{"id":227,"date":"2013-12-10T21:52:34","date_gmt":"2013-12-10T21:52:34","guid":{"rendered":"https:\/\/michaelhout.com\/?page_id=227"},"modified":"2015-01-21T11:11:07","modified_gmt":"2015-01-21T18:11:07","slug":"mds-image-database","status":"publish","type":"page","link":"https:\/\/michaelhout.com\/?page_id=227","title":{"rendered":"MM-MDS Database"},"content":{"rendered":"

In collaboration with <\/span>Dr. Stephen D. Goldinger<\/a> and Kyle J. Brady (at Arizona State University), we collected similarity ratings for 240 different image categories, selected from the Massive Memory Database (Brady et al., 2008; Konkle et al., 2010). \u00a0Their image database can be found at: <\/span>http:\/\/cvcl.mit.edu\/MM\/stimuli.html<\/a>. \u00a0Specifically, we selected each of their 240 image categories that contained 16 or 17 exemplars per category, collected similarity estimates on each (using the spatial arrangement method; <\/span>SpAM<\/em>), and analyzed the data using multidimensional scaling. \u00a0Our goal was to provide a large similarity database, indexed via multidimensional scaling, so that other researchers could make use of the Massive Memory stimuli in such a way as to know the precise similarity between the different images. \u00a0We hope that memory and perception researchers will put this database to good use. \u00a0If you do, please let us know! \u00a0Please visit the various sub-sections for information on our methods, sample analyses, and of course, the full database.<\/span><\/p>\n

Abstract:<\/span><\/p>\n

Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of \u201csameness\u201d among their stimuli.\u00a0 For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory.\u00a0 Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category.\u00a0 In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16-17 exemplar objects.\u00a0 We collected similarity ratings using the spatial arrangement method<\/em>. \u00a0Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications.\u00a0 For each picture, we categorized the item\u2019s prototypicality, indexed by its proximity to other items in the space.\u00a0 We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space.\u00a0 These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of \u201csameness.\u201d<\/p>\n

Our article has recently been accepted for publication. \u00a0If you use this database, please make sure to cite us! \u00a0Thanks very much.<\/p>\n