Algorithms

“Recognizing Novel Objects in Novel Surroundings with Single-shot Detectors,” a Presentation from the University of North Carolina at Chapel Hill

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

Alexander C Berg, Associate Professor at the University of North Carolina at Chapel Hill and CTO of Shopagon, presents the “Recognizing Novel Objects in Novel Surroundings with Single-shot Detectors” tutorial at the May 2018 Embedded Vision Summit. Berg’s group’s 2016 work on single-shot object detection (SSD) reduced the computation cost for accurate detection of object […]

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

Algorithms, 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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“Developing Computer Vision Algorithms for Networked Cameras,” a Presentation from Intel

Algorithms, Intel, Processors, Security, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Dukhwan Kim, computer vision software architect at Intel, presents the “Developing Computer Vision Algorithms for Networked Cameras” tutorial at the May 2018 Embedded Vision Summit. Video analytics is one of the key elements in network cameras. Computer vision capabilities such as pedestrian detection, face detection and recognition and object detection and tracking are necessary for

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

Algorithms, 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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“Bad Data, Bad Network, or: How to Create the Right Dataset for Your Application,” a Presentation from AMD

Algorithms, AMD, Processors, Software, Summit 2018, Tools, Videos /

Mike Schmit, Director of Software Engineering for computer vision and machine learning at AMD, presents the “Bad Data, Bad Network, or: How to Create the Right Dataset for Your Application” tutorial at the May 2018 Embedded Vision Summit. When training deep neural networks, having the right training data is key. In this talk, Schmit explores

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

Algorithms, 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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“From Feature Engineering to Network Engineering,” a Presentation from ShatterLine Labs and AMD

Algorithms, AMD, Processors, Software, Summit 2018, Tools, Videos /

Auro Tripathy, Founding Principal at ShatterLine Labs (representing AMD), presents the “From Feature Engineering to Network Engineering” tutorial at the May 2018 Embedded Vision Summit. The availability of large labeled image datasets is tilting the balance in favor of “network engineering”instead of “feature engineering”. Hand-designed features dominated recognition tasks in the past, but now features

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“Data-driven Business Models Enabled by 3D Vision Technology,” a Presentation from FRAMOS

Algorithms, FRAMOS, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Christopher Scheubel, Head of IP and Business Development at FRAMOS, presents the “Data-driven Business Models Enabled by 3D Vision Technology” tutorial at the May 2018 Embedded Vision Summit. This presentation describes which applications are enabled by low-cost 3D vision technology, such as home robotics, smart cities/communities and drones for precision farming, and which business models

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“Balancing Safety, Convenience and Privacy in the Era of Ubiquitous Cameras,” a Presentation from Intel

Algorithms, Intel, Privacy, Security, Sensors and Cameras, Software, Summit 2018, Videos /

Charlotte Dryden, Director of the Visual Computing Developer Solutions team at Intel, presents the “Balancing Safety, Convenience and Privacy in the Era of Ubiquitous Cameras” tutorial at the May 2018 Embedded Vision Summit. Computer vision-enabled cameras are proliferating rapidly and will soon be ubiquitous – in, on and around vehicles, homes, toys, stores, public transit,

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“What is Neuromorphic Event-based Computer Vision? Sensors, Theory and Applications,” a Presentation from Ryad B. Benosman

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

Ryad B. Benosman, Professor at the University of Pittsburgh Medical Center, Carnegie Mellon University and Sorbonne Universitas, presents the “What is Neuromorphic Event-based Computer Vision? Sensors, Theory and Applications” tutorial at the May 2018 Embedded Vision Summit. In this presentation, Benosman introduces neuromorphic, event-based approaches for image sensing and processing. State-of-the-art image sensors suffer from

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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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