Face Recognition Functions
“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
“Intelligent Video Surveillance: Are We There Yet?,” a Presentation from CheckVideo
Nik Gagvani, President and General Manager of CheckVideo, delivers the presentation "Intelligent Video Surveillance: Are We There Yet?" at the September 2016 Embedded Vision Alliance Member Meeting. Gagvani provides an insider's perspective on vision-enabled video surveillance applications.
Vision Processing Opportunities in Drones
UAVs (unmanned aerial vehicles), commonly known as drones, are a rapidly growing market and increasingly leverage embedded vision technology for digital video stabilization, autonomous navigation, and terrain analysis, among other functions. This article reviews drone market sizes and trends, and then discusses embedded vision technology applications in drones, such as image quality optimization, autonomous navigation,
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
“Techniques for Efficient Implementation of Deep Neural Networks,” a Presentation from Stanford
Song Han, graduate student at Stanford, delivers the presentation "Techniques for Efficient Implementation of Deep Neural Networks" at the March 2016 Embedded Vision Alliance Member Meeting. Song presents recent findings on techniques for the efficient implementation of deep neural networks.
Deep Learning Use Cases for Computer Vision (Download)
Six Deep Learning-Enabled Vision Applications in Digital Media, Healthcare, Agriculture, Retail, Manufacturing, and Other Industries The enterprise applications for deep learning have only scratched the surface of their potential applicability and use cases. Because it is data agnostic, deep learning is poised to be used in almost every enterprise vertical… Deep Learning Use Cases for
Using Convolutional Neural Networks for Image Recognition
This article was originally published at Cadence's website. It is reprinted here with the permission of Cadence. Convolutional neural networks (CNNs) are widely used in pattern- and image-recognition problems as they have a number of advantages compared to other techniques. This white paper covers the basics of CNNs including a description of the various layers
Vision in Wearable Devices: Enhanced and Expanded Application and Function Choices
A version of this article was originally published at EE Times' Embedded.com Design Line. It is reprinted here with the permission of EE Times. Thanks to the emergence of increasingly capable and cost-effective processors, image sensors, memories and other semiconductor devices, along with robust algorithms, it's now practical to incorporate computer vision into a wide
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
Smart In-Vehicle Cameras Increase Driver and Passenger Safety
This article was originally published at John Day's Automotive Electronics News. It is reprinted here with the permission of JHDay Communications. Cameras located in a vehicle's interior, coupled with cost-effective and power-efficient processors, can deliver abundant benefits to drivers and passengers alike. By Brian Dipert Editor-in-Chief Embedded Vision Alliance Tom Wilson Vice President, Business Development
