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Creepy Tracker Toolkit for Context-aware Interfaces

Title
Creepy Tracker Toolkit for Context-aware Interfaces
Type
Article in International Conference Proceedings Book
Year
2017
Authors
Sousa, M
(Author)
Other
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dos Anjos, RK
(Author)
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Medeiros, D
(Author)
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Ferreira, A
(Author)
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Raposo, A
(Author)
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Pereira, JM
(Author)
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Jorge, JA
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Conference proceedings International
Pages: 191-200
2017 ACM International Conference on Interactive Surfaces and Spaces, ISS 2017
17 October 2017 through 20 October 2017
Indexing
Other information
Authenticus ID: P-00N-911
Abstract (EN): 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. © 2017 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Language: English
Type (Professor's evaluation): Scientific
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