Who is where

Matching People in Video to Wearable Acceleration During Crowded Mingling Events

Conference paper (2016)

Authors

L.C. Cabrera Quiros Pattern Recognition and Bioinformatics - , Instituto Tecnologico de Costa Rica

H.S. Hung Pattern Recognition and Bioinformatics -

Research Group

Pattern Recognition and Bioinformatics () (TU Delft)

Computer vision Association Wearable sensor Mingling

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http://resolver.tudelft.nl/uuid:4b00df17-c1d8-4230-bbf2-2356a694fbc8

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Published Date

2016

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

We address the challenging problem of associating acceleration data from a wearable sensor with the corresponding spatio-temporal region of a person in video during crowded mingling scenarios. This is an important first step for multisensor behavior analysis using these two modalities. Clearly, as the numbers of people in a scene increases, there is also a need to robustly and automatically associate a region of the video with each person’s device. We propose a hierarchical association approach which exploits the spatial context of the scene, outperforming the state-of-the-art approaches significantly. Moreover, we present experiments on matching from 3 to more than 130 acceleration and video streams which, to our knowledge, is significantly larger than prior works where only up to 5 device streams are associated.