The rapidly increasing number of elderly people has led to the development of in-home assistive robots for assisting and monitoring elderly people in their daily life. To these ends, indoor scene and human activity recognition is fundamental. However, image processing is an expensive process, in computational, energy, storage and pricing terms, which can be problematic for consumer robots. For this reason, we propose the use of computer vision cloud services and a Naive Bayes model to perform indoor scene and human daily activity recognition. We implement the developed method on the telepresence robot Double to make it autonomously find and approach the person in the environment as well as detect the performed activity.
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