Human behavior recognition for an intelligent video production system

We propose a novel framework for automated video capturing and production for desktop manipulations. We focus on the system's ability to select relevant views by recognizing types of human behavior. Using this function, the obtained videos direct the audience's attention to the relevant portions of the video and enable more effective communication. We first discuss significant types of human behavior that are commonly expressed in presentations, and propose a simple and highly precise method for recognizing them. We then demonstrate the efficacy of our system experimentally by recording presentations in a desktop manipulation.