• DocumentCode
    2742167
  • Title

    Investigating the Effect of Illumination and Viewpoint on Image Recognisability

  • Author

    Bamunusinghe, Jeewanee ; Alahakoon, Damminda

  • Author_Institution
    Clayton Sch. of Inf. Technol., Monash Univ., Melbourne, VIC
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    502
  • Lastpage
    506
  • Abstract
    View point and illumination are two main factors that make difficult for machines to compare the two instances of the same object. Therefore investigating the effect of illumination and viewpoint on images recognisability is crucial. How ever the goal of our final project is to build a system which can achieve understanding from images. Thus this paper is focusing on investigating how an artificial system can separate the images based on view point and illumination. The technique we used in this experiment is image clustering. The growing self organizing map was used as the clustering tool as it has many advantages over many other clustering tools as well as the ability to generate hierarchical clustering. The experiments were carried out using a well known face image database called ´Yale face database B´. The results of this experiment showed the potential of using growing self organizing map to separate objects with different effects into different groups.
  • Keywords
    face recognition; self-organising feature maps; visual databases; Yale face database; artificial system; clustering tools; hierarchical clustering; image clustering; image recognisability; self organizing map; Defense industry; Humans; Image databases; Image recognition; Information technology; Lighting; Organizing; Streaming media; Temporal lobe; Visual perception; growing self organizing map; image clustering; visual perception;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation for Sustainability, 2008. ICIAFS 2008. 4th International Conference on
  • Conference_Location
    Colombo
  • Print_ISBN
    978-1-4244-2899-1
  • Electronic_ISBN
    978-1-4244-2900-4
  • Type

    conf

  • DOI
    10.1109/ICIAFS.2008.4783984
  • Filename
    4783984