LikeLines-Player

Welcome to the new home for the LikeLines player component. The original prototype is still available on the Knight-Mozilla repository.

Introduction

Conventional online video players do not make the inner structure of the video apparent, making it hard to jump straight to the interesting parts. LikeLines provides users with a navigable heat map of interesting regions for the videos they are watching. The novelty of LikeLines lies in its combination of content analysis and both explicit and implicit user interactions.

The LikeLines system is being developed in the Delft Multimedia Information Retrieval Lab at the Delft University of Technology.

Demo

Running the demo requires:

• A HTML5-compatible browser supporting the Canvas element and JavaScript.
• Internet access (for the YouTube API and jQuery library).
• Python 2.6+ (for the backend reference implementation) with the following packages:
  • Flask
  • PyMongo
  • Flask-PyMongo
• MongoDB (for the backend).

You can download the code via git or through the Github web interface. Once downloaded and unpacked to a directory, three processes need to be started in order to run the demo. These three processes can best be run in separate terminals or screens.

The first process is starting a web server (or use an existing one) which will serve demo web page and the LikeLines JavaScript library. Note that you cannot simply open the web page locally (the browser would simply refuse to execute JavaScript in a local context):

$ cd likelines-player
$ python -m SimpleHTTPServer 8080

Next step is to make sure a MongoDB server is running on the default port. You can start the MongoDB server by simply executing mongod:

$ mongod

The final step is to run the backend server for LikeLines. This server will receive requests to store and aggregate user playback behaviour:

$ cd likelines-player/server
$ python -m LikeLines.server -p 9090

When the three processes are running, please point your browser to http://localhost:8080/examples/demo.html to start the demo.

Roadmap and plans

• March 2013: Make LikeLines deployable on at least one cloud platform.
• March 2013: Finalize support for content analysis indexing.
• Future: Add HTML5
• Future: Improve UI.

Acknowledgments