Face Recognition Functions
Synaptics Demonstration of Smart Video Conferencing on the Edge
Zafer Diab, Director of Product Marketing at Synaptics, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Diab demonstrates smart video conferencing on the edge in partnership with Pilot.ai. Enhancements in AI processing capabilities on edge devices are enabling a richer video conferencing experience. These capabilities
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
“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
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
“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
“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
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
“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
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
“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
“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
“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
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
“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.
“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
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
“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
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
