Recognition systems have generally treated specular highlights as noise. We show how to use these highlights as a positive source of information that improves recognition of shiny objects. This also enables us to recognize very challenging shiny transparent objects, such as wine glasses. Specifically, we show how to find highlights that are consistent with a hypothesized pose of an object of known 3D shape. We do this using only a qualitative description of highlight formation that is consistent with most models of specular reflection, so no specific knowledge of an object's reflectance properties is needed. We first present a method that finds highlights produced by a dominant compact light source, whose position is roughly known. We then show how to estimate the lighting automatically for objects whose reflection is part specular and part Lambertian. We demonstrate this method for two classes of objects. First, we show that specular information alone can suffice to identify objects with no Lambertian reflectance, such as transparent wine glasses. Second, we use our complete system to recognize shiny objects, such as pottery.
Using specularities for recognition
Proceedings Ninth IEEE International Conference on Computer Vision ; 1512-1519 vol.2
01.01.2003
482638 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Removal of specularities using color and polarization
IEEE | 1993
|Using specularities in comparing 3D models and 2D images
British Library Online Contents | 2008
|Detecting and removing specularities in facial images
British Library Online Contents | 2005
|Specularities on Surfaces with Tangential Hairs or Grooves
British Library Online Contents | 2000
|British Library Conference Proceedings | 2001
|