For understanding the behavior, intent, and environment of a person, the surveillance metaphor is traditional; that is, install cameras in the environment and observe her and her interaction with other people and environment from them. Instead, we argue that the First-Person Vision that senses the environment and her activities from her point of view is more advantageous with available images about her environment from her own view points and with readily available information about her head motion and gaze. We have been working in this paradigm for a while, and this talk will present the current progresses in the First Person Vision – the ideas, devices, algorithms, and example applications.