We present MLIC-Synthetizer, a Blender plugin specifically designed for the generation of a syntethic Multi-Light Image Collection using physically-based rendering. This tool makes easy to generate large amount of test data that can be useful for Photometric Stereo algorithms evaluation, validation of Reflectance Transformation Imaging calibration and processing method, relighting methods and more. Multi-pass rendering allows the generation of images with associated shadows and specularity ground truth maps, ground truth normals and material segmentation masks. Furthermore loops on material parameters allows the automatic generation of datasets with pre-defined material parameters ranges that can be used to train robust learning-based algorithms for 3D reconstruction, relight and material segmentation.

MLIC-Synthetizer: a Synthetic Multi-Light Image Collection Generator

Tinsae Gebrechristos Dulecha;Andrea Giachetti
2019-01-01

Abstract

We present MLIC-Synthetizer, a Blender plugin specifically designed for the generation of a syntethic Multi-Light Image Collection using physically-based rendering. This tool makes easy to generate large amount of test data that can be useful for Photometric Stereo algorithms evaluation, validation of Reflectance Transformation Imaging calibration and processing method, relighting methods and more. Multi-pass rendering allows the generation of images with associated shadows and specularity ground truth maps, ground truth normals and material segmentation masks. Furthermore loops on material parameters allows the automatic generation of datasets with pre-defined material parameters ranges that can be used to train robust learning-based algorithms for 3D reconstruction, relight and material segmentation.
2019
MLIC-synthesizer, Multi-light Image Collections, MLIC
File in questo prodotto:
File Dimensione Formato  
STAG2019.pdf

accesso aperto

Licenza: Dominio pubblico
Dimensione 854.41 kB
Formato Adobe PDF
854.41 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1008326
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact