Lecture 3 Flashcards
Discuss the challenges of object perception
Different classes of things recognized - from different angles and when partly occluded. Occurs rapidly and without error. It appears effortless but is very complex. Objects overlap and vary enormously in their visual properties but we see them as the same thing. We accurately recognise objects over a wide range of viewing distances and orientations
Define perception
The ability of humans to recognise familiar, concrete things such as items of furniture, vechiles, fruits and vegetables.
Discuss the differences between human perception and computers
People take in information at multiple scales - registering large-scale shapes and patterns as quickly as small details. Whereas computers start with pixels in images and build up. We usually see the global features first, but we do have some control over which we see first.
What much be accomplished to recognise an object
See the basic features in the visual scene. Perceive organisation in the features. Perceive shape. Compare the shape percept to memory for known shapes. Make a decision about whether the object is familiar, and tap into knowledge about the object.
What is simultanagnosia
The inability to perceive how parts fit together. For example, in a picture they could pick out curtains or a child but would be unable to perceive the whole scene
Discuss the process of perceiving shape
Figure vs Group. Impossible fork - this illusion works because we process the global (a fork) before the local (the prongs) so we don’t initially see a problem until we examine the object carefully to try and separate figure and ground
What are 3 models of object recognition
Template matching. Feature recognition. Structural theories
Discuss template matching
Compares the whole object to stored representations to find a match.
To compare the shape percept to memory for known shapes and making a decision about whether the object is familiar, and tap into knowledge about what can we use
3 Models of object recognition - template matching, feature recognition, structural theories
Discuss feature analysis
Rather than focusing on the whole shape, feature models break shapes down into critical features - those critical features are recognised and then assembled into objects and shapes that are compared to mental templates.
Discuss strengths of feature detection
Reduces the number of representations the mind must stroe in order to process everything to be recognised. Physiological evidence of feature detectors
Discuss the limitations of matching models in general
Based on 2D but we see 3D. It cannot account for superficial differences in the same class of item. For example, in handwriting, different types of duck, guitar or yak. Can’t account for learning of new instances - instead has to be presented with them.
Discuss Marr & Nishihara’s (1978) model
Proposed 3 different levels of representation underpinning object recognition: Edge image (primal sketch) - provides 2D description of main light-intensity changes, including information about edges contours and blobs, it is observer centered. 2.5D sketch - incorporates depth and orientation of surfaces, makes use of shading, texture, motion, binocular disparity and is also observer-centered. 3D model representation - three-dimensional object shape, relative positions and viewpoint independent/invariant
Discuss where recognition occurs
Single model axis - identify main axis of object. Component axis - then identify the axes of each of the smaller sub-portions. 3D model match - between the arrangement of components and a stored 3D model description to identify object
Discuss Biederman’s recognition by components theory (RBC)
Objects consist of combinations of geons - geometric icons, combinations of 36 basic shapes. Object recognition is viewpoint invariant - emphasises bottom-up processes. Region of concativity are particularly important in RBC. Most experiments performed with familiar objects that we are used to seeing from multiple angles - does this differ?
Discuss Greebles and viewpoint dependence
Participants learn to recognise different types of Greeble so they become familiar, and are then presented with the same Greeble either in the same orientation or rotated. Familiar objects performance remained viewpoint-dependent with Greebles, even after extensive training
Discuss the dynamics of vision
Structural models focus on the perception of static images by a static observer. People and objects move and the perceptual system is good at dealing with this. Perception is not just for looking at things, it also guides actions
Discuss motion perception
To perceive moving objects we must be able to pick up changes in a stimulus over quite brief time intervals and recognise the same stimulus in different positions. Humans are good at this. Because apparent motion and real motion are so similar, some argue that the perception of movement can be thought of as the integration of a succession of discrete views.
What does object recognition depend on
Sensory information and prior expectation - models of object recognition have generally tried to explain the former.
What is Pareidolia
Seeing faces everywhere
What evidence is there that face recognition is different
Developmental. Configural processing. Mechanistic
Discuss developmental evidence for face recognition being different
Early work suggested that newborns orientated toward upright face stimuli. Subsequent research suggests that this tendency disappears after a month and later reappears some months later.
Discuss configural processing for face recognition being different
People respond faster and more accurately when the top and bottom halves are unaligned than when aligned, like faces are normal seen - can’t ignore one feature of faces when judging another. Upright faces are processed in an integrated way that makes access to their constituent features difficult
Discuss the evidence for face recognition being different in terms of mechanistic’s
Special brain areas are devoted to face processing - Fusiform Face Area (FFA), Superior Temporal Sulcus (STS), Occipital Face Area (OFA).
Discuss disorders of objects and face perception
Object agnostics - have trouble recongising objects Face agnostics - have trouble recognising faces
What is Prosopagnosia
Face without knowledge - A heterogeneous condition with varied origins. There are multiple reasons why face processing might be impaired: brain damage to face-processing regions, face recognition is just harder because it involves making finer distinctions
Discuss Bruce & Young’s (1986) research
Structural encoding - various representations or descriptions of faces. Expression analysis - an emotional state can be inferred from facial features. Facial speech analysis - speech perception can be aided by observing lip movements. Directed visual processing - specific facial information may be processed selectively. Face recognition units - structural information about known faces. Person identity units - information about individuals. Name generation - a person’s name. Cognitive system - contains additional information and influences which other components receive attention
What is Capgras syndrome
A disorder in which a person holds a delusion that a friend, spouse, parents or other close family member has been replaced by an identical-looking imposter. If the emotional pathway is damaged then perhaps people might look real to you perceptually but not feel real emotionally
What are some other questions about face recognition
If shape is everything for face recognition, why is a person harder to recognise in a negative image than a positive image? If processing is dependent on seeing very specific spatial relationships between features, why does distorting the face in a a number of ways have little effect on recognition?
Do we recognise/process familiar faces differently than we recognise/process unfamiliar faces and discuss
Yes. We can recognise familiar people at a greater distance and in poorer image quality
Discuss further implications
Facial attractiveness related to more lenient court decisions, but only for crimes where attractiveness is a factor - another reminder that context is important. Typical faces - not the most attractive - are deemed the most trustworthy. Flowe (2012) found that criminal faces were also rated as less trustworthy and more dominant
