Link for Live Seminar

Link for Recorded seminars – 2022/2023 school year

Abstract:

I will present a bio-inspired fish simulation platform, which we call “Foids”, to generate realistic synthetic datasets for an use in computer vision algorithm training. This is a first-of-its-kind synthetic dataset platform for fish, which generates all the 3D scenes just with a simulation. One of the major challenges in deep learning based computer vision is the preparation of the annotated dataset. It is already hard to collect a good quality video dataset with enough variations; moreover, it is a painful process to annotate a sufficiently large video dataset frame by frame. This is especially true when it comes to a fish dataset because it is difficult to set up a camera underwater and the number of fish (target objects) in the scene can range up to 30,000 in a fish cage on a fish farm. All of these fish need to be annotated with labels such as a bounding box or silhouette, which can take hours to complete manually, even for only a few minutes of video. We solve this challenge by introducing a realistic synthetic dataset generation platform that incorporates details of biology and ecology studied in the aquaculture field. Because it is a simulated scene, it is easy to generate the scene data with annotation labels from the 3D mesh geometry data and transformation matrix. To this end, we develop an automated fish counting system utilizing the part of synthetic dataset that shows comparable counting accuracy to human eyes, which reduces the time compared to the manual process, and reduces physical injuries sustained by the fish.

Bio: Masaki Nakada obtained a master degree in physics at Waseda University in Japan. Then, he finished PhD in computer science at UCLA and worked as a postdoc for another year, where he published a series of scientific papers. (https://www.masakinakada.com/) He devoted more than 10 years in the research of artificial life, specifically in the area of biomechanical human simulation with musculoskeletal models, neuromuscular controllers, and biomimetic vision. Previously, he worked for Intel as a software engineer. He received  MIT Technology Review Innovator Award Under 35, Forbes Next 1000, Institute for Digital Research and Education Postdoctoral Scholar Award, Siggraph Thesis Fast Forward Honorable mention, TEEC Cup North American Entrepreneurship Competition in Silicon Valley, Japan Student Services Organization Fellowship, Rotary Ambassadorial Fellowship, Itoh Foundation Fellowship, Entrepreneurship Foundation Fellowship, Aoi Foundation Fellowship and winner of several Startup business competition & hackathons. He founded NeuralX, Inc (https://www.neuralx.ai/) in 2019 based on the IP he has developed over the decade of research. The company provides an interactive online fitness service Presence.fit (https://www.presence.fit/), where it combines the power of human instructor and motion analytics AI, which enables them to provide highly interactive online fitness experience.