Fast 3D imaging using active imaging and an event-camera

Event-cameras ( represent a novel sensing modality for fast detection, imaging, and tracking. They have potential applications in surveillance, automotive, and robotics and microscopy. In contrast to classical cameras, such detectors only record changes in light intensity and do not produce standard images. Thus, they require existing (restoration, detection and tracking, SLAM) methods to be adapted or new, tailored methods to be developed.

In this project, a student will be developing a novel approach to fast 3D imaging using an event-camera coupled with a laser scanner. The main idea is to illuminate the scene with a straight line, scanned across the scene and image its deformation due to the 3D structure of the scene. The 3D information can then be recovered using simple geometric transformation. While this principle has already been demonstrated using classical cameras, it has never been used with an event-camera which can lead to higher resolution and faster 3D reconstruction.

This project involves basic system design (scanning system), experiments (calibration and data collection) and data analysis. Existing reconstruction algorithms will be used at first and this project does not require significant data modelling tasks. The data analysis will primarily be achieved using Matlab but other programming languages can be considered.

Required skills:
-Signal/Image processing
- Experience with Matlab
- Experience C/C++ or python is a plus
- Embedded software preferable

Supervisor name: 
Yoann Altmann
Supervisor and Deputy email addresses:
Project location: 
Earl Mountbatten Building, Riccarton
Deputy name: 
Yvan Petillot