eprintid: 27652
rev_number: 34
eprint_status: archive
userid: 4906
dir: disk0/00/02/76/52
datestamp: 2020-01-14 11:06:11
lastmod: 2020-02-03 13:44:55
status_changed: 2020-01-14 11:06:11
type: doctoralThesis
metadata_visibility: show
creators_name: Güssefeld, Burkhard
title: Acquisition, Modeling, and Augmentation of Reflectance for Synthetic Optical Flow Reference Data
subjects: 004
subjects: 500
divisions: 110001
divisions: 708000
divisions: 708070
adv_faculty: af-11
keywords: Referenzdaten, Ground Truth, Reflektanzfeld Messung, Reflektanz Modelierung, Augmentierte Realität
cterms_swd: Computergrafik
cterms_swd: Bidirektionale Reflektanzverteilungsfunktion
cterms_swd: Optische Messung
cterms_swd: Optischer Fluss
abstract: This thesis is concerned with the acquisition, modeling, and augmentation of material reflectance to simulate high-fidelity synthetic data for computer vision tasks. 
The topic is covered in three chapters: I commence with exploring the upper limits of reflectance acquisition. 
I analyze state-of-the-art BTF reflectance field renderings and show that they can be applied to optical flow performance analysis with closely matching performance to real-world images. 
Next, I present two methods for fitting efficient BRDF reflectance models to measured BTF data. 
Both methods combined retain all relevant reflectance information as well as the surface normal details on a pixel level. 
I further show that the resulting synthesized images are suited for optical flow performance analysis, with a virtually identical performance for all material types. 
Finally, I present a novel method for augmenting real-world datasets with physically plausible precipitation effects, including ground surface wetting, water droplets on the windshield, and water spray and mists. 
This is achieved by projecting the realworld image data onto a reconstructed virtual scene, manipulating the scene and the surface reflectance, and performing unbiased light transport simulation of the precipitation effects.
date: 2020
id_scheme: DOI
id_number: 10.11588/heidok.00027652
ppn_swb: 168732252X
own_urn: urn:nbn:de:bsz:16-heidok-276527
date_accepted: 2019-12-19
advisor: HASH(0x556120c03e40)
language: eng
bibsort: GUSSEFELDBACQUISITIO2020
full_text_status: public
place_of_pub: Heidelberg
citation:   Güssefeld, Burkhard  (2020) Acquisition, Modeling, and Augmentation of Reflectance for Synthetic Optical Flow Reference Data.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/27652/1/document.pdf