Location Based Activity Recognition
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SELECT lab meeting: Jonathan Huang ( [email protected] ) Advisor: Carlos Guestrin 4/25/2006 - PowerPoint PPT Presentation


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Location Based Activity Recognition Lin Liao, Dieter Fox, Henry Kautz. In Adv. in Neural Information Processing Systems, 2005. SELECT lab meeting: Jonathan Huang ( [email protected] ) Advisor: Carlos Guestrin 4/25/2006. Task. Given GPS location data we would like to:

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Location Based Activity RecognitionLin Liao, Dieter Fox, Henry Kautz.In Adv. in Neural Information Processing Systems, 2005.

SELECT lab meeting: Jonathan Huang ([email protected])

Advisor: Carlos Guestrin

4/25/2006


Task

  • Given GPS location data we would like to:

    • Segment a user’s day into activities

      • “Working”

      • “Visiting”

      • “Travelling”

    • Label significant locations associated with one or more activities

      • “Workplace”

      • “Friend’s House”

      • “Bus stop”


Applications
Applications

  • Automated Diary

  • Long term health monitoring



Previous approaches
Previous Approaches

  • To identify significant locations

    • Use simple temporal threshold

  • HMMs, DBNs (generative)

    • This approach will be discriminative


Outline
Outline

  • An Example Activity Model

  • Conditional Random Fields

  • Relational Markov Networks

  • The Location-based Activity Model

  • Efficient Inference

    • Summation templates

    • FFT-based Belief Propagation

  • Experimental Results


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