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PSYC*2650 Ch 3.doc

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University of Guelph
PSYC 2650
Anneke Olthof

Tuesday, Jan 22, 2013 Chapter 3: Recognizing Objects Visual Perception - vision is the dominant sense, which is reflected in how much brain area is devoted to vision Form Perception - the process through which you manage to see what the basic shape and size of an object are Object Recognition - the process through which you identify what the object is Why Is Object Recognition Crucial? - virtually all knowledge and all use of knowledge depend on form perception and object recognition - object recognition is also crucial for learning - in virtually all learning, one must combine new information with information learned previously - to do this you must categorize thing properly Beyond the Information Given - object recognition begins with the detection of simple visual features - Gestalt Psychology - the perceptual whole is often different from the sum of its parts - Jerome Bruner voiced similar claims and coined the phrase “beyond the information given” to describe some of the ways that our perception of a stimulus differs from (and goes beyond) the stimulus itself - e.g. the Necker Cube is an ambiguous figure because there is more than one way to perceive it Tuesday, Jan 22, 2013 - your perception of the cube is not neutral, you perceive it as having one configuration or the other (goes beyond the information given) - e.g. the vase and 2 faces is also neutral with regard to perceptual organization - it is neutral with regard to figure/ground organization, the determination of what is the figure and what is the ground - your perception is not neutral, it specifies whether you are looking at 2 faces or a vase Organization and “Features” - one might suppose our perception of the world proceeds in 2 broad steps: (1) we col- lect information about the stimulus, so that we know what corners or angles are con- tained in the input, (2) we interpret the information, and presumable it would be in this second step that we “go beyond the information given” - deciding how the form is laid out in depth - this is wrong, we do not just “pick up” the information and our organization of input happens before we start cataloguing the input’s basic features - e.g. these black shapes initially seem to have no meaning, but after a moment, most people discover a word hidden in the figure - this means that at the start, the form seems not to contain the features needed to iden- tify the letters, once it is recognized it does contain those features and the letters are im- mediately recognized - the features are as much “in the eye of the beholder” as they are in the figure itself - e.g. most of the features needed for this recognition are absent from the figure but you easily provide the missing features - these create a potential paradox, on one side our perception of any form must start with the stimulus and must be governed by what is in that stimulus - on the other side these last 2 examples suggest the opposite is also the case: that the features one finds in an input depend on how the figure is interpreted - therefore, it is the interpretation, not the features that must be first Tuesday, Jan 22, 2013 - the solution hinges on the fact that the brain relies on parallel processing (analyzing a pattern’s basic features at the same time as analyzing the configuration) The Logic of Perception These steps of perceptual organization matter for us in many ways: - the organization determines our most immediate impression of the stimulus - decides whether a form will be recognized as familiar or not - what matters for familiari- ty is the figure as perceived - the figure plus the specifications added by the perceiver In what sense is perception “logical”? - interpretation achieved by the perceptual system must fit with all the incoming stimulus information (hypothesis) - the perceptual system acts just like a scientist - avoiding overly elaborate explanations of the “data” is a simpler explanation will do - the perceptual system seems to avoid interpretations that involves coincidences - e.g. this is initially perceives as 2 lines crossing but could also be perceived as 2 V shapes (which would rely on a coincidence that the forms just happen to be in exactly the right position) Object Recognition - with the form organized, we are ready to take the next steps toward identifying what the form actually is - start with examining how we recognize letters and words Recognition: Some Early Considerations - you can recognize a high number of patterns, various actions and different sorts of sit- uations - you can also recognize objects even when your information is partial e.g. still recog- nize a cat if only its head and paw are visible behind a tree - you can recognize tends of thousands of different swords as well - recognition of objects is influenced in important ways by the context - e.g. you read this as THE CAT not TAE CHT Tuesday, Jan 22, 2013 Features - one plausible suggestion is that many objects are recognized by virtue of their parts or features (vertical lines, cerise) - the features that are relevant here are not the features of the raw input, we use the ones in our organized perception of the input - e.g. we recognize all the forms in this as triangles even those the essential features are present in only one of them - the features are however, present in our organized perception of the forms, and this returns us to our proposal: we recognize objects by detecting the presence of the rele- vant features Advantages of a feature-based system: 1. features could serve as general-purpose building blocks 2. people can recognize many variations on the objects they encounter 3. several lines of data indicate that features do have priority in our perception of the world - e.g. in a visual search task, participants have to indicate whether a certain target is or is not present in a display - if the target is a single prominent features, the task is absurdly easy - the visual system does not inspect each of the figures, the difference jumps out imme- diately 4. other results suggest that the detection of features is a separate (and presumably early) step in object recognition Tuesday, Jan 22, 2013 - evidence comes from people who suffer from Integrative Agnosia, caused by dam- age to the parietal cortex, they can recognize features but cannot recognize how the features are bound together to form complex objects - studies in which transcranial magnetic stimulation (TMS), was used to disrupt por- tions of the brain in healthy individual found that disruption of the parietal lobe has no impact on single features but did on conjunction of features Word Recognition Factors Influencing Recognition - in many studies, participants have been shown stimuli for just a brief duration (20 or 30 ms) - older research used a Tachistoscope, a device designed to present stimuli for pre- cisely controlled amounts of time, modern research sues computers - each stimulus is followed by a post-stimulus Mask - often just a random jumble of let- ters, which serves to interrupt any continued processing that participants might try to do for the stimulus - people can recognize these stimuli depending on how familiar the stimulus is and how recently they had seen them - the first exposure Primes the participant for the second exposure, this is a case of Repetition Priming The Word-Superiority Effect - words themselves are easier to perceive, as compared to isolated letters - this effect is usually demonstrated with a “two-alternative, forced-choice” procedure e.g. showing a K or DARK and asking was there an E or a K - the accuracy rates are higher in the word condition so apparently recognizing words is easier than recognizing isolated letters Degrees of Well-Formedness - it is easier to recognize an E if it appears within a string (FIKE) than it is if the E ap- pears in isolated - having the context is helpful even if the context if neither familiar or meaningful - all contexts provide an advantage - a letter strike like “GLAKE” is far easier to recognize than “JPSRW” even though it is no more familiar Tuesday, Jan 22, 2013 - what matters is whether the string, familiar or not, is well formed according to the rules of language - if the string is well formed, then it will be easier to recognize and will produce a word- superiority effect - following the rules is a matter of degree, and so a letter string that follows the rules closely with produce a stronger word-superiority effect How do we assess “resemblance to English?” - one way is through pronounceability - one way is in statistical terms (how often the letter P follows the letter J) - which letter combinations are likely and which are rare Making Errors - the influence of spelling patterns emerges in the mistakes we make - errors are systematic: there is a strong tendency to misread less-common letter se- quences as if they were more-common patterns, irregular patterns are misread as if they were regular patterns - e.g. “TPUM” is likely to be misread as “TRUM” or “DRUM” - these errors are sometimes quite large - misspelled words, partial words or nonwords are read in a way that brings them into line with normal spelling - these errors are referred to as Over-Regularization Errors Feature Nets and Word Recognition The Design of a Feature Net - imagine we want a system that will recognize the word “CLOCK” - how might a “CLOCK” detector work? - perhaps each individual letter has a detector, but how do they work? - perhaps the L-detector is wired to a horizontal-line detector, and a vertical-line detector and maybe a corner detector - the idea is that there is a network of detectors, organized in layers, with each subse- quent layer concerned with more complex, larger-scale objects - the bottom layer is concerned with features, and this is why networks of this sort are often referred to as Feature Nets Tuesday, Jan 22, 2013 - at any point, each detector would have a particular Activation Level, which reflects how activated the detector is at just that moment - the activation level will eventually reach the detectors Response Threshold, and at that point the detector will Fire (send its signal to other detectors it’s connected to) - no one is suggesting that detectors are neurons, or even large groups of neurons - detectors would presumably involve much more complex assemblies of neural tissue - within the net, some detectors will be easier to activate than others - this readiness to fire is determined in part by how activated the detector was to begin with - what determines a detectors starting activation level? - detectors that have fired recently will have a higher activation level (warm-up effect) - detectors that have fired frequently in the past will also have a higher activation level (exercise effect) - frequent words appeared often in the things you read, so the detectors needed for rec- ognizing these have been frequently used and have a high activation level - this, even a weak signal (brief presentation) will bring these detectors to their response threshold and will be enough to make the detectors fire - repetition priming - presenting a word once will cause the relevant detectors to fire, once they have fired, activation levels will be temporarily lifted, therefore only a weak signal will be needed to make the detectors fire again The Feature Net and Well-Formedness - the net we’ve described so far cannot explain all of the data - the effects of well-formedness can’t be explained in terms of letter detectors - e.g. the same letters are used in “PIRT” and “ITPR” yet one is easy to recognize - the difference also can’t be explained in terms of word detectors, non of these letter sequences is a word Tuesday, Jan 22, 2013 - one option is to add another layer to the net, a layer will with detectors for letter combi- nations - we have added a letter of Bigram Detectors - detectors of letter pairs - these detectors, like all the rest, will be triggered by lower-level detectors and send their output to higher-level detectors - like other detectors, bigram detectors will start out with a certain activation level - this turns out to be all the theory we need - for “RSFK”, none of these letter combinations is familiar, so this will receive no benefits from priming and a strong input will be needed to bring the relevant detectors to thresh- old, and so the string will be recognized only with difficulty Recovery from Confusion - imagine presenting the word “CORN” for 20 ms - the quantity of incoming information is small and so some of the word’s features may not be detected - the fast presentation of O wasn’t enough to trigger all of the feature detectors, only the bottom-curve detector is firing and it will only be weakly activated - this is the same for U, Q, and S, the detectors are responsive to the bottom-curve fea- ture detector so they w
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