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 a half GByte of storage per second, along with nearly 3 Gbps of bandwidth, and 8-bit alpha (transparency) or 3-D depth data further amplifies the payload by 33% in […]
Fundamentals of coolSRAM-1T Memory IP Read More +
VR (virtual reality) systems are beginning to incorporate practical computer vision techniques, dramatically improving the user experience as well as reducing system cost. This article provides an overview of embedded vision opportunities in virtual reality systems, such as environmental mapping, gesture interface, and eye tracking, along with implementation details. It also introduces an industry alliance
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UAVs (unmanned aerial vehicles), commonly known as drones, are a rapidly growing market and increasingly leverage embedded vision technology for digital video stabilization, autonomous navigation, and terrain analysis, among other functions. This article reviews drone market sizes and trends, and then discusses embedded vision technology applications in drones, such as image quality optimization, autonomous navigation,
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LETTER FROM THE EDITOR Dear Colleague, Next Thursday, September 22 from 9 am to 5 pm, the primary Caffe developers from U.C. Berkeley's Vision and Learning Center will present "Deep Learning for Vision Using CNNs and Caffe," a full-day detailed technical tutorial focused on convolutional neural networks (CNNs) for vision and the Caffe framework for
Embedded Vision Insights: September 13, 2016 Edition Read More +
FEATURED VIDEOS "Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation," a Presentation from Synopsys Deep learning-based object detection using convolutional neural networks (CNN) has recently emerged as one of the leading approaches for achieving state-of-the-art detection accuracy for a wide range of object classes. Most of the current CNN-based detection algorithm implementations run on high-performance
Embedded Vision Insights: August 30, 2016 Edition Read More +
FEATURED VIDEOS "3D from 2D: Theory, Implementation, and Applications of Structure from Motion," a Presentation from videantis Structure from motion uses a unique combination of algorithms that extract depth information using a single 2D moving camera. Using a calibrated camera, feature detection, and feature tracking, the algorithms calculate an accurate camera pose and a 3D
Embedded Vision Insights: August 16, 2016 Edition Read More +
Sofiane Yous, Principal Scientist in the machine intelligence group at Movidius, presents the "Dataflow: Where Power Budgets Are Won and Lost" tutorial at the May 2016 Embedded Vision Summit. This presentation showcases stories from the front lines in the battle between power and performance in embedded vision, deep learning and computational imaging applications. First, Youse
“Dataflow: Where Power Budgets Are Won and Lost,” a Presentation from Movidius Read More +
Jeff Bier, Founder of the Embedded Vision Alliance, welcomes attendees to the May 2016 Embedded Vision Summit on May 2, 2016 (Day 1). Bier 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
May 2016 Embedded Vision Summit Introductory Presentation (Day 1) Read More +
Seema Mirchandaney, Engineering Manager for Software Tools at Synopsys, presents the "Using the OpenCL C Kernel Language for Embedded Vision Processors" tutorial at the May 2016 Embedded Vision Summit. OpenCL C is a programming language that is used to write computation kernels. It is based on C99 and extended to support features such as multiple
Elif Albuz, Technical Lead for the VisionWorks Toolkit at NVIDIA, presents the "NVIDIA VisionWorks, a Toolkit for Computer Vision" tutorial at the May 2016 Embedded Vision Summit. In this talk, Albuz introduces the NVIDIA VisionWorks toolkit, a software development package for computer vision and image processing. VisionWorks implements and extends the Khronos OpenVX standard, and
“NVIDIA VisionWorks, a Toolkit for Computer Vision,” a Presentation from NVIDIA Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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