Motion perception

Motion perception is the process of inferring the speed and direction of elements in a scene based on visual, vestibular and proprioceptive inputs. Although this process appears straightforward to most observers, it has proven to be a difficult problem from a computational perspective, and difficult to explain in terms of neural processing.

Motion perception is studied by many disciplines, including psychology (i.e. visual perception), neurology, neurophysiology, engineering, and computer science.

The inability to perceive motion is called akinetopsia and it may be caused by a lesion to cortical area V5 in the extrastriate cortex. Neuropsychological studies of a patient who could not see motion, seeing the world in a series of static "frames" instead, suggested that visual area V5 in humans is homologous to motion processing area V5/MT in primates.

When two or more stimuli are alternatively switched on and off, they can produce two distinct motion perceptions. The first, known as beta movement, is demonstrated in the yellow-ball figure and forms the basis for electronic news ticker displays. However, at faster alternation rates, and when the distance between the stimuli is optimal, an illusory "object"—matching the background color—appears to move between the stimuli, alternately occluding them. This phenomenon is called the phi phenomenon and is often described as an example of "pure" motion detection, uncontaminated by form cues, unlike beta movement. Nevertheless, this description is somewhat paradoxical since creating such motion without figural percepts is impossible.

The phi phenomenon has been referred to as "first-order" motion perception. Werner E. Reichardt and Bernard Hassenstein have modelled it in terms of relatively simple "motion sensors" in the visual system, that have evolved 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 short delay. Sensors that are proposed to work this way have been referred to as either Hassenstein-Reichardt detectors after the scientists Bernhard Hassenstein and Werner Reichardt, who first modelled them, motion-energy sensors, or Elaborated Reichardt Detectors. These sensors are described as detecting motion by spatio-temporal correlation and are considered by some to be plausible models for how the visual system may detect motion. (Although, again, the notion of a "pure motion" detector suffers from the problem that there is no "pure motion" stimulus, i.e. a stimulus lacking perceived figure/ground properties). There is still considerable debate regarding the accuracy of the model and exact nature of this proposed process. It is not clear how the model distinguishes between movements of the eyes and movements of objects in the visual field, both of which produce changes in luminance on points on the retina.

Second-order motion is when the moving contour is defined by contrast, texture, flicker or some other quality that does not 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 to which they respond. (The notion that neural responses are attuned to frequency components of stimulation suffers from the lack of a functional rationale and has been generally criticized by G. Westheimer (2001) in an article called "The Fourier Theory of Vision.") Second-order motion produces a weaker motion aftereffect unless tested with dynamically flickering stimuli.

The motion direction of a contour is ambiguous, because the motion component parallel to the line cannot 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.

Some have speculated that, having extracted the hypothesized 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. (It is not clear how this 2D representation is then converted into the perceived 3D percept) Further processing is required to detect coherent motion or "global motion" present in a scene.