Does Free-Sorting Provide A Good Estimate Of Visual Similarity
Creators: name: Clarke, Alasdair D. F.
name: Dong, Xinghui
name: Chantler, Mike J.
Publisher: name: Zenodo
Year: 2012

description: The majority of work on texture analysis  in computer vision has concerned texture classification and segmentation, while the problem  of measuring and  modelling  the visual  similarity  between  pairs  of textures has  been  relatively neglected. One  likely reason  for this is the difficulty  in collecting subjective human similarity judgments over a large database of textures. A common  approach is to carry  out a free-sorting experiment to obtain a similarity matrix which can then be mapped onto a low dimensional space using techniques such as  MDS  or  Isomap.    This  results   in  a  Euclidean space  in which  textures are  represented as points, and  the  distance between  two points  is taken to represent the perceptual visual  dissimilarity between  the associated pair  of textures. However,  it  is unknown if such  a  metric  can  generalise  to predict human texture judgements in other tasks, or even if similarity judgements are metric  at all.  In this study  we investigate this question by carrying out an experiment using a  pair-of-pairs paradigm and  compare  these results  to  the predictions made  by  a low dimensional model  (d  = 3) obtained from a free-sorting experiment and find that it agrees with  the  judgements made  by participants. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down.
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