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
Avinash Nehemiah, Product Marketing Manager for Computer Vision at MathWorks, presents the "How to Create a Great Object Detector" tutorial at the May 2014 Embedded Vision Summit. Detecting objects of interest in images and video is a key part of practical embedded vision systems. Impressive progress has been made over the past few years by
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
Professor Li Zhang of the University of Wisconsin presents an introduction to computational photography at the December 2013 Embedded Vision Alliance Member Meeting.
This article is an expanded version of one originally published at EE Times' Embedded.com Design Line. It is reprinted here with the permission of EE Times. In order for robots to meaningfully interact with objects around them as well as move about their environments, they must be able to see and discern their surroundings. Cost-effective
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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
Ken Lee, CEO of VanGogh Imaging, presents the "Using FPGAs to Accelerate 3D Vision Processing: A System Developer's View" tutorial within the "Implementing Vision Systems" technical session at the October 2013 Embedded Vision Summit East. Embedded vision system designers must consider many factors in choosing a processor. This is especially true for 3D vision systems,
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