- Visual system is robust to illumination and perspective changes. We usually hold that we should be sensitive to changes in shape, but how do you study that in a well principled way?
- References to earlier work that studied 2d shape change, here considering 3d
- 3 main ideas about how to make pose-independent shape classification, and there are ways to test which one seems to be what we do
- <Mostly interested in the way they generate their shape data and properties of it, so skipping most of the other stuff>
- ex/ “theories such as Shepard’s law of generalization, Nosofsky’s GCM and Ashby’s GRT”
- Shapes made up bodies – in all they were 70-dimensional
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“We remark that the nonlinearities in the image creation process led to a complicated relationship between the shape-space representation of an object and its appear- ance on the screen”
- “Many early studies relied on the estimation of subjective similarities between stimuli, through a process in which the ob- server had to provide a numerical rating of similarity when presented with a pair of stimuli. One drawback of this method is that many subjects do not feel comfort-
able when forced to rate similarity on a numerical scale. Another problem is the possibility of subjects modifying their internal similarity scale as the experiment pro- gresses. We avoided these problems by employing two different methods for measuring subjective similarity: compare pairs of pairs (CPP) and delayed match to sample (DMTS).”
- <skipping different experimental designs, moving on to discussion>
- Running MDS on subject data puts points pretty much where they should be
- “The CPP experiments described above support the hypothesis of veridical representation of similarity, by demonstrating that it is possible to recover the true low-dimensional shape-space configuration of complex stimuli from proximity tables obtained from subjects who made forced-choice similarity judgments.”
- “It is important to realize that the major computa- tional accomplishment in the experiments we have de- scribed so far is that of the human visual system and not of the MDS procedure used to analyze the data.”
- “The detailed recovery from subject data of complex similarity patterns imposed on the stimuli supports the notion of veridical representation of similarity, dis- cussed in the introduction. Although our findings are not inconsistent with a two-stage scheme in which geometric reconstruction of individual stimuli precedes the computation of their mutual similarities, the com- putational model that accompanies these findings offers a more parsimonious account of the psychophysical data. Specifically, representing objects by their similari- ties to a number of reference shapes (as in the RBF model described in Section 6.2) allowed us to replicate the recovery of parameter-space patterns observed in human subjects, while removing the need for a prior reconstruction of the geometry of the objects.”
- “Assuming that perceptual simi- larities decrease monotonically with psychological space distances, multidimensional scaling algorithms derive the psychological space configuration of the stimulus points from the table of the observed similarities.”
- asd
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