Single user activity recognition with Density Activity Abstraction Graphics Algorithm

Abstract

Recognition of activities today is an essential element in the artificial intelligence field. The smart environment is more and more present in residential spaces, which makes the activities recognition algorithms more and more efficient and adaptable. This article addresses the issue of recognizing activity based on event density. Each activity is interpreted as a density graph, and the recognition is done using image processing algorithms. This method facilitates the determination of transition zones between activities. Each user performs each activity differently, which makes it difficult to recognize the activities. The activities abstracting method presented in this article improves the recognition rate of activities.