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Augmented Reality

Augmented Reality Functions

“Performing Multiple Perceptual Tasks With a Single Deep Neural Network,” a Presentation from Magic Leap

Andrew Rabinovich, Director of Deep Learning at Magic Leap, presents the "Performing Multiple Perceptual Tasks With a Single Deep Neural Network" tutorial at the May 2017 Embedded Vision Summit. As more system developers consider incorporating visual perception into smart devices such as self-driving cars, drones and wearable computers, attention is shifting toward practical formulation and

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“Computer Vision and Machine Learning at the Edge,” a Presentation from Qualcomm Technologies

Michael Mangan, a member of the Product Manager Staff at Qualcomm Technologies, presents the "Computer Vision and Machine Learning at the Edge" tutorial at the May 2017 Embedded Vision Summit. Computer vision and machine learning techniques are applied to myriad use cases in smartphones today. As mobile technology expands beyond the smartphone vertical, both technologies

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“Computer Vision and Machine Learning at the Edge,” a Presentation from Qualcomm Technologies

Michael Mangan, a member of the Product Manager Staff at Qualcomm Technologies, presents the "Computer Vision and Machine Learning at the Edge" tutorial at the May 2017 Embedded Vision Summit. Computer vision and machine learning techniques are applied to myriad use cases in smartphones today. As mobile technology expands beyond the smartphone vertical, both technologies

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May 2017 Embedded Vision Summit Slides

The Embedded Vision Summit was held on May 1-3, 2017 in Santa Clara, California, as a educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations delivered at the Summit are listed below. All of the slides from these presentations are included in… May 2017 Embedded Vision Summit

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May 2016 Embedded Vision Summit Proceedings

The Embedded Vision Summit was held on May 2-4, 2016 in Santa Clara, California, as a educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations presented at the Summit are listed below. All of the slides from these presentations are included in… May 2016 Embedded Vision Summit

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“Harman’s Augmented Navigation Platform—The Convergence of ADAS and Navigation,” a Presentation from Harman

Alon Atsmon, Vice President of Technology Strategy at Harman International, presents the "Harman’s Augmented Navigation Platform—The Convergence of ADAS and Navigation" tutorial at the May 2015 Embedded Vision Summit. Until recently, advanced driver assistance systems (ADAS) and in-car navigation systems have evolved as separate standalone systems. Today, however, the combination of available embedded computing power

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Practical Computer Vision Enables Digital Signage with Audience Perception

This article was originally published at Information Display Magazine. It is reprinted here with the permission of the Society of Information Display. Signs that see and understand the actions and characteristics of individuals in front of them can deliver numerous benefits to advertisers and viewers alike.  Such capabilities were once only practical in research labs

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“How to Make the World More Interactive: Augmented Reality as the Interface Between Wearable Tech and the Internet of Things,” a Presentation from AugmentedReality.org

Ori Inbar, co-founder and CEO of AugmentedReality.org, presents the "How to Make the World More Interactive: Augmented Reality as the Interface Between Wearable Tech and the Internet of Things" tutorial at the May 2014 Embedded Vision Summit. In this talk, Inbar explains how augmented reality, which relies heavily on embedded vision, is transitioning from a

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May 2014 Embedded Vision Summit Technical Presentation: “Evolving Algorithmic Requirements for Recognition and Classification in Augmented Reality,” Simon Morris, CogniVue

Simon Morris, CEO of CogniVue, presents the "Evolving Algorithmic Requirements for Recognition and Classification in Augmented Reality" tutorial at the May 2014 Embedded Vision Summit. Augmented reality (AR) applications are based on accurately computing a camera's 6 degrees of freedom (6DOF) position in 3-dimensional space, also known as its "pose". In vision-based approaches to AR,

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Augmented Reality: A Compelling Mobile Embedded Vision Opportunity

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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September 2013 Qualcomm UPLINQ Conference Presentation: “Accelerating Computer Vision Applications with the Hexagon DSP,” Eric Gregori, BDTI

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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October 2013 Embedded Vision Alliance Member Meeting Keynote: “Augmented Reality Opportunities and Challenges: From Novelty to Productivity,” Ori Inbar, AugmentedReality.org

Ori Inbar, Founder and CEO of AugmentedReality.org, delivers the keynote, "Augmented Reality Opportunities and Challenges: From Novelty to Productivity," at the October 2013 Embedded Vision Alliance Member Meeting. In this presentation, Ori explains how augmented reality (which relies heavily on embedded vision) is transitioning from a bleeding-edge technology embraced mainly by enthusiasts to a mainstream

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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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