An interactive method for activity detection visualization

Li Liu, Sedat Ozer, Karen Bemis, Jay Takle, Deborah Silver

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

Visualizing each time step in an activity from a scientific dataset can aid in understanding the data and phenomena. In this work, we present a Graphical User Interface (GUI) that allows scientists to first graphically model an activity, then detect any activities that match the model, and finally visualize the detected activities in time varying scientific data sets. As a graphical and state based interactive approach, an activity detection framework is implemented by our GUI as a tool for modelling, hypothesis-testing and searching for interested activities from the phenomena evolution of the data set. We demonstrate here some features of our GUI: a histogram is used to visualize the number of activities detected as a function of time and to allow the user to focus on a moment in time; a table is used to give details about the activities and the features participating in them; and finally the user is given the ability to click on the screen to bring up 3D images of the overall activity sequence, single time steps of an activity, or individual feature in an activity. We present examples from applications to two different data sets.

Original languageEnglish (US)
Pages129-130
Number of pages2
DOIs
StatePublished - Jan 1 2013
Event2013 3rd IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2013 - Atlanta, GA, United States
Duration: Oct 13 2013Oct 14 2013

Other

Other2013 3rd IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2013
CountryUnited States
CityAtlanta, GA
Period10/13/1310/14/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Keywords

  • Graphical user interface
  • activity detection
  • data visualization
  • graph-based technique
  • interactive method

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    Liu, L., Ozer, S., Bemis, K., Takle, J., & Silver, D. (2013). An interactive method for activity detection visualization. 129-130. Paper presented at 2013 3rd IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2013, Atlanta, GA, United States. https://doi.org/10.1109/LDAV.2013.6675173