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“Building a Typical Visual SLAM Pipeline,” a Presentation from Virgin Hyperloop One

Algorithms & Models, Edge AI and Vision Alliance, Object Tracking, Processors, Software, Summit 2018, Tools, Videos /

YoungWoo Seo, Senior Director at Virgin Hyperloop One, presents the “Building a Typical Visual SLAM Pipeline” tutorial at the May 2018 Embedded Vision Summit. Maps are important for both human and robot navigation. SLAM (simultaneous localization and mapping) is one of the core techniques for map-based navigation. As SLAM algorithms have matured and hardware has […]

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“Visual-Inertial Tracking for AR and VR,” a Presentation from Meta

Algorithms & Models, Augmented Reality, Edge AI and Vision Alliance, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Timo Ahonen, Director of Engineering for Computer Vision at Meta, presents the “Visual-Inertial Tracking for AR and VR” tutorial at the May 2018 Embedded Vision Summit. This tutorial covers the main current approaches to solving the problem of tracking the motion of a display for AR and VR use cases. Ahonen covers methods for inside-out

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“Understanding and Implementing Face Landmark Detection and Tracking,” a Presentation from PathPartner Technology

Algorithms & Models, Face Detection, Face Recognition, PathPartner Technology, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Jayachandra Dakala, Technical Architect at PathPartner Technology, presents the “Understanding and Implementing Face Landmark Detection and Tracking” tutorial at the May 2018 Embedded Vision Summit. Face landmark detection is of profound interest in computer vision, because it enables tasks ranging from facial expression recognition to understanding human behavior. Face landmark detection and tracking can be

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“Words, Pictures, and Common Sense: Visual Question Answering,” a Presentation from Facebook and Georgia Tech

Algorithms & Models, Edge AI and Vision Alliance, Object Identification, Processors, Software, Summit 2018, Tools, Videos /

Devi Parikh, Research Scientist at Facebook AI Research (FAIR) and Assistant Professor at Georgia Tech, presents the “Words, Pictures, and Common Sense: Visual Question Answering” tutorial at the May 2018 Embedded Vision Summit. Wouldn’t it be nice if machines could understand content in images and communicate this understanding as effectively as humans? Such technology would

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“Creating a Computationally Efficient Embedded CNN Face Recognizer,” a Presentation from PathPartner Technology

Algorithms & Models, Face Recognition, PathPartner Technology, Processors, Software, Summit 2018, Tools, Videos /

Praveen G.B., Technical Lead at PathPartner Technology, presents the “Creating a Computationally Efficient Embedded CNN Face Recognizer” tutorial at the May 2018 Embedded Vision Summit. Face recognition systems have made great progress thanks to availability of data, deep learning algorithms and better image sensors. Face recognition systems should be tolerant of variations in illumination, pose

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“Generative Sensing: Reliable Recognition from Unreliable Sensor Data,” a Presentation from Arizona State University

Algorithms & Models, Edge AI and Vision Alliance, Object Identification, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Lina Karam, Professor and Computer Engineering Director at Arizona State University, presents the “Generative Sensing: Reliable Recognition from Unreliable Sensor Data” tutorial at the May 2018 Embedded Vision Summit. While deep neural networks (DNNs) perform on par with – or better than – humans on pristine high-resolution images, DNN performance is significantly worse than human

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“Building A Practical Face Recognition System Using Cloud APIs,” a Presentation from the Washington County Sheriff’s Office

Algorithms & Models, Edge AI and Vision Alliance, Face Recognition, Processors, Security, Software, Summit 2018, Tools, Videos /

Chris Adzima, Senior Information Systems Analyst for the Washington County Sheriff’s Office in Oregon, presents the “Building a Practical Face Recognition System Using Cloud APIs” tutorial at the May 2018 Embedded Vision Summit. In this presentation, Adzima walks through the design and implementation of a face recognition system utilizing cloud computing and cloud computer vision

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May 2018 Embedded Vision Summit Slides

Aerospace and Defense, Algorithms & Models, Augmented Reality, Automotive, Biometrics, Downloads, Edge AI and Vision Alliance, Emotion Discernment, Entertainment, Face Detection, Face Recognition, Gesture Control, Industrial Vision (Computer Vision), Information Access and Analytics, Medical, Object Identification, Object Tracking, Optical Character Recognition, Processors, Retail, Robotics, Security, Sensors and Cameras, Software, Summit 2018, Tools /

The Embedded Vision Summit was held on May 21-24, 2018 in Santa Clara, California, as an 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 2018 Embedded Vision Summit

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“A New Approach to Mass Transit Security,” a Presentation from Lux Research

Edge AI and Vision Alliance, Face Recognition, Object Identification, Object Tracking, Processors, Security, Sensors and Cameras, Software, Videos /

Mark Bünger, Vice President of Research at Lux Research, delivers the presentation "A New Approach to Mass Transit Security" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. Bünger presents a revolutionary computer-vision-based methodology for public transit safety.

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“Instrumenting Greenhouses as Data-driven Manufacturing Facilities,” a Presentation from IUNU

Algorithms & Models, Edge AI and Vision Alliance, Object Identification, Processors, Sensors and Cameras, Software, Tools, Videos /

Matt King, Chief Technology Officer at IUNU, delivers the presentation "Instrumenting Greenhouses as Data-driven Manufacturing Facilities" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. King explains how his company is enabling increased efficiency in commercial greenhouses using robotic cameras, computer vision and machine learning.

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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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