Identifying human interactions in indoor environments

A laser range-finder-based system for detecting interactions between people in indoor environments is presented. An entropy-based measure is used to recursively segment tracks of individuals into distinct activities. Probability distributions corresponding to co-occurring activities are compared and similar distributions are flagged as representing possible interactions. Experimental results from two environments are described.

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