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Asynchronous Visualization of Spatiotemporal Information for Multiple Moving Targets

Wang, Huadong (2013) Asynchronous Visualization of Spatiotemporal Information for Multiple Moving Targets. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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In the modern information age, the quantity and complexity of spatiotemporal data is increasing both rapidly and continuously. Sensor systems with multiple feeds that gather multidimensional spatiotemporal data will result in information clusters and overload, as well as a high cognitive load for users of these systems.

To meet future safety-critical situations and enhance time-critical decision-making missions in dynamic environments, and to support the easy and effective managing, browsing, and searching of spatiotemporal data in a dynamic environment, we propose an asynchronous, scalable, and comprehensive spatiotemporal data organization, display, and interaction method that allows operators to navigate through spatiotemporal information rather than through the environments being examined, and to maintain all necessary global and local situation awareness.

To empirically prove the viability of our approach, we developed the Event-Lens system, which generates asynchronous prioritized images to provide the operator with a manageable, comprehensive view of the information that is collected by multiple sensors. The user study and interaction mode experiments were designed and conducted. The Event-Lens system was discovered to have a consistent advantage in multiple moving-target marking-task performance measures. It was also found that participants’ attentional control, spatial ability, and action video gaming experience affected their overall performance.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairLewis, Michaelml@sis.pitt.eduCMLEWIS
Committee MemberKarimi, Hassan A.hkarimi@pitt.eduHKARIMI
Committee MemberNourbakhsh, Illah
Committee MemberHirtle, Stephen C.hirtle@pitt.eduHIRTLE
Committee MemberZadorozhny, Vladimirvladimir@sis.pitt.eduVIZ
Date: 27 August 2013
Date Type: Publication
Defense Date: 1 May 2012
Approval Date: 27 August 2013
Submission Date: 29 July 2013
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 147
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Human Robot Interaction, Multi-dimensional Data, Information Visualization, Spatiotemporal Data Fusion, Moving Targets
Date Deposited: 27 Aug 2013 20:08
Last Modified: 15 Nov 2016 14:14

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