Everything about Motion Perception totally explained
Motion perception is the process of inferring the speed and direction of elements in a scene based on
visual input. Although this process appears straightforward to most observers, it has proven to be a difficult problem from a computational perspective, and extraordinarily difficult to explain in terms of
neural processing.
Motion perception is studied by many disciplines, including
psychology (for example
visual perception),
neurology,
neurophysiology,
engineering, and
computer science.
Neuropsychology
Area V5 seems to be important to the processing of visual motion and damage to this area can disrupt motion perception.
Neuropsychological studies of a patient who couldn't see motion, seeing the world in a series of static "frames" instead, suggested that visual area V5 in the human is homologous to area MT in the primate.
First-order motion perception
First-order motion perception refers to the perception of the motion of an object that differs in
luminance from its background, such as a black bug crawling across a white page. This sort of motion can be detected by a relatively simple motion sensor designed to detect a change in luminance at one point on the retina and correlate it with a change in luminance at a neighbouring point on the retina after a delay. Sensors that work this way have been referred to as
Reichardt detectors (after the scientist Werner Reichardt, who first modelled them), motion-energy sensors, or Elaborated Reichardt Detectors. These sensors detect motion by spatio-temporal
correlation and are plausible models for how the visual system may detect motion. Debate still rages about the exact nature of this process. First-order motion sensors suffer from the
aperture problem, which means that they can detect motion only perpendicular to the
orientation of the contour that's moving. Further processing is required to disambiguate true
global motion direction.
Second-order motion perception
Second-order motion is motion in which the moving contour is defined by
contrast,
texture, flicker or some other quality that doesn't result in an increase in luminance or motion energy in the
Fourier spectrum of the stimulus. There is much evidence to suggest that early processing of first- and second-order motion is carried out by separate pathways. Second-order mechanisms have poorer temporal resolution and are
low-pass in terms of the range of
spatial frequencies that they respond to. Second-order motion produces a weaker
motion aftereffect unless tested with dynamically flickering stimuli. First and second-order signals appear to be fully combined at the level of Area
V5/MT of the visual system.
Motion integration
Having extracted motion signals (first- or second-order) from the retinal image, the visual system must integrate those individual
local motion signals at various parts of the visual field into a 2-dimensional or
global representation of moving objects and surfaces.
The aperture problem
Each
neuron in the visual system is sensitive to visual input in a small part of the
visual field, as if each neuron is looking at the visual field through a small window or
aperture. The motion direction of a contour is ambiguous, because the motion component parallel to the line can't be inferred based on the visual input. This means that a variety of contours of different orientations moving at different speeds can cause identical responses in a motion sensitive neuron in the visual system.
Individual neurons early in the visual system (
LGN or
V1) respond to motion that occurs locally within their receptive field. Because each local motion-detecting neuron will suffer from the aperture problem, the estimates from many neurons need to be
integrated into a global motion estimate. This appears to occur in Area
MT/V5 in human
visual cortex.
See also the
barberpole illusion.
Motion in depth
As in other aspects of vision, the observer's visual input is generally insufficient to determine the true nature of stimulus sources, in this case their velocity in the real world. In monocular vision for example, the visual input will be a 2D projection of a 3D scene. The motion cues present in the 2D projection will by default be insufficient to reconstruct the motion present in the 3D scene. Put differently, many 3D scenes will be compatible with a single 2D projection. The problem of motion estimation generalizes to
binocular vision when we consider occlusion or motion perception at relatively large distances, where binocular disparity is a poor cue to depth. This fundamental difficulty is referred to as the
inverse problem.
Further Information
Get more info on 'Motion Perception'.
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