Literature DB >> 21757505

Visual similarity effects in categorical search.

Robert G Alexander1, Gregory J Zelinsky.   

Abstract

We asked how visual similarity relationships affect search guidance to categorically defined targets (no visual preview). Experiment 1 used a web-based task to collect visual similarity rankings between two target categories, teddy bears and butterflies, and random-category objects, from which we created search displays in Experiment 2 having either high-similarity distractors, low-similarity distractors, or "mixed" displays with high-, medium-, and low-similarity distractors. Analysis of target-absent trials revealed faster manual responses and fewer fixated distractors on low-similarity displays compared to high-similarity displays. On mixed displays, first fixations were more frequent on high-similarity distractors (bear = 49%; butterfly = 58%) than on low-similarity distractors (bear = 9%; butterfly = 12%). Experiment 3 used the same high/low/mixed conditions, but now these conditions were created using similarity estimates from a computer vision model that ranked objects in terms of color, texture, and shape similarity. The same patterns were found, suggesting that categorical search can indeed be guided by purely visual similarity. Experiment 4 compared cases where the model and human rankings differed and when they agreed. We found that similarity effects were best predicted by cases where the two sets of rankings agreed, suggesting that both human visual similarity rankings and the computer vision model captured features important for guiding search to categorical targets.

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Year:  2011        PMID: 21757505     DOI: 10.1167/11.8.9

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  23 in total

1.  Modeling guidance and recognition in categorical search: bridging human and computer object detection.

Authors:  Gregory J Zelinsky; Yifan Peng; Alexander C Berg; Dimitris Samaras
Journal:  J Vis       Date:  2013-10-08       Impact factor: 2.240

2.  Modelling eye movements in a categorical search task.

Authors:  Gregory J Zelinsky; Hossein Adeli; Yifan Peng; Dimitris Samaras
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-09-09       Impact factor: 6.237

Review 3.  Template-to-distractor distinctiveness regulates visual search efficiency.

Authors:  Joy J Geng; Phillip Witkowski
Journal:  Curr Opin Psychol       Date:  2019-01-11

4.  More target features in visual working memory leads to poorer search guidance: evidence from contralateral delay activity.

Authors:  Joseph Schmidt; Annmarie MacNamara; Greg Hajcak Proudfit; Gregory J Zelinsky
Journal:  J Vis       Date:  2014-03-05       Impact factor: 2.240

5.  Effects of target typicality on categorical search.

Authors:  Justin T Maxfield; Westri D Stalder; Gregory J Zelinsky
Journal:  J Vis       Date:  2014-10-01       Impact factor: 2.240

6.  Eye can read your mind: decoding gaze fixations to reveal categorical search targets.

Authors:  Gregory J Zelinsky; Yifan Peng; Dimitris Samaras
Journal:  J Vis       Date:  2013-12-12       Impact factor: 2.240

7.  Are summary statistics enough? Evidence for the importance of shape in guiding visual search.

Authors:  Robert G Alexander; Joseph Schmidt; Gregory J Zelinsky
Journal:  Vis cogn       Date:  2014-04-01

8.  Effects of part-based similarity on visual search: the Frankenbear experiment.

Authors:  Robert G Alexander; Gregory J Zelinsky
Journal:  Vision Res       Date:  2012-01-02       Impact factor: 1.886

9.  Incidental memory following rapid object processing: The role of attention allocation strategies.

Authors:  Juan D Guevara Pinto; Megan H Papesh
Journal:  J Exp Psychol Hum Percept Perform       Date:  2019-06-20       Impact factor: 3.332

10.  Searching for something familiar or novel: top-down attentional selection of specific items or object categories.

Authors:  Rachel Wu; Gaia Scerif; Richard N Aslin; Tim J Smith; Rebecca Nako; Martin Eimer
Journal:  J Cogn Neurosci       Date:  2013-01-02       Impact factor: 3.225

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