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Dear Colleague,
I’m pleased to announce that we’ve launched an all-new Embedded Vision
Summit area of the Alliance website, highlighting the upcoming 2016
Summit. The Embedded Vision Summit, an educational forum for product
creators interested in incorporating visual intelligence into
electronic systems and software, will take place May 2-4, 2016 at the
Santa Clara (California) Convention Center. Now in its fourth year, the
Summit is expanding to a multi-day event, and opens with the “Deep
Learning Day,” an immersion into convolutional neural networks for
product developers and business leaders. Visit the new Summit web
pages to learn about the expanded program and register by December 18th to get the
Super Early Bird discount
using the promotional code 50SVi.
Speaking of events, I’d also like to tell you about an upcoming
tutorial covering deep learning for vision using convolutional
neural networks (CNNs) and the Caffe open-source framework. Taking
place February 22, 2016, this full-day event is organized by the
Embedded Vision Alliance and BDTI, and will take place at the Hyatt
Regency Hotel in Santa Clara, California. It will be presented by the
primary Caffe developers from U.C. Berkeley’s Vision and Learning
Center, and will take participants from an introduction through the
theory behind convolutional neural networks to their actual
implementation, and includes multiple hands-on labs. A discounted registration fee of $720
is available only until January 22nd,
so don’t delay in signing up! For more tutorial details, and to
register, please
visit the event page.
While you’re on the Alliance website, make sure to check out
all the other great content published in the last several weeks,
including:
Thanks as always for your support of the Embedded Vision
Alliance, and for your interest in and contributions to embedded vision
technologies, products and applications. Please don’t hesitate to let me know how the
Alliance can better serve your needs. I’ll be taking a bit of a
breather for the remainder of this year; your next edition of Embedded
Vision Insights will arrive in mid-January. Happy Holidays to you and
yours, along with the Alliance’s best wishes for an even better 2016!
Brian Dipert
Editor-In-Chief, Embedded Vision Alliance
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“Implementing Real-Time Hyperspectral Imaging,” a Presentation from
National Instruments
Kalyanramu Vemishetty, Senior Systems
Engineer at National Instruments, presents the “Implementing Real-Time
Hyperspectral Imaging tutorial within the “Front-End Image Processing
for Vision Applications” technical session at the October 2013 Embedded
Vision Summit East. Hyperspectral imaging enables vision systems to use
many spectral bands rather than just the typical red, green, blue
bands. This can be very useful in a variety of applications, such as
separating agricultural produce from contaminants. Fast Fourier
transforms (FFTs) are often used in implementing hyperspectral imaging,
but it can be challenging to attain the necessary performance in cost-,
power-and size-constrained systems such as self-contained smart cameras
for industrial use. In this presentation, Vemishetty introduces
hyperspectral imaging for embedded vision applications, explains how
FFTs are used in hyperspectral imaging, and explores two different
streaming architectures for implementing a column FFT required for
hyperspectral imaging in an FPGA, balancing hardware resource
utilization and processing throughput..
Basler’s Thies Moeller Explains Camera Interfaces
In this Vision Campus video, Basler’s
Thies Moeller describes the different kinds of camera interfaces and
explains which are the most common options. He then gives a practical
example to show how you can choose the right camera interface for your
vision system. Choosing the right interface for an industrial camera in
a particular application involves much more than just choosing the
right cable. Cable length, resolution, bandwidth, overall costs and
interface-specific features are all important selection criteria.
Careful consideration of these factors is the basis of getting the most
out of your system.
More Videos
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How Computer Vision is Re-shaping the Four Key Growth Segments of 2016
Computer vision and computational
photography are intrinsic aspects of the Internet of Things (IoT),
where cameras and sensors reign supreme. This article authored by
Alliance member company CEVA provides an overview of how the company
sees computer vision technology transforming what it feels are the most
critical markets in 2016: mobile, automotive, security and
surveillance, and drones. More
OpenCL Extensions and Other Optimizations for Vision Processors and Cores
Computer vision applications, unlike
traditional image processing, employ a heterogeneous mix of algorithms
with a great diversity of control flows and memory access patterns.
Therefore, according to Alliance member company Movidius, vision
processors are naturally evolving towards complex architectures that
include, besides the CPU and GPU-like arrays of processing units,
dedicated hardware blocks that specialize on certain portions of
computer vision processing. More
More Articles
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