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 […]
“Visual-Inertial Tracking for AR and VR,” a Presentation from Meta Read More +
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
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
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
Rudy Burger, Managing Partner at Woodside Capital Partners, presents the “What’s Hot? The M&A and Funding Landscape for Machine Vision Companies” tutorial at the May 2018 Embedded Vision Summit. The six primary markets driving computer vision are automotive, sports and entertainment, consumer and mobile, robotics and machine vision, medical, and security and surveillance. This presentation
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
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
Devi Parikh, Research Scientist at Facebook AI Research (FAIR) and Assistant Professor at Georgia Tech, presents the “Words, Pictures, and Common Sense: Visual Question Answering” tutorial at the May 2018 Embedded Vision Summit. Wouldn’t it be nice if machines could understand content in images and communicate this understanding as effectively as humans? Such technology would
Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for
OpenVX Implementations Deliver Robust Computer Vision Applications Read More +
Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for
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