3D Blur Discrimination

Abstract

Blur is an important attribute in the study and modeling of the human visual system. In the blur discrimination experiments, just-noticeable additional blur required to differentiate from the reference blur level is measured. The past studies on blur discrimination have measured the sensitivity of the human visual system to blur using two-dimensional (2D) test patterns. In this study, subjective tests are performed to measure blur discrimination thresholds using stereoscopic 3D test patterns. Specifically, how the binocular disparity affects the blur sensitivity is measured on a passive stereoscopic display. A passive stereoscopic display renders the left and right eye images in a row interleaved format. The subjects have to wear circularly polarized glasses to filter the appropriate images to the left and right eyes. Positive, negative, and zero disparity values are considered in these experiments. A positive disparity value projects the objects behind the display screen, a negative disparity value projects the objects in front of the display screen, and a zero disparity value projects the objects at the display plane. The blur discrimination thresholds are measured for both symmetric and asymmetric stereo viewing cases. In the symmetric viewing case, the same level of additional blur is applied to the left and right eye stimulus. In the asymmetric viewing case, different levels of additional blur are applied to the left and right eye stimuli. The results of this study indicate that, in the symmetric stereo viewing case, binocular disparity does not affect the blur discrimination thresholds for the selected 3D test patterns. As a consequence of these findings, we conclude that the models developed for 2D blur discrimination can be used for 3D blur discrimination. We also show that the Weber model provides a good fit to the blur discrimination threshold measurements for the symmetric stereo viewing case. In the asymmetric viewing case, the blur discrimination thresholds decreased, and the decrease in threshold values is found to be dominated by eye observing the higher blur.

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Index Terms

• Computing methodologies

  • Artificial intelligence

    • Philosophical/theoretical foundations of artificial intelligence

      • Cognitive science

• Human-centered computing

  • Human computer interaction (HCI)