Human activity recognition using a mobile camera

This paper presents a vision-based human activity recognition system using a mobile camera. This system aims to enhance human-robot interaction in a home setting for applications such as health care and companion. In the first place, the camera needs to find a human in image frames. The body pose is classified for the detected human. Then the human activity is recognized by combining information of human pose, human location and elapsed time. In order to determine the situated place of the person in a home setting, a novel space-boundary detection method is proposed in this paper. This method uses features in the environment to automatically set space boundary in the image such that human location in the environment can be obtained. In the integrated experiments, human pose recognition rate of five poses(standing, walking, sitting, squatting, lying) is 94.8%. Experiments of human activity recognition in a home setting have been conducted to verify the performance of the proposed method by using a mobile camera from different view angles and positions in a home setting. The experimental results reveal that the space boundaries are detected as expected and satisfactory results are obtained.