Do You See What I See: Using AR and AI
Do You See What I See: Using AR and AI

Abstract: 

Welcome to the world of augmented reality and artificial intelligence! In this workshop, we demonstrate AR and AI via hands-on exercises where you will interact with your augmented world. We describe some of the novel applications of AR+AI, their limitations, and social impacts amplified by the COVID-19 pandemic. We leave attendees armed with code, inspiration and ethical considerations for future projects.
In this workshop, you will build an application where: you will take your own snapshot using your webcam and use deep learning to augment your background; you will use deep learning again to perform pose estimation in your augmented world. We will discuss ethical challenges associated with using deep learning and provide resources and guidance on this topic.
In deep learning, we will focus on two techniques: keypoint estimation using a deep neural network, and segmentation. Keypoint estimation recognizes specific points in an image – for example, the locations of joints on the body. Image segmentation separates parts of an image, pixel-by-pixel. For example, segmentation can be used to identify the background pixels in an image.
We will set you up for success to take on challenging projects in this domain. A clear and precise instruction sheet will guide you through exercises ranging from beginner to intermediate level. This workshop is highly interactive with hands-on exercises in which you will incrementally build the pieces of an AR+AI application and test it out. The presentation that accompanies the exercises demonstrates how powerful applications ranging from entertainment to healthcare can be built using the same components that we taught.

Bio: 

Louvere Walker-Hannon is a MathWorks Senior Application Engineer, who provides direction and recommendations on technical workflows for various applications. Specifically, she assists with the following topics image processing, computer vision, machine learning, deep learning, geospatial analysis, and data analytics when discussing technical workflows. She has a bachelor’s degree in Biomedical Engineering and a master’s degree in Geographic Information Technology with a specialization in Remote Sensing. Louvere has worked in three different engineering roles throughout her 20-year career while at MathWorks. She was also a Program Presenter; in this role she was the lead educator of STEM topics for Cahners ComputerPlace within the Boston Museum of Science. A prominent theme in her career is communication of technical concepts to various audiences and being involved with STEM education.

Louvere is a member of the Society of Women Engineers (SWE), the National Society of Black Engineers (NSBE), the Society of Hispanic Professional Engineers (SHPE), and other organizations. She has a long history of serving as a STEM mentor. Louvere volunteers with Black Girls Code and the Society of Women Engineers. She is a Curriculum Lead for the Boston Chapter of Black Girls CODE, a Co-Lead of the SWE Latinos Affinity Group, and a Society Engagement Lead for the SWE African American Affinity Group. Louvere has presented and continues to present at several STEM related conferences on various topics. She presented her work on a Natural Language Processing application at the 100th American Meteorological Society in January 2020 and at the American Association of Geographers (AAG) virtual conference in April 2020. She presented content on Augmented Reality, Artificial Intelligence, and their challenges at the virtual Grace Hopper Celebration in October 2020. She served as one of the Virtual Chairs for the thirty-seventh International Conference on Machine Learning (ICML) in July 2020 and thirty-fourth conference on Neural Information Processing Systems (NeurIPS) which occurs in December 2020. Louvere is scheduled to serve as one of the MeetUp Chairs for the upcoming thirty-fifth conference on Neural Information Processing Systems (NeurIPS) in 2021. She is helping her company begin an initiative regarding STEM Outreach with a DEI focus.

Open Data Science

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