Wearable social camera: Egocentric video summarization for social interaction

Wearable social camera is an egocentric camera that summarizes the video of the user's social activities. This paper proposes a core technology of the wearable social camera: egocentric video summarization for social interaction. Different from other works of third-person action/interaction recognition in egocentric videos, which focus on distinguishing different actions, this work finds the common features among all the interactions, which is called interaction features (IF). IF of the third-person is proposed to be composed of three parts: physical information of head, body languages, and emotional expression. Furthermore, hidden Markov model (HMM) is employed to model the interaction sequences, and a summarized video is generated with hidden Markov support vector machine (HM-SVM). Experimental results with a life-log dataset show that the proposed system performs well for summarizing life-log videos.