Active Visual Search: Investigating human strategies and how they compare to computational models

Simple item page
dc.contributor.advisorTsotsos, John K.
dc.contributor.authorWu, Tiffany
dc.date.accessioned2024-03-18T17:53:40Z
dc.date.available2024-03-18T17:53:40Z
dc.date.issued2024-03-16
dc.date.updated2024-03-16T10:54:56Z
dc.degree.disciplineComputer Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractReal world visual search by fully active observers has not been sufficiently investigated. Whilst the visual search paradigm has been widely used, most studies use a 2D, passive observation task, where immobile subjects search through stimuli on a screen. Computational models have similarly been compared to human performance only to the degree of 2D image search. I conduct an active search experiment in a 3D environment, measuring eye and head movements of untethered subjects during search. Results show patterns forming strategies for search, such as repeated search paths within and across subjects. Learning trends were found, but only in target present trials. Foraging models encapsulate subject location-leaving actions, whilst robotics models captured viewpoint selection behaviours. Eye movement models were less applicable to 3D search. The richness of data collected from this experiment opens many avenues of exploration, and the possibility of modelling active visual search in a more human-informed manner.
dc.identifier.urihttps://hdl.handle.net/10315/41862
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.subjectCognitive psychology
dc.subject.keywordsVisual search
dc.subject.keywordsActive vision
dc.subject.keywordsReal-world search
dc.subject.keywordsComputational models of visual search
dc.subject.keywordsActive search
dc.subject.keywordsActive visual search
dc.titleActive Visual Search: Investigating human strategies and how they compare to computational models
dc.typeElectronic Thesis or Dissertation

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Wu_Tiffany_C_2024_Masters.pdf
Size:
8.84 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
license.txt
Size:
1.87 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
YorkU_ETDlicense.txt
Size:
3.39 KB
Format:
Plain Text
Description:
Download

Collections

Computer Science

All items in the YorkSpace institutional repository are protected by copyright, with all rights reserved except where explicitly noted.