Online Audiovisual Signature Training for Person Re-identification

Abstract

In intelligent environments, activity detection is a necessary pre-processing step for adaptive energy management and interaction with humans. To characterize the interactions between individuals or between an individual and the infrastructure of a building, a re-identification process is required and using multimodal models improves its robustness. In this paper, we propose a method for audiovisual fusion, which introduces a novel confidence index of audio-video salience zones, for training an audiovisual signature of a person within a sparse network of cameras and microphones.