Dense Depth from Event Focal Stack
Journal:
arXiv
Published Date:
Dec 11, 2024
Abstract
We propose a method for dense depth estimation from an event stream generated
when sweeping the focal plane of the driving lens attached to an event camera.
In this method, a depth map is inferred from an ``event focal stack'' composed
of the event stream using a convolutional neural network trained with
synthesized event focal stacks. The synthesized event stream is created from a
focal stack generated by Blender for any arbitrary 3D scene. This allows for
training on scenes with diverse structures. Additionally, we explored methods
to eliminate the domain gap between real event streams and synthetic event
streams. Our method demonstrates superior performance over a depth-from-defocus
method in the image domain on synthetic and real datasets.
