Improving the impression of depth perception

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  • Haider Easa

    Research areas

  • PhD, School of Computer Science

Abstract

Computing and visual display technologies have made great advances in the last few decades in terms of the interface between man and machine. Many computer applications today make use of 3D interactive computer graphics. Ocular depth is perceived when our visual system combines various different sources of information, which are normally called depth cues, around a scene. This information plays an important role in our life. For example, receiving accurate information about the depth of a scene will save time and effort to a surgeon when performing a surgical operation. The main aim of the dissertation is to improve the impression of depth perception when visualise a multiple-layered computer-generated imagery (CGI). Three experiments were achieved: (1) to investigate which monocular cue provides a better impression of depth when other cues are not available, (2) to perform an evaluation to find which type of translucency among the two common types has a stronger effect on the depth perception, and (3) to study whether the shape of an incision made on the outer layer of a multiple-layered image would have an influence on depth perception. The outcomes of the study were promising. The results of the first experiment demonstrated that brightness, contrast and relative size cues having better impression of depth than other monocular cues. According to the results of the second experiments, we were unable to decide which type of translucency had a stronger effect on depth impression. It showed that there is no statistically significant difference between the two types. In conclusion, the consequences of the third experiment confirmed that the shape of an incision, made on the outer layer, influences the depth perception.

Details

Original languageEnglish
Awarding Institution
Supervisors/Advisors
  • Ik Soo Lim (Supervisor)
Thesis sponsors
  • Iraqi Ministry of Higher Education and scientific research
Award dateJan 2015

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