EagleSense:tracking people and devices in interactive spaces using real-time top-view depth-sensing

Wu, Chi-Jui and Houben, Steven and Marquardt, Nicolai (2017) EagleSense:tracking people and devices in interactive spaces using real-time top-view depth-sensing. In: CHI '17 Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, New York, pp. 3929-3942. ISBN 9781450346559

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Abstract

Real-time tracking of people's location, orientation and activities is increasingly important for designing novel ubiquitous computing applications. Top-view camera-based tracking avoids occlusion when tracking people while collaborating, but often requires complex tracking systems and advanced computer vision algorithms. To facilitate the prototyping of ubiquitous computing applications for interactive spaces, we developed EagleSense, a real-time human posture and activity recognition system with a single top-view depth sensing camera. We contribute our novel algorithm and processing pipeline, including details for calculating silhouetteextremities features and applying gradient tree boosting classifiers for activity recognition optimised for top-view depth sensing. EagleSense provides easy access to the real-time tracking data and includes tools for facilitating the integration into custom applications. We report the results of a technical evaluation with 12 participants and demonstrate the capabilities of EagleSense with application case studies.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©The Authors. 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI '17 Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems http://dx.doi.org/10.1145/3025453.3025562
ID Code:
84705
Deposited By:
Deposited On:
14 Feb 2017 15:28
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Oct 2020 04:36