 1.0 and OpenVX 1.1.
VeriSilicon Holdings Co., Ltd. announces VIP8000, a highly scalable and programmable processor for computer vision and artificial intelligence. It delivers over 3 Tera MACs per second, with power consumption more efficient than 1.5 GMAC/second/mW and the smallest silicon area in industry with 16FF process technology. The VIP8000 can directly import neural networks generated by popular deep learning frameworks, such as Caffe and TensorFlow and neural networks can be integrated to other computer vision functions using the OpenVX framework. The processor is programmed by OpenCL or OpenVX with a unified programming model across the hardware units, including customer application-specific hardware acceleration units. Learn more about the VIP8000.
This week at the Embedded Vision Summit (EVS) in California Imagination is showcasing their latest Convolutional Neural Network (CNN) object recognition demo. All of these networks have been implemented using Imagination’s own DNN library. IMG DNN sits on top of OpenCL but doesn’t obscure it, and makes use of OpenCL constructs so it can be used alongside other custom OpenCL code. Imagination’s Paul Brasnett is talking at EVS on the subject of ‘Training CNNs for Efficient Inference‘ and for further reading, take a look at this CNN based number recognition demo, which uses OpenVX with CNN extension. Learn more about Imagination's Convolutional Neural Networks.
The Intel Computer Vision SDK Beta is for developing and deploying vision-oriented solutions on platforms from Intel, including autonomous vehicles, digital surveillance cameras, robotics, and mixed-reality headsets. Based on OpenVX, this SDK offers many useful extensions and supports heterogeneous execution across CPU and SoC accelerators using an advanced graph compiler, optimized and developer-created kernels, and design and analysis tools. It also includes deep-learning tools that unleash inference performance on deep-learning deployment. If the functionality you need is not already available in the supplied library, you can create custom kernels using C, C++, or OpenCL kernels.
The Khronos Group announces the immediate release of the OpenVX 1.2 specification for cross-platform acceleration of computer vision applications and libraries. OpenVX is a high-level, graph-based API targeted at real-time mobile and embedded platforms. This open, cross-platform, royalty-free standard enables performance-portable, power-optimized computer vision applications such as face, body, and gesture tracking, smart video surveillance, autonomous driver assistance systems, visual inspection, and robotics. Core OpenVX 1.2 has significantly expanded functionality, including conditional execution, feature detection, and classification operations.
In December last year, Imagination announced we were the first to submit an OpenVX 1.1 conformant implementation. In this blog post, we will show how our work has developed since then on one of the first implementations of the Khronos OpenVX 1.1 API as well as the new and very first implementation of the Convolutional Neural Network (CNN) extension that goes along with it.