Computer Vision 1 - Spring 2019

for MSc in Artificial Intelligence at University of Amsterdam
This is an archived version for the class that happened in Spring 2019

About

Digital cameras, ubiquitously present in the form of webcams, cell phones, and professional cameras, have provided enormous streams of data and means for communication and interaction. In this course, image understanding is addressed with the focus on core vision tasks of scene understanding and object recognition.

A broad range of techniques are studied on how computers can understand the visual world of humans including image formation and filtering, features (color and shape invariants, interest point detectors, descriptors, SIFT, HoG), visual information representation (vector space, statistical models, bag-of-words), learning and classification (nearest neighbor, kernel density estimation, SVM), dimension reduction (PCA, LDA and SVD), object detection and classification, object tracking (mean-shift, Kalman), and user interaction (active learning).

The class is taught by Professor Theo Gevers, Assistant Professor Thomas Mensink and Dr. Amir Ghodrati. The teaching assistant team includes Anil Baslamisli, Hoang-An Le, Hanan ElNaghy, Berkay Kicanaoglu, William Thong, Mert Kilickaya, Wei Zeng, Jian Han, and Yunlu Chen.

Instructors

Teaching Assistants

Schedule

Following is the tentative schedule and some practical information. Please keep an eye on Datanose, Canvas, and Piazza for up-to-date changes.

Lecture 1: Introduction

SP C0.05 | 3pm-5pm | February 04, 2019

Warm-up: MATLAB tutorial

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | February 07, 2019

Lecture 2: Image Formation

SP C1.110 | 5pm-7pm | February 11, 2019

Exercise 1

SP C1.110 | 5pm-7pm | February 12, 2019

Lab1: Photometric Stereo and Color

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | February 14, 2019

Lecture 3: Color and Image Processing

SP C1.110 | 11am-1pm | February 18, 2019

Exercise 2

SP C0.05 | 1pm-3pm | February 20, 2019

Lab2: Neighborhood Processing: Gabor and Gaussian Filters

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | February 21, 2019

Lecture 4: Features, Detections, Motions and Classification

SP H0.08 | 3pm-5pm | February 25, 2019

Exercise 3

SP C1.110 | 1pm-3pm | February 27, 2019

Lab3: Optical Flow and Harris Corner Detector

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | February 28, 2019

Lecture 5: Object recognition: BoW and ConvNets

SP C0.05 | 5pm-7pm | March 04, 2019

Exercise 4

SP C0.05 | 1pm-3pm | March 06, 2019

Lab4: Image Alignment and Stitching

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm & 1pm-3pm | March 07, 2019

Lecture 6: Object Detection, Stereo and 3D Reconstruction

SP C0.05 | 5pm-7pm | March 11, 2019

Exercise 5

SP C0.05 | 5pm-7pm | March 13, 2019

Project: Building an Object Classification System | Part 1: Bag of Words

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | March 14, 2019

Lecture 7: Applications

SP H0.08 | 3pm-5pm | March 18, 2019

Exercise 6

SP C0.05 | 5pm-7pm | March 20, 2019

Project: Building an Object Classification System | Part 2: Convolution Neural Networks

SP G0.23-G.025 & SP F2.04 11am-1pm | SP B0.203 & SP D1.110 1pm-3pm | March 21, 2019

Contact

The good place to ask questions is Piazza