Face Recognition

May 2019 Embedded Vision Summit Slides

The Embedded Vision Summit was held on May 20-23, 2019 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 2019 Embedded Vision Summit […]

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

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

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

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

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

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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“Computer Vision on ARM: The Spirit Object Detection Accelerator,” a Presentation from ARM

Tim Hartley, Senior Product Manager in the Imaging and Vision Group at ARM, presents the "Computer Vision on ARM: The Spirit Object Detection Accelerator" tutorial at the May 2017 Embedded Vision Summit. In 2016, ARM released Spirit, a dedicated object detection accelerator, bringing industry-leading levels of power- and area-efficiency to computer vision workflows. In this

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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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“Combining Cloud and Edge Machine Learning to Deliver the Future of Video Monitoring,” a Presentation from Camio

Carter Maslan and Luca de Alfaro of Camio deliver the presentation "Combining Cloud and Edge Machine Learning to Deliver the Future of Video Monitoring" at the February 2017 Embedded Vision Alliance Member Meeting. Maslan and de Alfaro present their company's approach to using machine learning at the edge and in the cloud to deliver more

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Facial Analysis Delivers Diverse Vision Processing Capabilities

Computers can learn a lot about a person from their face – even if they don’t uniquely identify that person. Assessments of age range, gender, ethnicity, gaze direction, attention span, emotional state and other attributes are all now possible at real-time speeds, via advanced algorithms running on cost-effective hardware. This article provides an overview of

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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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