Event Visualization in a 3D Environment

1
Event Visualization in a 3D Environment

• Leonidas Deligiannidis, (Presenter)
• Farshad Hakimpour,
• Amit P. Sheth

2
Semantic Event Tracker (SET)

• SET is an interactive visualization tool for
  analyzing events (activities)
• in a three-dimensional environment.
• We model an event as an object that describes
• an action,
• its location,
• time, and
• relations to other objects

3
SET

• We use RDF graphs to represent semantic metadata
  and ontologies.
• SET displays
• Semantically associated information
• Utilizes speech (recognizer/synthesizer)
• Digital images
• Audio clips
• Video clips
• GIS data

4
Three versions of SET

• 2D interface using a browser
• 3D interface using a Java application
• VR interface using Java

5
The SET Platform

• Event Data Store (EDS)
• Web accessible. Provides data querying and
  extraction of event information
• Map Renderer (MR)
• Web service or a Java Application that provides
  geo-referenced maps
• Semantic Event Tracker Visualizer (SETV)
• Visualizes events on geo-referenced maps
• Speech Communicator (SC)
• Audio interface with the user

6
SETS Architecture
7
Browser Interface and 2D Visualizer

• Specify
• Time
• Space
• Semantics
• Spatiotemporal Proximity

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3D Visualizer
9
VR Visualizer
10
State Machine
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Evaluation Method

• We evaluated the
• 2D interface
• 3D interface
• VR interface
• The experiment
• Three groups
• Seven subjects per group

12
The Task

• Question 1 (Q1) What specific pattern do you see
  in the geographic distribution of the locations
  of the events? More specifically, where most of
  the events occur?
• Question 2 (Q2) What specific pattern do you see
  in the temporal distribution of the events? More
  specifically, when most of the events occur?

13
Results

• Three-Level Factor (Interface Type) 2D, 3D, VR
• Dependent Variable Performance (Time to answer
  each question)
• Between-subject experimental design
• One-way analysis of variance (ANOVA)

14
Descriptive Statistics

• Q1
• Q2
• Tukeys Honest Significant Difference (HSD)

15
Conclusion