Visualizing and Interacting with Video on Wall-Size Displays
Master-level internship at in|situ|
The goal of this internship is to design and evaluate interaction techniques that help users to annotate and visualize videos on a wall-size display.
Digiscope is a 22M€ project that explores collaboration within and across large interactive rooms that feature multiple display surfaces, such as the 140 million pixel WILD wall display at LRI (Beaudouin-Lafon et al., 2013). InSitu has explored how to interact with extremely large scientific data sets, such as images of the galaxy or collections of brain scans.
The goal of this internship is to explore how to interact with and manipulate multiple sets of time-based data, particularly video, on a wall-size display. The student will build upon a recent project that permits multiple users to display, annotate and interact with up to 32 concurrently displayed video clips using a mobile input device.
The goal is to create new ways of visualizing and interacting with these videos, e.g., finding new ways to represent time-based information, such as length and current play position; visualizing relationships among video clips, and exploring how to categorize, annotate and edit videos based on different characteristics. Another goal is to support multiple users, who can act together or on separate tasks in the same environment.
We will work with the student to design a study to observe how users analyze, manipulate and understand large video datasets, individually or in collaboration. This will most likely lead to the design of a controlled experiment. We anticipate that this work will lead to a publication in a conference such as ACM CHI.
During the internship, the student will be expected to:
- explore existing approaches for displaying time-based data on large displays, as well as relevant video control and annotation techniques;
- become familiar with the WILD wall environment;
- design and implement an application that enables multiple users to annotate, manipulate and obtain an overview of a large number of video clips that can play in parallel; and
- design and implement an experiment to explore collaborative interaction with video.
The internship may last from 4 to 6 months and could serve as the foundation for a Ph.D. thesis.
- Basic knowledge about Human-Computer Interaction
- Knowledge of node.js is a plus
- Experience in video editing is a plus
M. Beaudouin-Lafon, S. Huot, M. Nancel, W. Mackay, E. Pietriga, R. Primet, J. Wagner, O. Chapuis, C. Pillias, J. Eagan, T. Gjerlufsen, C. Klokmose (2012) Multisurface Interaction in the WILD Room. IEEE Computer. IEEE pp 48-56.
W. Mackay and M. Beaudouin-Lafon (1998) DIVA: Exploratory Data Analysis with Multimedia Streams. In Proc. ACM Human Factors in Computing Systems, CHI'98, Los Angeles (USA). ACM, pages 416-423.