Test 2 Flashcards
Invariance in object recognition
Object recognition tolerates substantial differences in retinal images (i.e., object constancy)
Template matching - Objects recognition
Object recognition based on fit with existing template in long-term memory (may use normalisation tricks like rotation).
Template alone doesn’t seem like the way to go, visual system has to do more
Feature analysis - Objects recognition
Attempts to obtain object constancy by having multiple feature detectors working in parallel
Image -> Feature demons -> Cognitive demons -> Decision demon
Structural Description - Objects recognition
Recognition model that describes objects by the structural organisation of parts/components (object skeletons)
Recognition by components (geon model) - Objects recognition
Identifies simple geometric components that make up complex objects (called shape primitives or “geons”). Much harder to recognise objects when geons are difficult to figure out due to occlusion or deletion.
Example of changing geon type or size
Equal amount of metric manipulation impacts object recognition more when the change involves geon types
View-based model - Objects recognition
Train participants to recognise novel objects at several 2D views then test with trained/untrained views. Participants perform better with trained views. Priming effects are translational invariant: moving object laterally b/w prime and test has no effect on performance
Object recognition is…
High level
Rapid
Object recognition and segmentation
Object recognition can influence figure/ground assignment in bistable displays. Experiment showed equal times of detection and categorization. Thus recognition can happen as fast as figure/ground segmentation but NOT within class identification
How rapid is object recognition?
between 100 - 150ms. This suggests mostly feed-forward mechanisms. This helps narrow down time for object recognition.
Define Apperceptive visual agnosia
Impaired visual perception of form/shape of objects, despite normal elementary vision (acuity, brightness, colour, etc)
Define Associative visual agnosia
A selective impairment in visual recognition of objects despite apparently adequate visual perception of them
what is the Lateral occipital complex
A set of ventral visual regions that responds more strongly to everyday objects than scrambled images of those objects. Responds to object format more than object cues.
Selective responses along ventral visual pathway
Some ventral regions show highly selective responses to particular object types (faces, bodies, scenes, words, etc)
Big debate about category-selective areas
Are these areas dedicated for recognising only preferred objects (modular view), or do they all work together in recognising all objects (distributed or many-to-many view)
Alternative hypotheses Prosopagnosia - Object agnosia hypothesis
Prosopagnosia is the most visible symptom of visual object agnosia. But there can be Prosopagnosia without object agnosia.
Alternative hypotheses Prosopagnosia - Within-class hypothesis
Prosopagnosia impairs within-class recognition of any objects. Testing within class -> worse for within faces than within other things.
Alternative hypotheses Prosopagnosia - Visual similarity hypothesis
Prosopagnosia impairs recognition of visually similar exemplars of an objects (upgraded within class). When testing dissimilarity scale of cars tracked at the same rate as other participants.
Alternative hypotheses Prosopagnosia - Expertise hypothesis
Prosopagnosia impairs recognition of objects with which we have obtained expertise. Predict they could not learn greebles, BUT they learned greebles similar to other participant success rates.
is there a double dissociation between face and object processing
Can be. One subject saw all the faces in the illusion and in silhouette could only see face not hand.
Define Face composite effect
Harder to discriminate face-halves aligned than misaligned because aligned halves are perceptually integrated
Face part-whole effect
Easier to discriminate features in whole face than in isolation because faces are represented as wholes.
Define the concept of Face Space
A multidimensional perceptual space in which the dimensions are features we use to discriminate faces (eye height, nose size, etc.). Individual faces are mapped according to their values on the dimensions
In relation to face space define prototype face and anti-face
Norm = A face that sits at the center of face space because it has the average value on all dimensions. Norm face doesn’t exist in real world, rather it’s a statistical average of all faces one has ever seen. Anti-face = A face that lies on the same trajectory as the original face but on the other side of the norm. An anti-face contains all the opposite features of its original face.
Norm based coding of faces
Adaptation to matched anti-face facilitates identification but adaptation to non-matched anti-face doesn’t. This shows that identity trajectories from norm face exist.
Feature coding in posterior face patch
Face cells in ML are tuned to simple attributes/dimensions of faces (hair thibkness, inter-eye distance, etc.)
Face space coding in posterior face patch
Face cells in ML track feature values across multiple attributes/dimensions in face space
Identity-invarient coding in anterior face patch
Face cells in AL are tolerant to image-level changes and show robust reponse to specific identities