Creepy Tracker Toolkit for Context-aware Interfaces

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2017

Autores

Sousa, M (Autor) Outra; Mendes, D (Autor) Outra; dos Anjos, RK (Autor) Outra; Medeiros, D (Autor) Outra; Ferreira, A (Autor) Outra; Raposo, A (Autor) Outra; Pereira, JM (Autor) Outra; Jorge, JA (Autor) Outra

Ata de Conferência Internacional

Título: Proceedings of the Interactive Surfaces and Spaces, ISS 2017, Brighton, United Kingdom, October 17 - 20, 2017

Páginas: 191-200

2017 ACM International Conference on Interactive Surfaces and Spaces, ISS 2017

17 October 2017 through 20 October 2017

Indexação

Scopus - 21 Citações

Outras Informações

ID Authenticus: P-00N-911

DOI: 10.1145/3132272.3134113

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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica