Event-based Unsupervised Learning of Epipolar Geometry

The stereo matching problem is a well-known bottleneck in stereo-vision. Event-based stereo matching approaches make explicit use of precise interocular temporal coincidences. This computationally expensive process can be greatly improved by imposing constraints from the geometry of the stereo setup. However, obtaining this geometry information requires precise camera calibration procedures, which are time consuming and prone to errors. In this discussion group we will investigate the use of event-based learning methods for estimating the stereo setup geometry without requiring prior knowledge about sensors' pose.

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Day Time Location
Wed, 25.04.2018 22:00 - 23:00 Lobby


Nicoletta Risi


Chiara Bartolozzi
Laurent Dardelet
Lukas Everding
Arren Glover
Álvaro González
Germain Haessig
Massimiliano Iacono
jacques kaiser
Dongchen Liang
James O'Keeffe
Nicoletta Risi
Yulia Sandamirskaya
Sergio Solinas
Lea Steffen
Michiel Van Dyck
Tetsuya Yagi
Guido Zarrella