Moving object detection and image inpainting in street-view imagery

Master Thesis (2018)
Author(s)

M.C. Uittenbogaard (TU Delft - Mechanical Engineering)

Contributor(s)

D.M. Gavrila – Mentor

Clint Sebastian – Mentor

Julien Vijverberg – Mentor

Faculty
Mechanical Engineering
Copyright
© 2018 Ries Uittenbogaard
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Ries Uittenbogaard
Graduation Date
28-09-2018
Awarding Institution
Delft University of Technology
Faculty
Mechanical Engineering
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Abstract

In this thesis, a pipeline is created consisting of two parts. In the first part, the moving objects (cars, cyclists, pedestrians) are detected in street-view imagery using image segmentation neural networks and a LIDAR-based moving object detection approach. In the second part, those moving objects are deleted from the image data and an image inpainting approach is used to inpaint the hole. This is a unique approach in which information from multiple views is used as an input for a Generative Adversarial Network (GAN).

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