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Annual Review of Vision Science

Volume 4, 2018

Motion Perception: From Detection to Interpretation

Abstract

Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequency-selective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains. In the higher level, the velocity map is interpreted. Although there are many motion interpretation processes, we highlight the recent progress in research on the perception of material (e.g., specular reflection, liquid viscosity) and on animacy perception. We then consider possible linking mechanisms of the two levels and propose intrinsic flow decomposition as the key problem. To provide insights into computational mechanisms of motion perception, in addition to psychophysics and neurosciences, we review machine vision studies seeking to solve similar problems.

Keyword(s): animacy, first-order motion, intrinsic flow decomposition, material, spatiotemporal frequency, vector field
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2018-09-15
2024-04-24
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Motion Perception: From Detection to Interpretation
Annual Review of Vision Science 4, 501 (2018); https://doi.org/10.1146/annurev-vision-091517-034328
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Supplementary Data

  • Supplemental Video 1: A global Gabor motion (100% signal). It consists of an array of Gabor patches in random orientations. Their drifting speeds are made consistent with a single global 2D vector (downward motion in this case). With fixation on the display center, the observer will see the whole pattern move coherently with the direction and speed consistent with the global 2D vector. Adapted from Amano, Edwards, Badcock & Nishida (2009, Adaptive pooling of visual motion signals by the human visual system revealed with a novel multi-element stimulus. J. Vis. 9(3):4).

    Supplemental Video 2: A multi-stage ambiguous motion stimulus, which is globally as well as locally ambiguous. The global ambiguity implies that the stimulus is simultaneously consistent with both a global rigid translation and an infinite number of global rigid rotations. In agreement with the conventional intersection-of-constraints rule (i.e., local motions share a common global motion), central fixation induces a perception of vertical translation. However, fixation to the left or right causes the array to appear to rotate with a center approximately at fixation. In the periphery, local motion ambiguity seems to be resolved by the global rotation constraint rather than the global translation constraint. Adapted from Rider, Nishida & Johnston (2016. Multiple-stage ambiguity in motion perception reveals global computation of local motion directions. J. Vis. 16(15):7).

    Supplemental Video 3: Dynamic image deformation produces the perception of a transparent liquid material in front of the background texture. The pattern of deformation does not have to precisely simulate refraction by a real transparent liquid. Adapted from Kawabe, Maruya and Nishida (2015. Perceptual transparency from image deformation. PNAS 112: E4620–27).

    Supplemental Video 4: Perception of liquid from motion flow. Computer-rendered graphics clips of liquid flows (left) and the corresponding two-dimensional noise patch arrays (right). The noise pattern within each patch is shifted on the basis of local optical flow extracted from successive two frames of the liquid flow clip. Adapted from Kawabe, Maruya, Fleming, Nishida (2015. Seeing liquids from visual motion. Vis. Res. 109:125–38).

    Supplemental Video 5: Perception of animacy from motion. A dynamic point light jumper (left) and a simplified box jumper (right). Adapted from Kawabe (2017, Perceiving animacy from deformation and translation. i-Perception 8:2041669517707767).

  • Article Type: Review Article

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