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스마트폰 기반 행동인식 기술 동향
Trends in Activity Recognition Using Smartphone Sensors

김무섭   (웨어러블컴퓨팅연구실  ); 정치윤   (웨어러블컴퓨팅연구실  ); 손종무   (웨어러블컴퓨팅연구실  ); 임지연   (웨어러블컴퓨팅연구실  ); 정승은   (웨어러블컴퓨팅연구실  ); 정현태   (웨어러블컴퓨팅연구실  ); 신형철   (웨어러블컴퓨팅연구실  );
  • 초록

    Human activity recognition (HAR) is a technology that aims to offer an automatic recognition of what a person is doing with respect to their body motion and gestures. HAR is essential in many applications such as human-computer interaction, health care, rehabilitation engineering, video surveillance, and artificial intelligence. Smartphones are becoming the most popular platform for activity recognition owing to their convenience, portability, and ease of use. The noticeable change in smartphone-based activity recognition is the adoption of a deep learning algorithm leading to successful learning outcomes. In this article, we analyze the technology trend of activity recognition using smartphone sensors, challenging issues for future development, and a strategy change in terms of the generation of a activity recognition dataset.


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