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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Action Recognition in a Crowded Environment.

Laura Fademrecht1, Judith Nieuwenhuis1, Isabelle Bülthoff2

  • 1Max PlanckInstitute for Biological Cybernetics, Tübingen, Baden-Württemberg, Germany.

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Summary
This summary is machine-generated.

Recognizing human actions, even in peripheral vision, is impacted by crowds performing similar movements. Dissimilar crowd actions, however, show minimal interference with action recognition.

Keywords:
action recognitionadaptationcrowdingeccentricityperipheral vision

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Area of Science:

  • Human visual perception
  • Cognitive neuroscience
  • Action recognition

Background:

  • Action recognition studies traditionally use limited visual stimuli.
  • Real-world scenarios involve recognizing life-size humans in varied contexts, including crowds.
  • Understanding action recognition in central and peripheral vision is crucial.

Purpose of the Study:

  • To investigate action recognition mechanisms in central and peripheral vision.
  • To assess the impact of surrounding crowds on recognizing a target's action.
  • To differentiate the effects of crowd movement similarity on action recognition.

Main Methods:

  • Employed an action adaptation paradigm to test interference effects.
  • Utilized a recognition task to confirm findings.
  • Compared central vision with peripheral vision (40° eccentricity).

Main Results:

  • Crowds with dissimilar movements minimally affected action recognition.
  • Crowds with similar movements diminished adaptation aftereffects in both central and peripheral vision.
  • Action recognition accuracy decreased significantly in peripheral vision when crowds performed similar actions.

Conclusions:

  • Crowd actions similar to the target's action interfere with recognition.
  • High-level crowding effects on action-sensitive perceptual channels may explain these findings.
  • This research extends action recognition to more ecologically valid cluttered scenes.