Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes

Marie-Anne Bauda (1, 2) , Sylvie Chambon (3, 4) , Pierre Gurdjos (3, 5) , Vincent Charvillat (3, 4)

1 IRIT-VORTEX - Visual Objects from Reality To Expression
2 Imajing Sas
3 IRIT-REVA - Real Expression Artificial Life
4 Toulouse INP - Institut National Polytechnique (Toulouse)
5 CNRS - Centre National de la Recherche Scientifique

In the context of semantic segmentation of urban scenes, the calibrated multi-views and the flatness assumption are commonly used to estimate a warped image based on the homography estimation. In order to classify planar and non-planar areas, we propose an evaluation protocol that compares several Image Quality Assessments (IQA) between a reference zone and its warped zone. We show that cosine angle distance-based measures are more efficient than euclidean distance-based for the planar/non-planar classification and that the Universal Quality Image (UQI) measure outperforms the other evaluated measures.

Mots clés: Image quality assessment; Urban scene; Planar classification; Image segmentation

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]; Traitement du signal et de l'image [eess.SP]; Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Intelligence artificielle [cs.AI]

Marie-Anne Bauda, Sylvie Chambon, Pierre Gurdjos, Vincent Charvillat. Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes. 4th International Conférence on Pattern Recognition Applications and Methods (ICPRAM 2015), Jan 2015, Lisbonne, Portugal. pp.328-333, ⟨10.5220/0005222603280333⟩. ⟨hal-01390843⟩