Vision technologies are rapidly emerging in the automotive market and improving the safety of vehicles. Fused with other technologies such as RADAR, LIDAR, and far infrared sensors, the automobile is well on its way to becoming fully self-driving. By Michael McDonald President, Skylane Technology Consulting Consultant, Embedded Vision Alliance Many of us have been affected, […]
This article was originally published at John Day's Automotive Electronics News. It is reprinted here with the permission of JHDay Communications. Cameras located in a vehicle's interior, coupled with cost-effective and power-efficient processors, can deliver abundant benefits to drivers and passengers alike. By Brian Dipert Editor-in-Chief Embedded Vision Alliance Tom Wilson Vice President, Business Development
Smart In-Vehicle Cameras Increase Driver and Passenger Safety Read More +
Roger Lanctot, Associate Director of the Automotive Practice at Strategy Analytics, delivers the presentation "Cameras In, On, and Around the Car: Understanding and Sizing Marketing Opportunities" at the May 2014 Embedded Vision Alliance Member Meeting.
Nathaniel Fairfield, Technical Lead at Google, presents the "Self-Driving Cars" keynote at the May 2014 Embedded Vision Summit. Self-driving cars have the potential to transform how we move: they promise to make us safer, give freedom to millions of people who can't drive, and give people back their time. The Google Self-Driving Car project was
“Self-Driving Cars,” an Embedded Vision Summit Keynote Presentation from Google Read More +
There is a growing need for fast and power-efficient computer vision on embedded devices. This session will focus on computer vision capabilities on embedded platforms available to ADAS developers, covering the OpenCV CUDA implementation and the new computer vision standard, OpenVX. In addition, Itseez traffic sign detection will be showcased. The algorithm is capable of
Real-Time Traffic Sign Recognition on Mobile Processors Read More +
This article was originally published at John Day's Automotive Electronics News. It is reprinted here with the permission of JHDay Communications. Thanks to the emergence of increasingly capable and cost-effective processors, image sensors, memories and other semiconductor devices, along with robust algorithms, it's now practical to incorporate computer vision into a wide range of embedded
Francis MacDougall, Senior Director of Technology at Qualcomm, presents the "Vision-Based Gesture User Interfaces" tutorial within the "Vision Applications" technical session at the October 2013 Embedded Vision Summit East. MacDougall explains how gestures fit into the spectrum of advanced user interface options, compares and contrasts the various 2-D and 3-D technologies (vision and other) available
Michael Tusch, Founder and CEO of Apical Imaging, presents the "Better Image Understanding Through Better Sensor Understanding" tutorial within the "Front-End Image Processing for Vision Applications" technical session at the October 2013 Embedded Vision Summit East. One of the main barriers to widespread use of embedded vision is its reliability. For example, systems which detect
Tom Michiels, R&D Manager at Synopsys, presents the "Designing a Multi-Core Architecture Tailored for Pedestrian Detection Algorithms" tutorial within the "Algorithms and Implementations" technical session at the October 2013 Embedded Vision Summit East. Pedestrian detection is an important function in a wide range of applications, including automotive safety systems, mobile applications, and industrial automation. A
Eric Gregori, Senior Software Engineer at BDTI, presents the "Accelerating Computer Vision Applications with the Hexagon DSP" tutorial at the September 2013 Qualcomm UPLINQ Conference. Smartphones, tablets and embedded systems increasingly use sophisticated vision algorithms to deliver capabilities like augmented reality and gesture user interfaces. Since vision algorithms are computationally demanding, a key challenge when
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