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The Future of Embedded Vision is Mobile! Join us at ARM’s Computer Vision Seminar, 11 May Santa Clara Convention Center

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The Embedded Vision Summit 2015 is nearly upon us.  This annual gathering of experts interested in this highly dynamic area is a day of fascinating presentations and demonstrates of leading-edge developments in vision-enabled products.  The Summit is on 12 May.

 

This year ARM® is hosting a special half-day seminar connected with the Summit on the day before.  Titled “Enabling Computer Vision on ARM” the event will see a number of industry-leading developers presenting their experiences in computer vision working over a variety of ARM platforms and use cases.

 

Growth in Computer Vision


Computer vision is seeing phenomenal growth in adoption and deployment.  The increased power, efficiency and variety of processors is enabling many new use cases while revolutionizing existing vision applications previously confined to the desktop.  These are now increasingly possible on energy efficient mobile devices and across market segments from automotive, retail, medical and industry.

 

In this seminar, a selection of computer vision experts and leaders in their fields will present their experiences working with ARM-based systems across a variety of real use cases.  Attendees will learn how to:

 

  • Resolve common issues encountered when implementing complex vision algorithms on embedded processors in areas such as object recognition and augmented reality
  • Balance workloads across processors and processor types
  • Debug heterogeneous vision applications on ARM-based systems to remove design bottlenecks and improve performance and efficiency

 

Seminar program:

 

  • Jeff Bier, President, BDTI
    Title: Benchmarking Metrics and Processor Selection for Computer Vision
    Abstract:
    This presentation looks at the long term trends in computer vision applications and processors and the challenges these pose to benchmarking vision applications.  As the complexity of applications, processors and the heterogeneous design of systems increases, so do the challenges in measuring their performance in meaningful ways.  Being able to assess the relative performance of processors and processor types under various combinations and configurations is a vital factor in matching systems to particular use cases.  For example, mobile use cases are becoming the a key focus for software development and these systems increasingly rely on heterogeneous configurations to increase processing efficiency.  To use these processors efficiently, developers must determine the optical mapping of their applications onto the SoC’s heterogeneous processing cores.


  • Dr. Masaki Satoh, Morpho Inc
    Title: Development of Image and Vision Processing Software and Optimizations for ARM
    Abstract:
    This presentation will give technical insight on the benefit of NEON Acceleration, including detailing actual performance improvement.  From the developer perspective, the presentation will examine specific algorithms and how they are optimized with NEON™.  The future of imaging will also be examined, looking at the potential of GPU compute and other heterogeneous combinations, deep learning image recognition engines accelerated through NEON and OpenCL, and research and development into automotive products.

  • Dr. Piotr Stec, Project Manager in the Imaging Field, FotoNation
    Title: Video Image Stabilization for Mobile Devices
    Abstract:
    The presentation will show the processing steps needed to perform video stabilization on mobile devices. We will show the algorithm flow indicating the steps that need to be taken to perform the algorithm and the data flow between various components of the algorithm. Some parts of the algorithm proven to be particularly challenging in terms of achieving suitable performance. Not always the most complex parts turned out to be the bottleneck. We will show how those difficulties were overcome on the device using ARM chipset and what gains were achieved in terms of processing time.  The last part of the presentation will be a live demonstration of the working algorithm.

  • Gian Marco Iodice, Compute Engineer, ARM
    Title: Real-time Dense Passive Stereo Vision: A Case Study in Optimizing Computer Vision Applications Using OpenCL on ARM
    Abstract: Passive stereo vision is a powerful visual sensing technique aimed at inferring depth without using any structured light. Nowadays, as it offers low cost and reliability solutions, it finds application in many real use cases, such as natural user interfaces, industrial automation, autonomous vehicles, and many more. Since stereo vision algorithms are extremely computationally expensive, resulting in very high CPU load, the aim of this presentation is to demonstrate the feasibility of this task on a low power mobile ARM Mali GPU. In particular, the presentation will focus on a local stereo vision method based on a novel extension of census transform, which exploits the highlyparallel execution feature of mobile Graphic Processing Units with OpenCL.  The presentation will show also the approaches and the strategies used to optimize the OpenCL code in order to reach significant performance benefits on the GPU.

  • Martin Lechner, CTO and Markus Eder, Head of Computer Vision, Wikitude
    Title: Utilizing NEON for Accelerated Computer Vision Processing in Augmented Reality Scenarios
    Abstract:
    In the core of the Wikitude SDK runs an engine that heavily relies on different computer vision algorithms to get information about the current environment of the user. As those algorithms can be very computationally intensive, a major part in our work is to optimize and specifically design the algorithms for the architecture on mobile devices.  As most of the current mobile phones have either armv7 or armv8 architectures the ARM NEON SIMD-instruction set provides a huge possibility for improving the performance of computer vision algorithms. This presentation will focus on how the NEON instruction set can be used to improve the performance of general image processing functions. It will also include a discussion of our experience with the NEON instruction set, specifically the process on how to find the hotspots in the code and how those functions can be tested and debugged as well as our experience with porting the NEON functionality from armv7 to armv8.

  • Tim Hartley, Technical Marketing Manager, ARM
    Title:Measuring the Whole System: Holistic Profiling of CPU and GPU for Optimal Vision Applications on ARM Platforms
    Abstract:
    Developers of sophisticated vision applications need all the processing power they can lay their hands on, and using OpenCL on a GPU can be a vital additional compute resource.  But spreading the workload amongst processors and processor types brings its own problems and difficulties, and traditional application optimization techniques are not always effective in this brave new heterogeneous world.  The key to achieving performance is twofold: getting access to hardware counters for all the processors in your system, and then understanding what those numbers are telling you.  In this talk, I will examine the tools and techniques available to profile these sorts of applications and will use real case studies from vision applications. Using tools like DS5 Streamline I will show how to extract meaningful performance numbers and how to interpret them.

  • Ken Lee, Founder and CEO, Van Gogh Imaging
    Title:Using ARM Processors to Implement Real-Time 3D Object Recognition on Mobile Devices
    Abstract:Diverse applications such as 3D printing, augmented reality, medical, parts inspections, and ecommerce can benefit significantly from the ability of 3D computer vision to separate a scene into discrete objects and then recognize and analyze them reliably. The 3D approach is much more robust and accurate than the traditional 2D approach and is now possible with embedded 3D sensors and powerful processors in mobile devices.  This discussion will focus on how real-time 3D computer vision can now be implemented in the ARM CPU.  Further, we will discuss how these algorithms can be further accelerated using ARM Mali GPU with OPENCL implementation.

 

 

The seminar will include an industry panel discussion. Experts from the worlds of vision IP, ADAS (Automatic Driver Assistance Systems), and image sensors and recognition software will discuss future trends in technology for ARM-based systems.

 

To register for free for the ARM Seminar:
http://www.eventbrite.com/e/seminar-enabling-computer-vision-on-arm-tickets-10231417445?aff=EVS

 

There’s more about the Embedded Vision Summit here:
http://www.embedded-vision.com/summit


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