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Embedded Vision Insights
VOL. 5, NO. 15 A NEWSLETTER FROM THE EMBEDDED VISION ALLIANCE Late August 2015
IN THIS EDITION
To view this newsletter online, please click here
- New Content from the Embedded Vision Summit and Alliance Member Meeting
- Embedded Lucas-Kanade Tracking: Theory and Implementation
- Has Neural Network Processors' Time Come?
- Embedded Vision Community Conversations
- Embedded Vision in the News
LETTER FROM THE EDITOR
The Alliance continues to publish videos of great presentations from May's Embedded Vision Summit. Make sure you check out, for example, the highly rated keynote "Enabling Ubiquitous Visual Intelligence Through Deep Learning," by Dr. Ren Wu, formerly distinguished scientist at Baidu's Institute of Deep Learning (IDL). Dr. Wu shares an insider's perspective on the practical use of neural networks for vision.
In "Navigating the Vision API Jungle: Which API Should You Use and Why?", Neil Trevett, President of the Khronos Group, maps the landscape of APIs for vision software development. Long-time Alliance collaborator Gary Bradski, President of the OpenCV Foundation, provides an insider's perspective on the new version of OpenCV and how vision developers can utilize it in his presentation, "The OpenCV Open Source Computer Vision Library: Latest Developments." Also make sure to take a look at "Harman's Augmented Navigation Platform: The Convergence of ADAS and Navigation" from that company's Vice President of Technology Strategy, Alon Atsmon.
Roberto Mijat, Visual Computing Marketing Manager at ARM, explores when it makes sense to utilize a graphics core as a coprocessor in his presentation, "Understanding the Role of Integrated GPUs in Vision Applications." And echoing Dr. Wu's neural network focus, Jeff Gehlhaar, Vice President of Technology at Qualcomm, used his presentation "Deep-learning-based Visual Perception in Mobile and Embedded Devices: Opportunities and Challenges" to discuss the benefits, challenges and solutions for implementing neural networks in mobile and embedded devices. And the insights continued the next day at the quarterly Alliance Member Meeting: in "Combining Vision, Machine Learning and Natural Language Processing to Answer Everyday Questions," Faris Alqadah, CEO and Co-Founder of QM Scientific, explains how his firm is simplifying shopping for consumers by extracting and organizing product information from many data sources.
While you're on the Alliance website, make sure to check out all the other great content recently published there. And for timely notification of the publication of new content, subscribe to our RSS feed and Facebook, Google+, LinkedIn company and group, and Twitter social media channels. 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.
Editor-In-Chief, Embedded Vision Alliance
"Embedded Lucas-Kanade Tracking: How It Works, How to Implement It, and How to Use It," a Presentation from Goksel Dedeoglu of Perceptonic
Goksel Dedeoglu, Ph.D., Founder and Lab Director of PercepTonic, presents the "Embedded Lucas-Kanade Tracking: How It Works, How to Implement It, and How to Use It" tutorial at the May 2014 Embedded Vision Summit. This tutorial is intended for technical audiences interested in learning about the Lucas-Kanade (LK) tracker, also known as the Kanade-Lucas-Tomasi (KLT) tracker. Invented in the early 80s, this method has been widely used to estimate pixel motion between two consecutive frames. Dedeoglu presents how the LK tracker works and discuss its advantages, limitations, and how to make it more robust and useful. Using DSP-optimized functions from TI's Vision Library (VLIB), he also shows how to detect feature points in real-time and track them from one frame to the next using the LK algorithm. He demonstrates this on Texas Instruments' C6678 Keystone DSP, where he detects and tracks thousands of Harris corner features in 1080p HD resolution video.
Introduction to the Embedded Vision Opportunity and the Embedded Vision Alliance Community
Jeff Bier, Founder of the Embedded Vision Alliance and President and Co-Founder of BDTI, presents the introductory remarks at the May 2015 Embedded Vision Summit. Jeff provides an overview of the embedded vision market opportunity, challenges, solutions and trends. He also introduces the Embedded Vision Alliance and the resources it offers for both product creators and potential members, and reviews the event agenda and other logistics.
Neural Network Processors: Has Their Time Come?
Lately, neural network algorithms have been gaining prominence in computer vision and other fields where there's a need to extract insights based on ambiguous data. Classical computer vision algorithms typically attempt to identify objects by first detecting small features, then finding collections of these small features to identify larger features, and then reasoning about these larger features to deduce the presence and location of an object of interest (such as a face). These approaches can work well when the objects of interest are fairly uniform and the imaging conditions are favorable, but they often struggle when conditions are more challenging. An alternative approach, convolutional neural networks ("CNNs"), massively parallel algorithms made up of layers computation nodes, have been showing impressive results on these more challenging problems. More
Facebook Oculus Acquires Pebbles Interfaces for Gesture Control
Last month, Facebook's subsidiary Oculus reported that it had acquired Israel-based Pebbles Interfaces. Based in Israel, Pebbles Interfaces has spent the past five years developing technology that uses custom optics, sensor systems and algorithms to detect and track hand movement. Pebbles Interfaces will be joining the hardware engineering and computer vision teams at Oculus to help advance virtual reality, tracking, and human-computer interactions. More
FEATURED COMMUNITY DISCUSSION FEATURED NEWS
Upcoming Free Qualcomm Vuforia Webinar Discusses Enabling Mobile Apps to See
Intel Expands Developer Opportunities as Computing Expands Across All Areas of Peoples' Lives
Altera Launches Worldwide SoC FPGA Developers Forums
ON Semiconductor Introduces Series of Advanced Image Co-Processors for Next Generation Automotive Camera
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Sunday, August 23, 2015
---------- Forwarded message ----------
From: Hack A Robot <firstname.lastname@example.org>
Date: Saturday, August 22, 2015
Subject: Invitation: Let's build a humanoid robot with computer vision
Wednesday, September 9, 2015
Just when we thought we were done with the video codec wars in WebRTC – we found out we're only just beginning.
In the past several weeks we've seen the names Thor, Daala, VP9 and H.265 thrown in the news as potential candidates to replace our current generation of video codecs. How is that going to play out, and where are we headed with all this?
We can't be sure but we think Tsahi Levent-Levi can make a few educated guesses about it.
Join TokBox and Tsahi to discuss the power plays of the video coding industry.
Come along to TokBox HQ at 6:00pm for a 6:30pm start.
As usual, we will provide pizza and beer.
We look forward to seeing you there!
About the speaker:
Tsahi Levent-Levi is an Independent Analyst and Consultant for WebRTC.
Tsahi Levent-Levi has over 15 years of experience in the telecommunications, VoIP and 3G industry as an engineer, manager, marketer and CTO. Tsahi is an entrepreneur, independent analyst and consultant, assisting companies to form a bridge between technologies and business strategy in the domain of telecommunications.
Tsahi has an MSc in Computer Science, and an MBA degree specializing in Entrepreneurship and Strategy. Tsahi has been granted three patents related to 3G-324M and VoIP. He acted as the chairman of various activity groups within the IMTC, an organization focusing on interoperability of multimedia communications.
Tsahi is the author and editor of bloggeek.me, which focuses on the ecosystem and business opportunities around WebRTC.