Evaluating video visualizations of human behavior

Mario Romero; Alice Vialard; John Peponis; John Stasko; Gregory Abowd

doi:10.1145/1978942.1979155

Evaluating video visualizations of human behavior

Mario Romero, Alice Vialard, John Peponis, John Stasko, Gregory Abowd

School of Architecture and Built Environment

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

7 Citations (Scopus)

35 Downloads (Pure)

Abstract

Previously, we presented Viz-A-Vis, a VIsualiZation of Activity through computer VISion [17]. Viz-A-Vis visualizes behavior as aggregate motion over observation space. In this paper, we present two complementary user studies of Viz-A-Vis measuring its performance and discovery affordances. First, we present a controlled user study aimed at comparatively measuring behavioral analysis preference and performance for observation and search tasks. Second, we describe a study with architects measuring discovery affordances and potential impacts on their work practices. We conclude: 1) Viz-A-Vis significantly reduced search time; and 2) it increased the number and quality of insightful discoveries.

Original language	English
Title of host publication	CHI '11 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher	ACM
Pages	1441-1450
ISBN (Print)	978-1-4503-0228-9
DOIs	https://doi.org/10.1145/1978942.1979155
Publication status	E-pub ahead of print - 11 May 2011
Event	Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - Duration: 11 May 2011 → …

Conference

Conference	Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Period	11/05/11 → …

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10.1145/1978942.1979155

Romero vialard peponis stasko abowd 2011Final published version, 877 KB

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abstract = "Previously, we presented Viz-A-Vis, a VIsualiZation of Activity through computer VISion [17]. Viz-A-Vis visualizes behavior as aggregate motion over observation space. In this paper, we present two complementary user studies of Viz-A-Vis measuring its performance and discovery affordances. First, we present a controlled user study aimed at comparatively measuring behavioral analysis preference and performance for observation and search tasks. Second, we describe a study with architects measuring discovery affordances and potential impacts on their work practices. We conclude: 1) Viz-A-Vis significantly reduced search time; and 2) it increased the number and quality of insightful discoveries.",

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AU - Romero, Mario

AU - Vialard, Alice

AU - Peponis, John

AU - Stasko, John

AU - Abowd, Gregory

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N2 - Previously, we presented Viz-A-Vis, a VIsualiZation of Activity through computer VISion [17]. Viz-A-Vis visualizes behavior as aggregate motion over observation space. In this paper, we present two complementary user studies of Viz-A-Vis measuring its performance and discovery affordances. First, we present a controlled user study aimed at comparatively measuring behavioral analysis preference and performance for observation and search tasks. Second, we describe a study with architects measuring discovery affordances and potential impacts on their work practices. We conclude: 1) Viz-A-Vis significantly reduced search time; and 2) it increased the number and quality of insightful discoveries.

AB - Previously, we presented Viz-A-Vis, a VIsualiZation of Activity through computer VISion [17]. Viz-A-Vis visualizes behavior as aggregate motion over observation space. In this paper, we present two complementary user studies of Viz-A-Vis measuring its performance and discovery affordances. First, we present a controlled user study aimed at comparatively measuring behavioral analysis preference and performance for observation and search tasks. Second, we describe a study with architects measuring discovery affordances and potential impacts on their work practices. We conclude: 1) Viz-A-Vis significantly reduced search time; and 2) it increased the number and quality of insightful discoveries.

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T2 - Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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ER -

Evaluating video visualizations of human behavior

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