Efficient Multi-frame Obstruction Removal

Modern mobile phones have become the dominant photography device in recent years. However, their users are often not professional photographers. Thus, they lack the skills of choosing proper lighting, proper shot framing, and proper settings on the camera. In particular, photographs are often taken in unfavourable conditions where the scene of interest is obstructed by a fence or a window. We would like to remove such obstruction automatically. Capturing scenes from multiple viewpoints, not only helps to identify the obstruction better, but also helps in removing it. There are existing multi-frame obstruction removal methods, but they are too computationally intensive. This project will focus on a multi-frame obstruction removal approach that is accurate while keeping in mind the computational constraints that would enable mobile deployment. This is of major interest to Samsung as one of the leaders in the mobile phone industry.

Faculty Supervisor:

Kiriakos Neoklis Kutulakos

Student:

Partner:

Samsung Electronics Canada

Discipline:

Computer science

Sector:

Manufacturing

University:

University of Toronto

Program: