|
Dear Colleague,
Back in early
December, I mentioned that some of the
presentations from the upcoming Alliance Member Meeting would
subsequently appear on the website. That time is now; check out the
following newly published content:
Speaking of IoT, make sure you also take a look at a newly
published article on the Alliance website, authored by yours truly,
entitled “The
Internet of Things That See.” The IoT, widely anticipated to be a
notable driver of both semiconductor and software demand in coming
years, is differentiated from the “normal” Internet by the direct
machine-to-machine aspects of its transactions. Much of its data is
generated by a variety of sensor technologies, not surprisingly
including image sensors. And although automated security systems are a
perhaps obvious application of vision-enabled IoT technology, plenty of
other examples exist in both current and emerging products. In fact, as
IoT devices become increasingly networked to each other and to the
greater ecosystem, the data supplied by their image sensors and
analyzed by their vision processors will be used in ways that we can’t
even yet imagine.
Read through the IoT article for more information, and sound
off in the comments with your own thoughts. And while you’re on the
site, check out all the other great new content published there in
recent weeks. 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.
Brian Dipert
Editor-In-Chief, Embedded Vision Alliance
|
|
“Efficient Super-Resolution Algorithms and Implementation
Techniques for Constrained Applications,” an
Embedded VIsion Summit Presentation from Ilan Yona of CEVA
MIlan Yona, Director of Imaging and
Computer Vision at CEVA, presents the “Efficient Super-Resolution
Algorithms and Implementation Techniques for Constrained Applications”
tutorial within the “Front-End Image Processing for Vision
Applications” technical session at the October 2013 Embedded Vision
Summit East. Image quality is a critical challenge in many
applications, including smart phones, especially when using low quality
sensors or when using digital zoom for enlarging part of the image.
Super-resolution is a set of techniques that can address this challenge
by combining multiple images to produce a single, higher quality image.
However, super-resolution can be extremely computationally demanding,
so when implementing it on a constrained platform (such as a smart
phone), the algorithm should be carefully chosen, balancing image
quality, speed, and power consumption. CEVA tested variety of known
super-resolution algorithms and found that they were not efficient for
cost- and power-constrained systems. The company then developed a new
algorithm that produces good quality images and is suitable for
constrained systems. In this talk, Ilan Yona explains how
super-resolution works, introduces the previously known algorithms, and
presents CEVA’s new algorithm and a sample implementation of it.
“Processors for Embedded Vision:
Technology and Market Trends,” an Embedded Vision Alliance Member
Meeting Presentation from the Linley Group
Linley Gwennap, founder and principal
analyst of The Linley Group, delivers the presentation “Processors for
Embedded Vision: Technology and Market Trends” at the September 2014
Embedded Vision Alliance Member Meeting. Linley discusses vision
processing alternatives and trends in a variety of markets and
applications; mobile devices, automotive systems, cloud servers, and
the Internet of Things.
More Videos
|
|
Semiconductor Innovations in Computer Vision and Mobile
Photography
A previous
article in this series discussed the rapid growth in photography
and computer vision, the ability to extract information from an image.
Promising new computational photography features are being added
despite some major challenges. The sensor pixel size is rapidly
approaching the wavelength of light, leaving limited opportunity to
reduce costs by further shrinking pixels, the fundamental building
block of the image sensor. In addition, the increasing performance
requirements of video and vision provide challenges for mobile phones
and embedded solutions that are also being called upon to run more and
more applications. This article looks at some of the emerging silicon
architectures, in the form of optimized and innovative processors and
sensors, that are enabling these advanced features. More
Automotive Touchless Sensing Market Will Reach $6 Billion by
2020
Touch Display Research Inc., an
independent market research and consulting firm, forecasts the
automotive touchless sensing market will reach $6 Billion by 2020.
“Gesture control, voice recognition, eye tracking, proximity touch, and
motion sensors have gained momentum in the past few years. We recommend
automotive industry to adopt more touchless sensors to help with
monitoring babies at the car seats, assisting senior drivers, and
preventing sudden-illness-caused collisions,” said Dr. Jennifer
Colegrove, Principal Analyst at Touch Display Research. “We also
recommend manufacturers to consider both portable and built-in
solutions to save cost.” More
More Articles
|
