ECE516: Intelligent Image Processing

Schedule		Labs		Philosophy		Opportunities		20-Year ECE516 History

Instructor: Prof. Steve Mann (bio).
Teaching Assistants:
Head TA: Mete Isiksalan (mete.isiksalan@mail.utoronto.ca);
Yuntao Cai (yuntao.cai@mail.utoronto.ca).

This website was hand-written, using just a text-editor, like I did with my first website at MIT in 1993 (world's first photo, video, streaming site). Enjoy the Amish-like tradition of simplicity and reliability!

Subscribe to Prof. Steve Mann's YouTube channel (hydraulist), which has a ECE516 playlist for some previous lectures where you can look at recorded lectures made during the pandemic years. You might also enjoy looking at the eXtended metaVerse (XV = beyond the metaverse) playlist also.

You can also subscribe to the older 2021 channel as well, if you like: Previous (pre-2021) YouTube channel.

Prof. Steve Mann (bio), together with a team of super-smart TAs who all know the material really well: Mete Isiksala and Yuntao Tony Cai and other advisors (we've also got some of the world's leading experts as advisors) are ready to make your learning experience awesome! Connections to MIT, Stanford University, Silicon Valley, California, and Shenzhen

In this course [link to syllabus for 2023 (last year's syllabus); this year's is coming soon!] you will learn how to invent, design, build, and deeply understand:

• Cameras and imaging systems, starting from the very simplest form of camera and then advancing from there;
• Photoquantigraphic image sensing systems based on comparametic sensing (comparametric equations);
• Photocell Experiment and Comperiodicity (fractal periodicity = fractal ambiguity) in comparametric sensing (ref.)
• HDR (High Dynamic Range) computer vision systems;
• Panoramic computer vision systems ("Video Orbits");
• Wearable computing by building an active vision system for the blind, using a mathematical transform that has built-in machine learning;
• Vision-based Human/Machine learning and Extended Intelligence;
• VR/AR (Virtual/All Reality) (see our AWE 2018 paper), XR (eXtended Reality), metaverse (metaverse.ieee.org), and beyond-metaverse = XV (eXtendiVerse); see also a short (6-minute) video intro to Beyond the Metaverse (link);
• Vision systems for autonomous electric vehicles;
• Sensing, meta-sensing, smart buildings, smart cities, etc.;
• Health and wellbeing, wearables: ultrasound heart sensing;

You will learn from the world's leading experts in imaging, sensing, meta-sensing (metaveillance, metavision, metaverse, https://metaverse.ieee.org/ and beyond metaverse), and computer vision, both passive (e.g. cameras) and active (e.g. sonar, radar, lidar, etc.), while deeply understanding computer vision and machine learning from first principles (mathematics and fundamental physics).

What you learn in this course applies at any physical scale from wearables to smart cars to smart buildings (clothing is a building built for a single occupant), to smart cities, and from vision-based model craft (model cars, drones, etc.) to full size self-driven transportation systems.

You might like to subscribe to my YouTube, "hydraulist" and watch the ECE516 playlist and learn the fundamental scientific and mathematical principles that gave rise to the extended metaverse and will guide you to inventing the future.

This website was hand-made without the use of any software... [Consider free and open-source ... link].

We're hoping that the most talenented students in this course will help us teach the course while you learn it! Become a "deputy student", meaning that you'll have fun and get additional bonus marks plus an offer for a summer position plus we can help get you into MIT (Prof. Mann's alma mater) or Stanford (Prof. Mann, Visiting Full Professor...), connections to Silicon Valley, Shenzhen, etc..

Please be sure to read this excellent safety manual written by our very own Afshin Poraria.

Copyleft 2023

This work is licensed under "Against DRM 2.0".