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Form Perception

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Joe Kim

Form Perception Introduction to Form Perception Form perception – manage to make sense of things so quickly and easily The Gestalt Philosophy • Gestalt psychologists - studied how people perceive the world around them o Believed the whole is greater than the sum of its parts o Believed that people perceive the whole stimulus rather than each individual part o Believed that people tended to perceive the whole stimulus rather than just putting together a collection of the stimulus’ discrete parts • The Gestalt movement was in part reaction to the structuralist approach in vogue at the time, which suggested that everything could be reduced to basic elements o Example – perception of movement you experience when watching a movie made by flashing slightly different static pictures every o Example - Isn’t continuous movement in or across any of these frames  Still perceive continuous movement as we watch the rapid sequence of still pictures  Motion is an emergent property of the sequence of pictures  The perception of movie in its entirety – including all the complex movements is more than a collection of still photographs • Would never provide same rich experience that would get from watching the movie itself Gestalt Principle – laws that describe how we organize visual input • Proposed laws of organization that described how we group visual input in certain ways • Innate/acquire them rapidly Six Gestalt Principles: Figure-Ground • Ability of a visual scene is part of the object itself and what is part of the background • Example – viewing a vase of flowers against a flowery wallpaper • The Snowman Example o Small enclosed region that is completely surrounded by a larger region (background) o Figure tend to have distinct borders/edges - give it a perceptible form, is perceived as being in front of the background, which is typically be formless or made up of multiple forms • Example – optical illusions(faces and wine glass) Proximity • Helps with grouping • Elements that are close together in space tend to belong together • Example - more likely to group together the X’s that are close together than the X’s that are far apart • Example – daisies: regions of high daisy density as one group of daisies because of their proximity to each other rather than grouping together some daisies from one cluster with some from another Closure • If there are gaps in the contours of a shape, we tend to fill in those gaps and perceive a whole object • Example – broken truck • Example – your eyes will automatically perceive the shape as a rectangle Similarity • Tendency for us to group together elements that are physically similar • Example – sunflowers vs. corns (groups together vegetation of same type) and alternating XO’s (rather than grouping row of XOXO, group columns of X’s) Continuity • Perceive a simple continuous form rather than a combination of awkward forms • Example – the letter X (rather than a combination of two v’s joined in the middle) and the flower stems in a vase of flowers (continuous line as a stem even though they cross) Common Fate • Idea that things that change in the same way should be grouped together • A perception of the group of elements as a kind of object on its own • Example – school of fish • Example – camouflaged moth – moving elements with a common fate allow the contour of the moth’s shape to be perceived and suddenly, the moth seems to pop out against the tree Pattern/Object Recognition Expectations • What a person expects to see can influence what they do see Processes of Object Recognition • Preliminary steps in object recognition involve o Identifying what aspect of the scene is the figure o What is the background • Once it is established, parts of the figure are identified and grouped together into a single object Bottom-Up Processing • Combination of two processes required in order to recognize an object • First is bottom-up processing o The features that are present in the stimulus itself guides object recognition • Recognize what you see by analyzing the individual features and comparing those features to things with similar features that you have in memory • Stimulus driven • Pizza – must eat toppings before you get to crust o Features Top-Down Processing • Where your own beliefs or expectations are the primary influence for determining what youre seeing • Use expectations • Example - B/13 – read respectively depending on numbers or alphabet • Example – Priming o The experimenter measures how fast a participant can read a word that is flashed on a screen o Tell participant that the next work is an animal – priming effect, any animal will be recognized quicker than a random object o Shows that processing of a word is more efficient if the participant is primed to expect a word from a certain category • Top-down processing cannot work alone o Need some input from stimulus itself before expectations about stimulus can influence recognition • Same for bottom-up processing o Expectations influence perceptions • Thus, both processes are involved • Bi-directional activation – processing occurs in both directions at once o Features of the object in combination with our expectations guides object recognition o Object Features + Viewer’s Expectations = Object Recognition Theories of Object Recognition Biederman’s Geon Theory • Suggests that we have 36 different geons/simple geometrical forms stored in memory • Forms like a cone, shape, cylinder • Using 36 geons, possible to recognize over 150 million different objects • Example – ice cream cone: cone and sphere • Problems o Some stimuli cannot be described by geons o Stimuli such as faces/crumpled pieces of paper  Difficult to determine what geons would be used, however there is no difficult recognizing these stimuli Criticism from brain damage studies • Some forms of brain damage lead to very specific deficits o People suffering with brain injuries may not be able to recognize different types of fruits but can recognize different tools  If geons were involved in object recognition, might expect deficits in recognizing all types of objects based on their shapes and not a specific category of objects  Geons could also be processed at a different level of processing separate from the area of brain damage Exemplar/Template Theory • Theory of how we recognize objects is that we store many different templates in memory and when we come across an object, we compare that object to all the templates in memory • If match found – familiar object and person could name it by activating connections to other language areas in the brain • If no match is found, then it’s an unfamiliar object and a new template is stored in memory • Problem – numerous amount of templates o Mother template – face, different facial expression, hairstyles, lightning conditions and points of view Prototype Theory • Theory that overcomes the storage problems of the template theory • Store the most typical/ideal example of an object • Flexible system – don’t need an exact match between the observed object and what is stored in memory • Thus, easily recognize common objects that we’ve never seen before (dog/coffee mug) • Also recognize specific individual objects (favourite coffee mug/own dog) • Likely that there is more than one type of representation of each object (ideal prototypical dog and dogs that we are personally familiar with) Importance of Parallel Processing • Able to recognize objects because much of the neural processing of object information is done in parallel o Parallel - different brain systems process different components of visual signal simultaneously • At this time, no particular theory can provide a complete explanation for the success of our ability to recognize objects • Better at performing than computers Perceptual Constancies Perceptual Constancy – our ability to perceive an object as unchanging even though the visual image produced by the object is constantly changing Shape Constancy - perceive objects to have a constant shape • Even though actual retinal image of the shape would change as point of view changes/object changes position • Example – door closed (rectangle), door open (not rectangle anymore but still perceived as a rectangle) Location Constancy – perceive objects as stationary • But objects are constantly moving around on our retina as we move our eyes, heads and bodies • Example – drive in a car, don’t perceive objects as moving when passing by Size Constancy – see size of objects as unchanging even though as these objects vary in distance, the size of the retinal image that they can produce can vary quite a bit • Example – friend moving away from you, perceive him as being the same size just farther away from you Brightness Constancy – ability to know that the brightness of objects around us do not change even though the object may reflect more or less light depending on the ambient lighting conditions • For example- black looks black, white looks white o Black object outside is actually reflecting more light than white objects inside Colour Constancy – perceive objects around us to have a constant colour even though the light stimulus that reaches the retina may change with different illumination conditions • Example – still recognize white dog in reddish light (as long as a range of other colours are available in the background for reference) How do we explain perceptual constancies? 1. Existing knowledge • Top-down influence on how we see objects • Cues in scene o Visual system picks up cues in the rest of the scene and uses them as clues to perceiving constancy in an object  Depth cues – when friend is far away, keeps us from seeing friend as shrinking in size as he moves farther away • Perceptual constancies occur because we know that certain properties of objects do not change and our perceptual system automatically factors in other cues in the environment that give us information about the object of interest Visual Illusions Three Types of Visual Illusions • When given ambiguous or partial information • Illusions occur because our perceptual strategies are used in these particular situations where they don’t belong • Think we see one thing when in reality we’re looking at something quite different • Many perceptual constancies can be overcome by simply removing the relevant contextual information Muller-Lyer Illusion • Both lines are exactly the same in length • Why? Example of misapplying size constancy and inaccurately interpreting depth • Two lines give the exact same retinal image but the one on the left is assumed to be closer to you than the one on the right, the closer one is perceived as shorter • What if your culture had very few right angles? o People from cultures who live in round huts and aren’t surrounded by right angles are much less susceptible to the illusion o More likely to say that the two lines are of the same length o Illusion partly due to cultural and experience dependent processes The Ames Room • Specially constructed room that looks like a normal rectangular room except that its actually trapezoidal in shape o One corner is much farther from your point of view than the other corner o Two people of equal height – one looks much smaller than the other  The one who is in reality closer to you will be seen as larger o When your brain applies the compensatory computations that normally lead to size constancy - tricked by the cues normally used for distance constancy Ponzo Illusion • Result of conflicting size constancy and depth cues • Same length lines • Illusion occurs because two vertical lines are converging – gives a sense of depth • Top of the lines have converged the most as farther away than the bottom of the lines where they’re farther apart • Using depth cues to gauge size • Retinal size is the same but perceived distance differs Feature Detectors • Brain uses division of labour – each region along the visual pathway processing relatively specific information and then passing it on Magno and Parvo Cells • Magno and Parvo cells in the retina transduce the light stimulus into a neural impulse • Magno cells – found mainly in the periphery of the retina o Detect changes in brightness, motion and depth • Parvo cells – found throughout the retina o Detect colour, pattern and form • These ganglion cells with their small receptive fields are crucial first step to object recognition • From the retina o The axons of these cells exit the eye via the optic nerve, travel to the LGN and end up in the primary visual cortex in the occipital lobe • Feature detectors – cells are particular about what will make them fire Hodgkin and Huxley • Recorded the electrical activity in an individual neuron of the squid • Paved the way for other researchers to use this technology to see how individual neurons respond to specific stimuli Lettvin et al • Discovered a neuron in the optic nerve of a frog that responded only to moving black dots – these cells called bug detectors Hubel and Wiesel • Studies of cells in the visual cortex of cats and monkeys • Exploration of visual cortex began by trying to learn what type of stimuli the individual cortical cells responded to o Did this by putting microelectrodes in the cortex of a cat and recorded the electrical acidity of the individual neurons as the cat was shown different types of visual stimuli (flashes of light) o Problem – weren’t getting much response from the neurons unti
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