Francis MacDougall, Senior Director of Technology at Qualcomm, presents the "Vision-Based Gesture User Interfaces" tutorial at the May 2014 Embedded Vision Summit. The means by which we interact with the machines around us is undergoing a fundamental transformation. While we may still sometimes need to push buttons, touch displays and trackpads, and raise our voices, […]
Kees Vissers, Distinguished Engineer at Xilinx, presents the "Programming Novel Recognition Algorithms on Heterogeneous Architectures" tutorial at the May 2014 Embedded Vision Summit. The combination of heterogeneous systems, consisting of processors and FPGA, is a high-performance implementation platform for image and vision processing. One of the significant hurdles in leveraging the compute potential was the
Yann LeCun, Director of AI Research at Facebook and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University, presents the "Convolutional Networks: Unleashing the Potential of Machine Learning for Robust Perception Systems" keynote at the May 2014 Embedded Vision Summit. Convolutional Networks (ConvNets) have become the dominant method
Ken Lee, Founder of VanGogh Imaging, presents the "Fast 3D Object Recognition in Real-World Environments" tutorial at the May 2014 Embedded Vision Summit. Real-time 3D object recognition can be computationally intensive and difficult to implement when there are a lot of other objects (i.e. clutter) around the target. There are several approaches to deal with
Chris Rowen, Fellow at Cadence, presents the "Taming the Beast: Performance and Energy Optimization Across Embedded Feature Detection and Tracking" tutorial at the May 2014 Embedded Vision Summit. This presentation looks at a cross-section of advanced feature detectors, and considers the algorithm, bit precision, arithmetic primitives and implementation optimizations that yield high pixel processing rates,
The Embedded Vision Summit was held on May 29, 2014 in Santa Clara, California, as a technical educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The program for the event included the following presentations, whose PDF-formatted foilsets are available for download as a… May 2014 Embedded Vision Summit
May 2014 Embedded Vision Summit Proceedings Read More +
For decades, computer vision technology was found mainly in university laboratories and a few niche applications. Today, virtually every tablet and smartphone is capable of sophisticated vision functions such as hand gesture recognition, face recognition, gaze tracking, and object recognition. These capabilities are being used to enable new types of applications, user interfaces, and use
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Larry Matthies, Supervisor of the Computer Vision Group at NASA's Jet Propulsion Laboratory, delivers the technology presentation, "Vision-Based Navigation Applications: From Planetary Exploration to Consumer Devices," at the March 2014 Embedded Vision Alliance Member Meeting. Dr. Matthies is a Senior Research Scientist at JPL and is the Supervisor of the Computer Vision Group in the
This article was originally published at Electronic Engineering Journal. It is reprinted here with the permission of TechFocus Media. Although augmented reality was first proposed and crudely demonstrated nearly fifty years ago, its implementation was until recently only possible on bulky and expensive computers. Nowadays, however, the fast, low power and cost-effective processors and high
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Do you want to write your own blazing fast, interactive mobile apps using computer vision technology? Apps that can make your camera smarter, find people's faces, understand their gestures, interpret scenes and augment them with graphics? The Tegra super chip and the OpenCV for Tegra library can help you to do just that! OpenCV for
Introduction to OpenCV for Tegra 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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