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Activity Recognition and Crowd Sensing

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As Humans, we are always engaged in activity and it has been considered to be one of the most important ingredients of context awareness and ubiquitous computing. At the lab we pursue the goal of capturing the activity of individuals, groups and crowds on a city scale.

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Research

arpic
Sensing the Activities of Individuals

  • ActionSLAM (infrastructure-free indoor location tracking)
  • Topic models for activity routine discovery
  • Activity recognition with noisy crowdsourced annotation
  • Less supervision in activity recognition
  • Ambient sensing in activity recognition and semantic location awareness
crowdbehavior

Sensing Urban Behavior

  • Urban activity recognition
  • Social media as a probe for activity
  • Collective behavior on city scale events
  • Crowd sourcing activity models

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© 2017 ETH Zurich | Imprint | 13 October 2016
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