Topic 6: Objects and Scenes

Question 1

inverse projection problem

Answer 1

2d image on retina from 3d world
different objects can look identical
single object can look different

Question 2

viewpoint invariance

Answer 2

ability to recognize an object regardless of viewpoint

-object constancy

Question 3

gestalt approach

principle of good continuation

Answer 3

whole is other than the sum of parts

• principles of perceptual grouping
• lines tend to be seen as following smoothest path

Question 4

principle of good figure/simplicity/pragnanz

principle of similarity

Answer 4

stimulus patters are seen so the resulting structure is as simple as possible
-similar things appear grouped together

Question 5

principle of proximity/nearness

principle of common fate

Answer 5

nearby objects appear grouped together

-elements that move together appear grouped together

Question 6

principle of common region
principle of uniform connectedness
principle of perceptual separation

Answer 6

• elements that are in the same region of space appear grouped together
• a connected region with the same visual elements is perceived as a single unit
• allows us to separate elements apart

Question 7

figure-ground separation

Answer 7

figure is more thing-like and memorable than ground
-figure is in front of ground
ground is more uniform and extends behind figure
border ownership-contour separating figure from ground belongs to figure
-convex shapes are usually considered figure

Question 8

holistic (gestalt)

Answer 8

characterized by comprehension of the parts of something as intimately interconnected and explicable only by reference to the whole

Question 9

recognition by components theory (RBC)

Answer 9

we perceive objects by perceiving elementary features
geons = 3d volumes
an object is recognized when enough info is available to ID geons

Question 10

discriminability
resistance to visual noise
invariance
GEONS

Answer 10

-geons can be distinguished from other geons from almost all viewpoints
-geons can be perceived in noisy conditions
-recognizable no matter the illumination direction, surface markings or texture
36

Question 11

principle of componential recovery

Answer 11

-key to object recognition is not amount of info but ability to ID components or geons
-quantified by amount of surface area and amount of lines covered
critical juncture point determine ID ability

Question 12

JIMS model
layer 1
layer 2

Answer 12

neurally inspired, multi-layered, bottom up
starts with visual scene and travels up for processing
-basic visual features (edges and orientation)
-gives info of higher processing and more detail of environment (long lines and vertices)

Question 13

gist of a scene

Answer 13

according to RBC theory we build up from small details to overall object
-experiments on scene perception suggest we can perceive large properties first (250ms) and then fill detials

Question 14

degree of naturalness

degree of openness

Answer 14

undulating corners vs straight lines

visible horizon vs close environment

Question 15

degree of roughness
degree of expansion
colour

Answer 15

large even areas vs many small elements
-convergence of lines vs parallel lines
characteristic colours

Question 16

experience and perception

top down

Answer 16

perception based not just on the stimulus but depends on experience context goals
letters or numbers perceived based on orientation

Question 17

figure-ground separation experiment

Answer 17

when black image is similar to shadow it is more likely to be seen as figure
-when ambiguous black and white equally likely to be seen as figure
meaning and familiarity influences separation

Question 18

likelihood principle

unconscious interference

Answer 18

we perceive the object most likely to have cause the pattern of stimuli we receive
-application of likelihood principle is unconscious but based on past experience

Question 19

visual (what) stream
Fusiform face area
parahippocampal place area
extrastriate body area

Answer 19

-ventral stream and object ID
-responds to images of faces
-responds to images of places, houses scenes (bottom of temporal lobe)
responds to images of body parts and bodies in motion, in between dorsal and ventral stream

Question 20

visual expertise in FFA

Answer 20

task is to recognize faces or made up greebles
before training ffa was higher for faces
training was matching following blocking
after training there was no difference in ffa activation between faces and greebles
ffa can recognize similar objects that are distinct

Question 21

PPA vs 3d space

Answer 21

space defining objects and space ambiguous objects

SD objects activated PPA more - responds more than FFA but still not fully defined

Question 22

reconstructing visual experiences from brain
teach and use decoder
reconstruction

Answer 22

record brain activity while P watches trailers, build regression models, build library to put through regression and generate predicitons
-record brain activity for new set of trailers, select 100 clips which is similar to brain activity
average of clips togther

Question 23

neural decoding of neural imagery during sleep

Answer 23

train linear support vector machine (SVM) on fMRI data measured while each person viewed web images
-record fmri during sleep, predict images and compare to verbal descriptions
higher accuracy with higher levels of visual processing stream
ex. ffa more accurate than v1