Chenliang Xu

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Spring 2019 - CSC 249/449: Machine Vision

Basic Information

Instructor: Prof. Chenliang Xu
Instructor's Office Hours: TR 14:00-15:00, 3005 Wegmans

TA and TA's Office Hours:

Meet Time/Location: TR 12:30-13:45 in Goergen 101

Syllabus: pdf

Dicussion: This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. Find our class page here.


Description

Fundamentals of computer vision, including image formation, elements of human vision, low-level image processing, and pattern recognition techniques. Advanced topics include modern visual features, graphical models, model-based and data-driven approaches, and contextual inference, as well as illustrative examples of successes and challenges in applications. CSC 449, a graduate-level course, requires additional readings and assignments.

Rough Topic Outline
Prerequisites

Basic knowledge of probability and linear algebra; data structures, algorithms; programming experience. For assignments and projects, the most common programming language is Python.


Schedule

This is a tentative schedule of the course and will be modified over the semester.
Course materials will be posted on Blackboard.

Dates Tuesday (T) Thursday (R) HW Due Project
1/17 No Class: Before Term Introduction
1/22,24 Linear Filtering and Image Transforms Edges T: 1 Out
1/29,31 Corners SIFT and Feature Matching Sat: 1 Due (ext.)
2/5,7 Neural Network and Backpropagation CNN and Feature Visualization Tue: 2 Out
2/12,14 Fitting I Fitting II and Alignment Sat: 2 Due
2/19,21 Dense Motion Estimate Case Study: Object Tracking Tue: 2 Due (ext.)
Tue: 3 Out
2/26,28 Segmentation I Segmentation II
3/5,7 RNN and Image Captioning Cancelled Sat: 3 Due
3/12,14 No Class: Spring Break No Class: Spring Break Sat: 3 Due (ext.)
3/19,21 Case Study: Image Captioning Midterm Exam Tue: 4 Out
3/26,28 Advanced CNNs I Advanced CNNs II Sat: 4 Due Train/Val Out
4/2,4 Object Recognition I Object Recognition II Tue: 5 Out
4/9,11 GAN and Image Synthesizing Visual and Sound
4/16,18 Face Recognition, Style Transfer Video Analysis Tue: Test Out
4/23,25 Camera Models, Light and Color Stereo Vision Tue: Submit Due
4/30 Project Presentation No Class: Term Finished Sat: 5 Due

Information Flow

This course primarily uses Blackboard to manage information flow. The course ID is CSC249.2019SPRING.52339. It will be used for announcements, posting lecture notes and assignments, discussions and submitting work. The instructor's course website contains an outline of course schedule, which will be updated over the term, and also serves for the purpose of a syllabus.