• DocumentCode
    597963
  • Title

    Salient view selection based on sparse representation

  • Author

    Yi-Chen Chen ; Patel, Vishal M. ; Chellappa, Rama ; Phillips, Jonathon

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    649
  • Lastpage
    652
  • Abstract
    A sparse representation-based approach is proposed to find the salient views of 3D objects. Under the assumption that a meaningful object can appear in several perceptible views, we build the object´s approximate convex shape that exhibits these apparent views. The salient views are categorized into two groups. The first are boundary representative views that have several visible sides and object surfaces attractive to human perceivers. The second are side representative views that best represent views from sides of the approximating convex shape. The side representative views are class-specific views that possess the most representative power compared to other within-class views. Using the concept of characteristic view class, we first present a sparse representation-based approach for estimating the boundary representative views. With the estimated boundaries, we determine the side representative view(s) based on a minimum reconstruction error.
  • Keywords
    compressed sensing; image representation; 3D objects; approximate convex shape; boundary representative view estimation; boundary representative views; convex shape approximation; human perceivers; object surfaces; reconstruction error; salient view selection; salient views; sparse representation-based approach; Abstracts; Clocks; Salient view; characteristic view class; compressive sensing; sparse representation; view geometry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6466943
  • Filename
    6466943