Fast, portable, power-efficient vision processing across diverse hardware architectures; Full conformance test suite and Adopters Program immediately available; Khronos to ship open source OpenVX implementation by end of 2014
Source: Khronos Group
“Vivante is working with leading industry partners to deliver high performance, real time, intelligent vision processing solutions in mobile, automotive and smart security products through our OpenVX based GC7000 VX Series GPUs,” said Wei-Jin Dai, CEO and President of Vivante. “This innovative design enables SoC vendors to use the same processing core for embedded vision acceleration and photorealistic 3D rendering, while keeping power consumption within mobile levels. Through a dynamic VLIW vision instruction set and enhanced shader extensions to achieve single cycle API efficiency, this new GPU Vision approach will allow rapid adoption of vision applications on Vivante OpenVX platforms.”
October 20th, 2014, – The Khronos™ Group today announced the ratification and public release of the finalized OpenVX™ 1.0 specification, an open, royalty-free standard for cross platform acceleration of computer vision applications. OpenVX enables performance and power-optimized computer vision processing, especially important in embedded and real-time uses cases such as face, body and gesture tracking, smart video surveillance, advanced driver assistance systems (ADAS), object and scene reconstruction, augmented reality, visual inspection, robotics and more. In addition to the OpenVX specification, Khronos has developed a full set of conformance tests and an Adopters Program, that enables implementers to test their implementations and use the OpenVX trademark if conformant. Khronos plans to ship an open source, fully-conformant CPU-based implementation of OpenVX 1.0 before the end of 2014. The full OpenVX 1.0 specification and details about the OpenVX Adopters Program are available at www.khronos.org/openvx.
OpenVX defines a higher level of abstraction for execution and memory models than compute frameworks such as OpenCL™, enabling significant implementation innovation and efficient execution on a wide range of architectures while maintaining a consistent vision acceleration API for application portability. An OpenVX developer expresses a connected graph of vision nodes that an implementer can execute and optimize through a wide variety of techniques such as: acceleration on CPUs, GPUs, DSPs or dedicated hardware, compiler optimizations, node coalescing, and tiled execution to keep sections of processed images in local memories. This architectural agility enables OpenVX applications on a diversity of systems optimized for different levels of power and performance, including very battery-sensitive, vision-enabled, wearable displays.
“Increasingly powerful and efficient processors and image sensors are enabling engineers to incorporate visual intelligence into a wide range of systems and applications,” said Jeff Bier, founder of the Embedded Vision Alliance. “A key challenge for engineers is efficiently mapping complex algorithms onto the processor best suited to the application. OpenVX is an important step towards easing this challenge.”
The precisely defined specification and conformance tests for OpenVX make it ideal for deployment in production systems, where cross-vendor consistency and reliability are essential. OpenVX is complementary to the popular OpenCV open source vision library that is also used for application prototyping but is not so tightly defined and lacks OpenVX graph optimizations. Khronos has defined the VXU™ utility library to enable developers to call individual OpenVX nodes as standalone functions for efficient code migration from traditional vision libraries such as OpenCV. Finally, as any Khronos specification, OpenVX is extensible to enable nodes to be defined and deployed to meet customer needs, ahead of being integrated into the core specification.
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