/computer-vision

Computer Vision Courses 2017/2018 - MSc Artificial Intelligence @ UvA

Primary LanguageCMIT LicenseMIT

Computer Vision

License

Description

Labs and presentation of the Computer Vision 1 and Computer Vision 2 courses of the MSc in Artificial Intelligence at the University of Amsterdam. Labs in Computer Vision 1 are joint work with Gabriele Bani. For Computer Vision 2, work was done together with Gabriele Bani and Andreas Hadjipieri.

Computer Vision 1

Labs

Photometric Stereo & Color

Problem statement and Solution


Face heightmap for different configurations

Neighborhood Processing & Filters

Problem statement and Solution


Gabor segmentation applied to images with and without smoothing

Harris Corner Detector & Optical Flow

Problem statement and Solution


Corner detection with varying sigma and threshold


Feature Tracking

Image Alignment and Stitching

Problem statement and Solution


Original and stitched bus images

Final Project: Bag-of-Words based Image Classification (part 1) and Convolutional Neural Networks for Image Classification (part 2)

Problem statement for part 1, Problem statement for part 2 and Solution


Performance of Bag-of-Words model


T-SNE Visualizations of CNN model features


Dependencies

  • Matlab 2017a

Computer Vision 2

Labs

Iterative Closest Point

Problem statement and Solution


Result of Scene Merging

Structure from Motion

Problem statement and Solution

Feature Matching Point-View Matrices


Result of the Structure from Motion algorithm

3D Mesh Generation and Texturing

Problem statement and Solution


Reconstruction using Poisson with texture


Dependencies

To run each file, take a look at following files:


Paper Presentation

Paper Learning to Reason: End-to-End Module Networks for Visual Question Answering by Hu et al. is trying to tackle problem of question answering. As questions are inherently compositional, authors argue that they can be answered easier if decomposed into modular sub-problems. They propose End-to-End Module Networks, which learn to reason by directly predicting instance-specific network layouts without the aid of a parser.

Slides presenting paper can be found here.

Copyright

Copyright © 2017-2018 Andrii Skliar.

This project is distributed under the MIT license. This was developed as part of the courses Computer Vision 1 and Computer Vision 2 taught by Theo Gevers at the University of Amsterdam. Please follow the UvA regulations governing Fraud and Plagiarism in case you are a student.