Fichas
Illusions
Fichas del conjunto (28)
- 1We are constantly exposed toillusions, making the claim 'believe what you see' unreliable.
- 2Light iseither emitted or reflected by a surface and converted into perceived brightness by information processing mechanisms which reduce redundancy and enhance contrast, which can lead to illusions or errors of representation.
- 3Therefore our sensesonly give us an approximation of the world, and do not generate reliable information in the case of perceptual illusions.
- 4Illusions play a major role inthe scientific study of sensory systems. They are a painter's favourite trick and the key to the animated arts of the 21st century such as the cinema, creating big fast and loud illusions.
- 5Minimal illusions: Kanizsa Triangle (1976)simply a pattern of three lines and three disc sections however we see this as a triangle.
- 62 fundamental approaches to understanding illusions: IPillusions reflect an error in the processing mechanisms underlying perception leading to discrepancies between the physical stimulus and mental experience. Gestalt Psychology supporters interpret illusions as going beyond the components of a stimulus, 'the whole is more than the sum of parts'. The perceptual system arguably chooses the simplest shape to interpret according to the law of praegnanz.
- 72 fundamental approaches to understanding illusions: Computational ApproachIllusions tell us about the mechanisms of visual information processing. Phenomena can be observed in the responses of single neurons in the visual system.
- 8Modern picture of visual processingcontains more detail than Descartes' initial sketch but is driven by similar organisational principles. Visual information flows along a complex neural pathway and involves parallel and hierarchial processing
- 9From the visual field to the retinotopic mapthe 3D environment is captures as flat two-dimensional images and the information is combined to give some depth perception
- 10Human eye can discriminate5000 perceptual levels of grey. An 8 bit computer screen can only discriminate 256.
- 11Differences between neighbouring regions of greyis called contrast
- 12Our perception of spatial resolutiontested by the finest pattern you can resolve at a distance without the lines blurring into a grey field.
- 13Using a lower resolution meansyou can identify individual pixels
- 14Spatial frequencythe number of pattern cycles (black and white strips) per degree of visual angle (Wilson 1991)
- 15With 100% visual acuitythere are approximately 50 cycles per degree
- 16Filteringparallel sets of receptive fields operate to separate different spatial frequency components. The size and structure of receptive fields determines optimum size
- 17The outside world is represented inretinotopic maps of neurons, with centre-surround receptive fields operating opponency filtering (such as contrast enhancement, redundancy reduction, and spatial filtering)
- 18Hermann Grid IllusionIllusory grey spots are perceived at the intersections of a white grid on a black background
- 19Herman Grid ExplanationIllusory grey spots are believed to be the result of lateral inhibition. Black squares are correctly perceived as being dark as there is little excitation. With white bars, only small parts of the inhibitory surround are stimulated and they are correctly perceived as being bright. With intersections however, larger parts of the inhibitory surround are stimulated leading to an apparent reduction in brightness.
- 20Hermann Grid - Image Compression: Why are the central regions of black squares not perceived as brighter than the boundary regions?Redundant information is removed ans no signal is transmitted for regions of equal luminance. Only luminance boundaries are encoded.
However the operation of simple receptive fields cannot explain how we perceive brightness.
Filling in mechanisms are required to reconstruct redundant image components, by assuming that regions enclosed by clear boundaries, originally have the same intensity. - 21Craik Cornsweet Illusionsurfaces between boundaries are filled in with assumed uniform brightness, causing subtle gradients to be overlooked. In an attempt to reduce redundant information, only changes in intensity are encoded which is because our visual system responds more strongly to sharper rather than gradual changes in intensity. This accounts for the more visible change in gradient between regions. This is the result of opponency, balancing the signs of receptive fields to determine the output.
- 22Colour helps toidentify one particular object within a group. E.g. instead of directing someone to the exact location of your car or describing details such as shape and intricate engineering details, you can simply direct someone to the 'bright blue car'.
- 23We make constant use ofthe extra information colour perception provides to our retinal images. Colour helps us to recognise objects and keep them in our memory (Gegenfurtner and Reiger 2000).
- 24In evolution the key functions of colour visionwere related to the detection or predators or prey, or fruits (Osorio and Vorobyev 1996)
- 25According to 21st century knowledgeeach pure light source can be described by it's wavelength within the visible range of electromagnetic waves, which is perceived as colour
- 26Intensity isperceived brightness (Hubel 1988)
- 27Perceptual properties of colourare more difficult to describe than physical properties. There is no immediate relationship between physical properties of a light beam and perceived quality of a particular colour.
Hue = dimension 1. What we refer to as perceived colour.
Saturation = dimension 2. Intensity of colour sensation
Contrast = changes which generate contrast are possible in two directions, saturation and hue. - 28How to measure colourthere's only a few true colour names but many object related ones. The system and number of true colours varies in culture suggesting some kind of evolution (Berlin & Kay 1969).
By arranging colours into a colour circle we can measure discrimination thresholds (how many colours you can discriminate). Human visual system (5 million), 24 bit computer (16 million)
Información
- Descripción
- Fichas sobre Illusions, creado por lauradavies94 el 20/04/2014.
- Creado por
- lauradavies94
- Visitas
- 12
- Valoración