Face Recognition

May 2021 Embedded Vision Summit Slides

The Embedded Vision Summit was held online on May 25-28, 2021, 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 PDF form. To… May 2021 Embedded Vision Summit […]

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“Case Study: Facial Detection and Recognition for Always-On Applications,” a Presentation from Synopsys

Jamie Campbell, Product Marketing Manager for Embedded Vision IP at Synopsys, presents the “Case Study: Facial Detection and Recognition for Always-On Applications” tutorial at the May 2021 Embedded Vision Summit. Although there are many applications for low-power facial recognition in edge devices, perhaps the most challenging to design are always-on, battery-powered systems that use facial

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September 2020 Embedded Vision Summit Slides

The Embedded Vision Summit was held online on September 15-25, 2020, 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 PDF form. To… September 2020 Embedded Vision Summit

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“Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking,” a Presentation from Seedland

Kit Thambiratnam, General Manager of the Seedland AI Center, presents the “Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking” tutorial at the September 2020 Embedded Vision Summit. The recent COVID-19 outbreak necessitated monitoring in communities such as tracking of quarantined residents and tracking of close-contact interactions with sick individuals. High-density communities also have

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“Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification,” a Presentation from Imagination Technologies

Ana Salazar, Senior Research Manager at Imagination Technologies, presents the “Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification” tutorial at the September 2020 Embedded Vision Summit. This talk explores the challenges of deploying serial computer vision tasks implemented with DNNs. Neural network accelerators have demonstrated significant gains in

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Introducing Intel RealSense ID Facial Authentication

What’s New: Today, Intel introduced Intel® RealSense™ ID, an on-device solution that combines an active depth sensor with a specialized neural network designed to deliver secure, accurate and user-aware facial authentication. Intel RealSense ID works with smart locks, access control, point-of-sale, ATMs, kiosks and more. “Intel RealSense ID combines purpose-built hardware and software with a dedicated

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“Designing Home Monitoring Cameras for Scale,” a Presentation from Ring

Ilya Brailovskiy, Principal Engineer, and Changsoo Jeong, Head of Algorithm, both of Ring, present the "Optimizing SSD Object Detection for Low-power Devices" tutorial at the May 2019 Embedded Vision Summit. In this talk, Brailovskiy and Jeong discuss how Ring designs smart home video cameras to make neighborhoods safer. In particular, they focus on three key

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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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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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