Machine Vision and Applications

, Volume 23, Issue 1, pp 65–77 | Cite as

Disparity disambiguation by fusion of signal- and symbolic-level information

  • Jarno Ralli
  • Javier Díaz
  • Sinan Kalkan
  • Norbert Krüger
  • Eduardo Ros
Original Paper

Abstract

We describe a method for resolving ambiguities in low-level disparity calculations in a stereo-vision scheme by using a recurrent mechanism that we call signal-symbol loop. Due to the local nature of low-level processing it is not always possible to estimate the correct disparity values produced at this level. Symbolic abstraction of the signal produces robust, high confidence, multimodal image features which can be used to interpret the scene more accurately and therefore disambiguate low-level interpretations by biasing the correct disparity. The fusion process is capable of producing more accurate dense disparity maps than the low- and symbolic-level algorithms can produce independently. Therefore we describe an efficient fusion scheme that allows symbolic- and low-level cues to complement each other, resulting in a more accurate and dense disparity representation of the scene.

Keywords

Disparity fusion Feed-back loop Disparity disambiguation Low- and symbolic-level fusion Signal-symbol loop 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jarno Ralli
    • 1
  • Javier Díaz
    • 1
  • Sinan Kalkan
    • 2
  • Norbert Krüger
    • 3
  • Eduardo Ros
    • 1
  1. 1.Departamento de Arquitectura y Tecnología de Computadores, Escuela Técnica Superior de Ingeniería Informatica y de TelecomunicacíonUniversidad de GranadaGranadaSpain
  2. 2.KOVAN Research Lab, Department of Computer EngineeringMiddle East Technical UniversityAnkaraTurkey
  3. 3.Cognitive Vision Lab, The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkOdense MDenmark

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