Modelling the Influence of Cultural Information on Vision-Based Human Home Activity Recognition
| Autor: | Antonio Sgorbissa, Barbara Bruno, Roberto Menicatti |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Computer science Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Ambient Assisted Living 02 engineering and technology Semantics Activity recognition Computer Science - Computers and Society Computer Science - Robotics Naive Bayes classifier 020901 industrial engineering & automation Human–computer interaction Cultural diversity Computers and Society (cs.CY) 0202 electrical engineering electronic engineering information engineering Point (typography) Vision based business.industry Culture-aware Robotics Robot 020201 artificial intelligence & image processing Artificial intelligence Human Activity Recognition business Robotics (cs.RO) |
| Zdroj: | URAI 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) ZENODO Archivio istituzionale della ricerca-Università di Genova arXiv.org e-Print Archive |
| DOI: | 10.48550/arxiv.1803.07915 |
| Popis: | Daily life activities, such as eating and sleeping, are deeply influenced by a person's culture, hence generating differences in the way a same activity is performed by individuals belonging to different cultures. We argue that taking cultural information into account can improve the performance of systems for the automated recognition of human activities. We propose four different solutions to the problem and present a system which uses a Naive Bayes model to associate cultural information with semantic information extracted from still images. Preliminary experiments with a dataset of images of individuals lying on the floor, sleeping on a futon and sleeping on a bed suggest that: i) solutions explicitly taking cultural information into account are more accurate than culture-unaware solutions; and ii) the proposed system is a promising starting point for the development of culture-aware Human Activity Recognition methods. Comment: 7 pages, 4 figures, Proc. URAI2017, International Conference on Ubiquitous Robots and Ambient Intelligence, Maison Glad Jeju, Jeju, Korea from June 28-July 2017 |
| Databáze: | OpenAIRE |
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