Motion perception

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"Motion estimation" redirects here. For the video compression topic, see Motion compensation#Motion estimation.
The dorsal stream (green) and ventral stream (purple) are shown. They originate from a common source in visual cortex. The dorsal stream is responsible for detection of location and motion.
The dorsal stream (green) and ventral stream (purple) are shown. They originate from a common source in visual cortex. The dorsal stream is responsible for detection of location and motion.

Motion perception is the process of inferring the speed and direction of objects that move in a visual scene given some visual input. While this process appears straightforward to most observers, it has proven to be a hard problem from a computational perspective, and extraordinarily difficult to explain in terms of neural processing.

Motion perception has connections to both neurology (i.e. visual perception) and computer science.

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[edit] First-order motion perception

When an object (defined by a difference in luminance from its surroundings) moves, the 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 delayed change in luminance at a neighbouring point on the retina. Sensors that work this way have been referred to as Reichardt detectors, [1] motion-energy sensors [2] or Elaborated Reichardt Detectors. [3] 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. These 'first-order' (i.e. luminance-based) motion sensors unfortunately suffer from the aperture problem, which means that they can only detect motion perpendicular to the orientation of the contour that is moving. Further processing is required to disambiguate true global motion direction.

[edit] The aperture problem

The Aperture Problem.
The Aperture Problem.

Each neuron in the visual system is sensitive to visual input in a small part of our 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 cannot be inferred based on the visual input. This means that a variety of contours moving at different speeds will 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.

[edit] Motion in depth

As in other aspects of vision, the observer's visual input is generally insufficient to uniquely determine the 'true' nature of stimulus sources, in this case their velocity in a visual scene. 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."

[edit] Second-order motion perception

Motion stimuli are classified into first-order stimuli, in which the moving contour is defined by luminance, and second-order stimuli in which the moving contour is defined by contrast, texture, flicker or some other quality that does not result in an increase in motion energy in the Fourier spectrum of the stimulus. [4] [5]. There is much evidence to suggest that early processing of first- and second-order motion is carried out by separate pathways [6]. 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 [7].

[edit] References

  1. ^ Reichardt, W. (1961). "Autocorrelation, a principle for the evaluation of sensory information by the central nervous system.". W.A. Rosenblith (Ed.) Sensory communication (: 303-317. 
  2. ^ Adelson, E.H., & Bergen, J.R. (1985). "Spatiotemporal energy models for the perception of motion.". J Opt Soc Am A, 2 (2): 284-299. 
  3. ^ van Santen, J.P., & Sperling, G. (1985). "Elaborated Reichardt detectors.". J Opt Soc Am A, 2 (2): 300-321. 
  4. ^ Cavanagh, P & Mather, G (1989). "Motion: the long and short of it.". Spatial vision 4: 103-129. 
  5. ^ Chubb, C & Sperling, G (1988). "Drift-balanced random stimuli: A general basis for studying non-Fourier motion perception.". J Opt Soc Amer A, 5: 1986-2007. 
  6. ^ Nishida, S., Ledgeway, T. & Edwards, M. (1997). "Dual multiple-scale processing for motion in the human visual system.". Vision Research 37: 2685-2698. 
  7. ^ Ledgeway, T. & Smith, A.T. (1994). "The duration of the motion aftereffect following adaptation to first- and second-order motion.". Perception 23: 1211-1219. 

[edit] See also

[edit] External links

[edit] Labs specialising in motion research

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