MaDeepStereo

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Deep Stereo

Supervision: Christian Rupprecht, Federico Tombari

In this project we aim at developing a method for learning how to predict stereo disparities from a pair of images. We will start from the analysis of a recently published method (Zbontar and LeCun?, 15), and investigate different aspects aimed at improving this approach in terms of accuracy and efficiency. Another important goal of the project is to experimentally evaluate how learned disparities can deal with noisy images under realistic working conditions.

For further information please contact: Christian Rupprecht

ProjectForm
Title: Deep Stereo
Abstract: In this project we aim at developing a method for learning how to predict stereo disparities from a pair of images. We will start from the analysis of a recently published method (Zbontar and LeCun?, 15), and investigate different aspects aimed at improving this approach in terms of accuracy and efficiency. Another important goal of the project is to experimentally evaluate how learned disparities can deal with noisy images under realistic working conditions.
Student: Christoph Kick
Director: Prof. Nassir Navab
Supervisor: Christian Rupprecht, Federico Tombari
Type: Bachelor Thesis
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Status: finished
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Edit | Attach | Refresh | Diffs | More | Revision r1.4 - 29 Aug 2016 - 07:57 - ChristianRupprecht