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3D reconstruction with event cameras
This project will explore the application of event camera setups for scene reconstruction.
Accurate and efficient reconstructions using event-camera setups is still an unexplored topic. This project will focus on solving the problem of 3D reconstruction using active perception with event cameras​.
Keywords: Event camera, computer vision, Depth, 3D reconstruction
Event cameras are bio-inspired sensors that offer several advantages, such as low
latency, high-speed and high dynamic range, to tackle challenging scenarios in
computer vision.
Research on structure from motion and multi-view stereo with images has produced
many compelling results, in particular accurate camera tracking and sparse
reconstruction. Active sensors with standard cameras like Kinect have been used for
dense scene reconstructions.
Accurate and efficient reconstructions using event-camera setups is still an unexplored
topic. This project will focus on solving the problem of 3D reconstruction using active
perception with event cameras​ .
Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. Research on structure from motion and multi-view stereo with images has produced many compelling results, in particular accurate camera tracking and sparse reconstruction. Active sensors with standard cameras like Kinect have been used for dense scene reconstructions. Accurate and efficient reconstructions using event-camera setups is still an unexplored topic. This project will focus on solving the problem of 3D reconstruction using active perception with event cameras​ .
The goal is to develop a system for accurate mapping of complex and arbitrary scenes using depth acquired by an event camera setup.
We seek a highly motivated student with the following minimum qualifications:
- Excellent coding skills in Python and C++
- At least one course in computer vision (multiple view geometry)
- Strong work ethic
- Excellent communication and teamwork skills
Preferred qualifications:
- Experience with machine learning
Contact for more details.
The goal is to develop a system for accurate mapping of complex and arbitrary scenes using depth acquired by an event camera setup.
We seek a highly motivated student with the following minimum qualifications: - Excellent coding skills in Python and C++ - At least one course in computer vision (multiple view geometry) - Strong work ethic - Excellent communication and teamwork skills
Preferred qualifications: - Experience with machine learning