Paul Zoratti, Automotive Driver Assistance System Architect at Xilinx, presents the "Vision-Based Automotive Driver Assistance Systems: Challenges and Approaches" tutorial within the "Embedded Vision Applications" technical session at the April 2013 Embedded Vision Summit.
José Alvarez, Engineering Director for Video Technology at Xilinx, presents the "Challenges and Opportunities in Accelerating OpenCV" tutorial within the "Developing Vision Software, Accelerators and Systems" technical session at the April 2013 Embedded Vision Summit. Computer vision continues to see increased adoption across a wide variety of applications. The industry's trend towards the incorporation of
Semiconductor and software advances are enabling medical devices to derive meaning from digital still and video images. By Brian Dipert Editor-in-Chief, Embedded Vision Alliance Senior Analyst, BDTI and Kamran Khan Technical Marketing Engineer, Xilinx This article was originally published in the May 2013 edition of MD+DI (Medical Device and Diagnostic Industry) Magazine. It is reprinted
The Embedded Vision Revolution Read More +
By Tom Catalino Vice President Critical Link, LLC and Asheesh Bhardwaj DSP Senior Applications Engineer Texas Instruments This is a reprint of a Texas Instruments-published white paper, which is also available here (560 KB PDF). Introduction Machine vision technology is growing in adoption, and it has been and will continue to be deployed in a
An Architecture for Compute-Intensive, Custom Machine Vision Read More +
By Jon Alexander, Technical Marketing Manager for ISM (Industrial, Scientific, Medical) Markets Xilinx Corporation Image enhancement functions – noise reduction, edge enhancement, dynamic range correction, digital zoom, scaling, etc – are key elements of many embedded vision designs, in improving the ability for downstream algorithms to automatically extract meaning from the image. Interface flexibility and
Using Xilinx FPGAs to Solve Endoscope System Architecture Challenges Read More +
Dan Isaacs, Director of Processing Product Marketing at Xilinx, and Michael Fawcett, Chief Technology Officer at iVeia, presents the "Image Processing for Object Recognition and Tracking" tutorial, part of the "Embedded Vision Applications and Algorithms" technical session at the September 2012 Embedded Vision Summit. Topics discussed included trends in image processing for embedded vision applications,
By Sateesh Reddy Jonnalagada and Vamsi Krishna Xilinx Corporation Embedded vision applications deal with a lot of data; a single 1080p60 (1920×1080 pixel per frame, 60 frames per second) 24-bit color video stream requires nearly 3 Gbps of bandwidth, and 8-bit alpha (transparency) or 3-D depth data further amplifies the payload by 33% in each
Designing High-Performance Video Systems in 7 Series FPGAs with the AXI Interconnect Read More +
Rapidly emerging applications in the area of embedded vision require ability to do real-time processing of one or more streams of HD video at high frame rates. In this demonstration, Xilinx's Navanee Sundaramoorthy, Product Manager for Processing Platforms, shows how you can use the Zynq-7000 Extensible Processing Platform with dual ARM Cortex-A9 processors and programmable
HD Video Processing using Xilinx’s Zynq-7000 EPP for Intelligent Video Systems Read More +
Converting images from one color domain to another is a common and often misunderstood operation in embedded vision processing. Image formats and color spaces vary when information is interchanged among processing domains. FPGAs provide a flexible, fast and scalable way of converting images using readily available IP cores. This video tutorial from José Alvarez, Video
Image Color Conversion and Formatting Using FPGAs Read More +
By José Alvarez Video Technology Engineering Director Xilinx Corporation José Alvarez, Video Technology Engineering Director at Xilinx Corporation, introduces the basic steps in the development of embedded vision systems: overall system definition, building IP processing pipelines using simulation models to speed up evaluation, using Targeted Design Platforms for rapid exploration and implementation, and establishing a
Introduction to Video and Image Processing System Design Using FPGAs Read More +
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