The long-term evaluation of fisherman in a partial-attention environment

Xiaobin Shen, Andrew Vande Moere, Peter Eades, Seok-Hee Hong

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

9 Citations (Scopus)


Ambient display is a specific subfield of information visualization that only uses partial visual and cognitive attention of its users. Conducting an evaluation while drawing partial user attention is a challenging problem. Many normal information visualization evaluation methods (full attention) may not suit the evaluation of ambient displays. Inspired by concepts in the social and behavioral science, we categorize the evaluation of ambient displays into two methodologies: intrusive and non-intrusive. The major difference between these two approaches is the level of user involvement, as an intrusive evaluation requires a higher user involvement than a non-intrusive evaluation. Based on our long-term (5 months) non-intrusive evaluation of Fisherman presented in [16], this paper provides a detailed discussion of the actual technical and experimental setup of unobtrusively measurement of user gaze over a long period by using a face-tracking camera and IR sensors. In addition, this paper also demonstrates a solution to the ethical problem of using video cameras to collect data in a semi-public place. Finally, a quantitative term of interest measurement with three remarks is also addressed.
Original languageEnglish
Title of host publicationProceedings of the 2008 Conference on BEyond Time and Errors: Novel EvaLuation Methods for Information Visualization
EditorsEnrico Bertini
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
Publication statusPublished - 2008
Externally publishedYes
EventWorkshop on BEyond time and errors: novel evaLuation methods for Information Visualization 2008 - Florence, Italy
Duration: 5 Apr 20085 Apr 2008


ConferenceWorkshop on BEyond time and errors: novel evaLuation methods for Information Visualization 2008
Abbreviated titleBELIV 2008

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