OpenVX is a royalty-free, open standard API released by the Khronos group, that enables performance and power-optimized computer vision functionality, especially important in embedded and real-time use cases. OpenVX has the support of all the major processor vendors and will be appearing in various devices in the very near future.
The IEEE Signal Processing Society of Santa Clara Valley, is organizing a half day tutorial, open to everyone, so that computer vision application developers can become familiar with this exciting new API. The course will be taught by experts in OpenVX from Intel, AMD and NVIDIA. It covers both the function-based API and the graph API that enable OpenVX developers to efficiently run computer vision algorithms on heterogeneous computing architectures. A set of example algorithms from computational photography and advanced driver assistance will be discussed, and hands on practice sessions will be used to allow participants to get a solid understanding of OpenVX using real-world application scenarios. Also covered is the relationship between OpenVX and OpenCV, as well as OpenCL.
Kari Pulli, Intel
Kari Pulli is Sr. Principal Engineer at Intel. Earlier, he was VP of Computational Imaging at Light, Sr. Director of Research at NVIDIA, and Nokia Fellow at Nokia Research center, working on Mobile Visual Computing. Kari has a long background in standardization and at Khronos he has contributed to many mobile media standards including OpenVX. He is a frequent author and speaker at venues like CVPR and SIGGRAPH, with h-index of 27. Kari has a PhD from University of Washington, MBA from University of Oulu, and has taught and worked as a researcher at University of Oulu, Stanford University, and MIT.
Radhakrishna Giduthuri, AMD
Radhakrishna Giduthuri is a Design Engineer at Advanced Micro Devices (AMD) focusing on development of computer vision toolkit and libraries for heterogeneous compute platforms. He has extensive background with software design and performance tuning for various computer architectures ranging from General Purpose DSPs, Customizable DSPs, Media Processors, Heterogeneous Processors, GPUs, and several CPUs. He is a member of Khronos OpenVX working group representing AMD. In the past he was a member of SMPTE video compression standardizing committee for several years. He is also chair of IEEE Signal Processing Society Chapter of Santa Clara Valley.
Thierry Lepley, NVIDIA
Thierry Lepley is Senior Computer Vision Engineer at NVIDIA and the NVIDIA representative in the Khronos OpenVX standardization group. His focus is on the development of optimized computer vision toolkits and libraries for real-time embedded systems. Earlier, Thierry was Principal Engineer at STMicroelectronics, working on many-core acceleration for computer vision, where he developed a compiler that automates the parallelization of image processing pipelines and the management of image tiling.