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Creepy Tracker Toolkit for Context-aware Interfaces

Published: 17 October 2017 Publication History

Abstract

Context-aware pervasive applications can improve user experiences by tracking people in their surroundings. Such systems use multiple sensors to gather information regarding people and devices. However, when developing novel user experiences, researchers are left to building foundation code to support multiple network-connected sensors, a major hurdle to rapidly developing and testing new ideas.
We introduce Creepy Tracker, an open-source toolkit to ease prototyping with multiple commodity depth cameras. It automatically selects the best sensor to follow each person, handling occlusions and maximizing interaction space, while providing full-body tracking in scalable and extensible manners. It also keeps position and orientation of stationary interactive surfaces while offering continuously updated point-cloud user representations combining both depth and color data. Our performance evaluation shows that, although slightly less precise than marker-based optical systems, Creepy Tracker provides reliable multi-joint tracking without any wearable markers or special devices. Furthermore, implemented representative scenarios show that Creepy Tracker is well suited for deploying spatial and context-aware interactive experiences.

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    cover image ACM Conferences
    ISS '17: Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces
    October 2017
    504 pages
    ISBN:9781450346917
    DOI:10.1145/3132272
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    Published: 17 October 2017

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    Author Tags

    1. Context-aware Computing
    2. Rapid-Prototyping
    3. Toolkit

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    October 17 - 20, 2017
    Brighton, United Kingdom

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    Overall Acceptance Rate 147 of 533 submissions, 28%

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