Welcome to Embedded Vision Insights, the newsletter of the Embedded Vision Alliance.
The Embedded Vision Alliance is an industry partnership dedicated to helping engineers use embedded vision technology to design "machines that see." The Alliance currently comprises 18 companies, including leaders in semiconductors, tools, algorithms, cameras, and design services for embedded vision applications. Our web site, www.Embedded-Vision.com, is growing rapidly with video seminars, technical articles, coverage of industry news, and discussion forums.
We are excited to launch the Embedded Vision Insights newsletter to help keep the industry informed on developments related to designing machines that see. Initially the newsletter will be published on a monthly basis. Please help us get the word out by forwarding Embedded Vision Insights to colleagues who will find it valuable, and encouraging them to subscribe. Please also send us your feedback about the newsletter and how we can improve it. I look forward to hearing from you.
Founder, Embedded Vision Alliance
An Introduction to Computer Vision Using OpenCV
This video training session from Eric Gregori, BDTI Senior Software Engineer and Embedded Vision Specialist, covers some of the algorithms available in OpenCV and is intended for programmers and non-programmers alike. You can download (and install) the pre-built examples and follow along. The examples run on various Windows operating systems and require no prior programming knowledge. For advanced users, source code is also provided. Also, you can read an online article that provides even more information on these OpenCV examples.
An Interview with Professor Jitendra Malik
In this three-part video series, Jeff Bier interviews embedded vision academic luminary Jitendra Malik, Arthur J. Chick Professor of EECS at the University of California at Berkeley. Professor Mailk discusses the progression of the computer vision industry over his 25 year academic career to date, as well as its more recent expansion into embedded vision systems, and he also forecasts possible future trends.
A Conversation with Gary Bradski
In this two-part video series, Scott Gardner from the Embedded Vision Alliance interviews Gary Bradski, the creator of OpenCV, the open-source library for computer vision. Gary discusses his latest work on robotics at Willow Garage, along with some of the features in version 2.0 of OpenCV.
Lens Distortion Correction
With less-than-ideal optical systems, such as those found in inexpensive smartphones and tablets, incoming video frames will tend to be distorted along their edges. The most common types of lens distortions are barrel distortion, pincushion distortion, or some combination of the two. This article from Shehrzad Qureshi, President and Founder of Medallion Solutions LLC, discusses strategies and implementations for correcting these types of lens distortions. More
Design Guidelines for Embedded Real-Time Face Detection Applications
In this article, Eldad Melamed, Project Manager for Video Algorithms at CEVA, presents an application that detects faces in a digital image, crops the selected main face, and resizes it to a fixed size output image. The application can be used on a single image or on a video stream, and it is designed to run in real time. Although the target implementation is a programmable vector processor, the general-purpose steps taken can be used to implement similar computer vision algorithms on any mobile device. More
Selecting and Designing with an Image Sensor: The Tradeoffs You'll Need to Master
A diversity of image sensor options are available for your consideration, differentiated both in terms of their fundamental semiconductor process foundations and of their circuit (and filter, microlens and other supplement) implementations. This article from Brian Dipert, Editor-In-Chief of the Embedded Vision Alliance, helps you understand their respective strengths and shortcomings, which are critical to making an appropriate product selection for your next embedded vision system design. More
FEATURED FORUM DISCUSSIONS
Is OpenCV being deployed in any high-volume products?
Machine Vision Libraries
What type of CPU do you plan to use for pixel-level processing?
The counterpart of GenICam for hardware interface?
More Forum Discussions
Emotions in motion: sentiment discernment comes to embedded vision.
Networked camera phones: traffic timing awareness makes good gas mileage sense.
Facial recognition: is caricature the key to accurate cognition?
Motion capture: embedded vision advancements make it beefier and faster.
Kinect for the visually-impaired.