This column was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. For most of its history, computer vision was a topic of academic research, gaining its first sizable commercial success in factory automation applications, where it has become an essential technology. Nevertheless, vision has remained a niche […]
Computer Vision Evolves Towards Ubiquity Read More +
Comprehensive Vision Platform Incorporates New CEVA-XM6 DSP Core, Hardware Accelerators, Neural Network Software Framework, Software Libraries and a Broad Set of Algorithms Enables Embedded Neural Networks for Mass Market Intelligent Vision Applications Targeted for Autonomous Driving, Sense and Avoid Drones, Virtual and Augmented Reality, Smart Surveillance, Smartphones, Robotics and More SANTA CLARA, Calif., – Linley
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
Vision Processing Opportunities in Virtual Reality Read More +
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,
Vision Processing Opportunities in Drones Read More +
Andy The, Product Manager at MathWorks, demonstrates the company's latest embedded vision technologies and products at the May 2016 Embedded Vision Summit. Specifically, Andy first demonstrates how Simulink supports HDL development from design through production. By combining Simulink with built-in FPGA hardware support, you can quickly design, tune, and deploy production ready HDL vision algorithms
MathWorks Demonstrations of MATLAB and Simulink for Embedded Vision Development Read More +
Marco Jacobs, Vice President of Marketing at videantis, demonstrates the company's latest embedded vision technologies and products at the May 2016 Embedded Vision Summit. Specifically, Jacobs demonstrates an implementation of the pedestrian detection algorithm based on OpenCV's HOG/SVM routine. The demonstration shown runs easily in real-time at very lower power on a chip that videantis
Videantis Demonstration of Pedestrian Detection Read More +
FEATURED VIDEOS Combining Flexibility and Low-Power in Embedded Vision Subsystems: An Application to Pedestrian Detection Bruno Lavigueur, Embedded Vision Subsystem Project Leader at Synopsys, presents a case study of a pedestrian detection application. Starting from a high-level functional description in OpenCV, he decomposes and maps the application onto a heterogeneous platform consisting of a high-performance
Embedded Vision Insights: August 2, 2016 Edition Read More +
Neural networks enable the identification of objects in still and video images with impressive speed and accuracy after an initial training phase. This so-called "deep learning" has been enabled by the combination of the evolution of traditional neural network techniques, with one latest-incarnation example known as a CNN (convolutional neural network), by the steadily increasing
Deep Learning for Object Recognition: DSP and Specialized Processor Optimizations Read More +
The substantial parallel processing resources available in modern graphics processors makes them a natural choice for implementing vision-processing functions. The rapidly maturing OpenCL framework enables the rapid and efficient development of programs that execute across GPUs and other heterogeneous processing elements within a system. In this article, we briefly review parallelism in computer vision applications,
Optimizing Computer Vision Applications Using OpenCL and GPUs Read More +
This blog post was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. When developing computer vision software, de facto standards such as the OpenCV open source computer vision library (which I mentioned in a recent column) are extremely valuable in helping you get your development done quickly
Industry Standards Simplify Computer Vision Software Development 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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