Classification of photometric factors based on photometric linearization

Yasuhiro Mukaigawa, Yasunori Ishii, Takeshi Shakunaga

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)


We propose a new method for classification of photometric factors, such as diffuse reflection, specular reflection, attached shadow, and cast shadow. For analyzing real images, we utilize the photometric linearization method which was originally proposed for image synthesis. First, we show that each pixel can be photometrically classified by the simple comparison of the pixel intensity. Our classification algorithm requires neither 3D shape information nor color information of the scene. Then, we show that the accuracy of the photometric linearization can be improved by introducing a new classification-based criterion to the linearization process. Experimental results show that photometric factors can be correctly classified without any special device.

Original languageEnglish
Pages (from-to)613-622
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3852 LNCS
Publication statusPublished - Jun 14 2006
Event7th Asian Conference on Computer Vision, ACCV 2006 - Hyderabad, India
Duration: Jan 13 2006Jan 16 2006

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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