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Dynamic Range And Edge Detection: An Example Of Embedded Vision Algorithms’ Dependence On In-Camera Image Processing

By Michael Tusch Founder and CEO Apical Limited This article will expand on the theme initiated in the premier article of this series, that of exploring how the pixel processing performed in cameras can either enhance or hinder the performance of embedded vision algorithms. Achieving natural or otherwise aesthetically pleasing camera images is normally considered …

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Implementing Vision Capabilities in Embedded Systems

by Jeff Bier Founder and President, BDTI September 29, 2011 This paper was originally published at the 2011 Embedded Systems Conference Boston. Abstract—With the emergence of increasingly capable processors, it’s becoming practical to incorporate computer vision capabilities into a wide range of embedded systems, enabling them to analyze their environments via video inputs. Products like …

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Introduction To Computer Vision Using OpenCV (Video)

By Eric Gregori Senior Software Engineer and Embedded Vision Specialist BDTI This video training session covers some of the algorithms available in OpenCV, and is intended for programmers and non-programmers alike. You can download (and install) the BDTI OpenCV Executable Demo Package here and follow along. The examples run on various Windows operating systems and …

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Introduction To Computer Vision Using OpenCV (Software Demo)

The BDTI OpenCV Executable Demo Package is an easy-to-use tool which allows anyone with a Windows computer and a web camera to experiment with some of the algorithms in OpenCV v2.3. After downloading the installer zip file, double-click on the zip file to uncompress its contents, then double-click on the… Introduction To Computer Vision Using …

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Introduction To Computer Vision Using OpenCV (Article)

By Eric Gregori Senior Software Engineer and Embedded Vision Specialist BDTI The name OpenCV has become synonymous with computer vision, but what is OpenCV? OpenCV is a collection of software algorithms put together in a library to be used by industry and academia for computer vision applications and research (Figure 1). OpenCV started at Intel …

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Interview With Professor Jitendra Malik, UC Berkeley, Part One (August 17, 2011)

Jeff Bier, Founder of the Embedded Vision Alliance, interviews Jitendra Malik, Arthur J. Chick Professor of EECS at the University of California at Berkeley, on August 17, 2011. Bier and Malik discuss computer vision's history, current status, and future trends. This is part one of a three-part video series. Please click here for part two.

Interview With Professor Jitendra Malik, UC Berkeley, Part Two (August 17, 2011)

Jeff Bier, Founder of the Embedded Vision Alliance, interviews Jitendra Malik, Arthur J. Chick Professor of EECS at the University of California at Berkeley, on August 17, 2011. Bier and Malik discuss computer vision's history, current status, and future trends. This is part two of a three-part video series. Please click here for part three.

Interview With Professor Jitendra Malik, UC Berkeley, Part Three (August 17, 2011)

Jeff Bier, Founder of the Embedded Vision Alliance, interviews Jitendra Malik, Arthur J. Chick Professor of EECS at the University of California at Berkeley, on August 17, 2011. Bier and Malik discuss computer vision's history, current status, and future trends. This is the final part three of a three-part video series.

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How Does Camera Performance Affect Analytics?

By Michael Tusch Founder and CEO Apical Limited Camera designers have decades of experience in creating image processing pipelines which produce attractive and/or visually accurate images, but what kind of image processing produces video which is well-purposed for subsequent analytics? It seems reasonable to begin by considering a conventional ISP (image signal processor). After all, …

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