Visual Computing

About the course

Visual Computing concerns the analysis and synthesis of images and videos. Understanding images is an AI problem, and the field has grown substantially because of the confluence of big data, powerful hardware, and machine learning. Applications are everywhere: face detection in digital cameras, optical character recognition for text translation, diet apps in smartphones, etc. 
 
In this course, you will learn the basics of visual computing, including: image processing & synthesis, object recognition. You will learn through lectures and hands-on sessions, culminating in a final group project. 
 
At the end of the course, you will: 

Understand the basics of visual computing
Use Python and OpenCV to perform image processing and analysis
Complete a non-trivial but interesting image analysis project

Prerequisites:
Open to Year 3 or above students

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About the Lecturer

Terence Sim

Department of Computer Science, School of Computing, NUS

D r. Terence Sim is an Associate Professor and Assistant Dean at the NUS School of Computing. Dr. Sim actively conducts research in biometrics and computer vision, employing AI and Machine Learning to create powerful new algorithms that analyze and synthesize images. He is also a Principal Investigator at NCRiPT, a strategic research center at NUS that develops privacy-preserving technologies. His current projects include understanding the privacy of gait biometrics, protecting facial images from machine spying, as well as detecting fake videos. 
 
Dr. Sim has published over 100 papers in top international journals and conferences. He obtained his SB from the Massachusetts Institute of Technology, MSCS from Stanford University, and PhD from Carnegie Mellon University. He is also an award-winning teacher, and an engaging speaker.

Past Projects