Entire Reflective Object Surface Structure Understanding
Author(s) -
Qinglin Lu,
Olivier Laligant,
Éric Fauvet,
Anastasia Zakharova
Publication year - 2015
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.29.116
Subject(s) - computer science , object (grammar) , surface (topology) , artificial intelligence , computer vision , geometry , mathematics
Reflection from reflective surface has been a long-standing problem for object recognition, it brings negative effects on object’s color, texture and structural information. Because of that, it is not a trivial task to recognize the surface structure affected by the reflection, especially when the object is entirely reflective. Most of the time, reflection is considered as noise. In this paper, we propose a novel method for entire reflective object sub-segmentation by transforming the reflection motion into object surface label. Instead of considering the reflection as noise, our approach takes reflection as an advantage for understanding the surface structure of the entire reflective objects. The experimental results on specular and transparent objects show that the surface structures of the reflective objects can be revealed and the segmentation based on the surface structure outperforms the approaches in literature.
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