Student research opportunities
Image Segmentation and Scene Understanding
Project Code: CECS_817
This project is available at the following levels:
Summer Scholar
Please note that this project is only for undergraduate students.
Keywords:
computer vision, machine learning
Supervisor:
Dr Stephen GouldOutline:
Semantic segmentation is the task of automatically breaking an image into regions and labelling each region with a semantic class label. For example, an image of a person riding a bike could be segmented into three regions: (i) the person, (ii) the bike, and (iii) the background.
In this project you will work on cutting-edge computer vision and machine learning algorithms to enhance the state-of-the-art in semantic segmentation.
Goals of this project
Develop algorithms and software for semantic segmentation. Work done in this project could lead to a scientific publication in a top quality conference or journal.
Requirements/Prerequisites
Strong programming skills in C++ and Matlab are required. A background in computer vision and machine learning is desirable.
Student Gain
Experience it cutting-edge research in machine learning and computer vision.
Background Literature
http://users.cecs.anu.edu.au/~sgould/papers/cvpr12-multiSeg.pdf
http://users.cecs.anu.edu.au/~sgould/papers/iccv09-sceneDecomposition.pdf
