Conference Paper

The effects of semantic grouping on visual search.

DOI: 10.1145/1358628.1358876 Conference: Extended Abstracts Proceedings of the 2008 Conference on Human Factors in Computing Systems, CHI 2008, Florence, Italy, April 5-10, 2008
Source: DBLP

ABSTRACT This paper reports on work-in-progress to better understand how users visually interact with hierarchically organized semantic information. Experimental reaction time and eye movement data are reported that give insight into strategies people employ while searching visual layouts containing words that are either grouped by category (i.e. semantically cohesive) or randomly grouped. Additionally, sometimes the category labels of the cohesive groups are displayed as part of the group. Preliminary results suggest that: (a) When groups are cohesive, people tend to search labeled and unlabeled layouts similarly. (b) People seem to trust the categorical information of labels more than non-labels. This work will be used to extend current computational models of visual search to better predict users visual interaction with interfaces.

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    ABSTRACT: ABSTRACT We propose a novel framework to localize and label affec- tive objects and actions in images through a combination of text, visual and gaze-based analysis. Human gaze pro- vides useful cues to infer locations and interactions of af- fective objects. While concepts (labels) associated with an image can be determined from its caption, we demonstrate localization of these concepts upon learning from a statisti- cal affect model for world concepts. The affect model is derived from non-invasively acquired fixation patterns on labeled images, and guides localization of affective objects (faces, reptiles ) and actions (look, read ) from fixations in un- labeled images. Experimental results obtained on a database of 500 images confirm the effectiveness and promise of the proposed approach. Categories and Subject Descriptors: H.4 [Information Systems Applications]: Multimedia Application General Terms: Human Factors, Algorithms. Keywords: Automated localization and labeling, caption text-cum-eye gaze analysis, affect model for world concepts, statistical model.
    Proceedings of the 17th International Conference on Multimedia 2009, Vancouver, British Columbia, Canada, October 19-24, 2009; 01/2009


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