Author_Institution :
Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
For understanding the behavior, intent, and environment of a person, the surveillance metaphor is traditional; that is, install cameras and observe the subject, and his/her interaction with other people and the environment. Instead, we argue that the first-person vision (FPV), which senses the environment and the subject´s activities from a wearable sensor, is more advantageous with images about the subject´s environment as taken from his/her view points, and with readily available information about head motion and gaze through eye tracking. In this paper, we review key research challenges that need to be addressed to develop such FPV systems, and describe our ongoing work to address them using examples from our prototype systems.
Keywords :
body sensor networks; cameras; image sensors; FPV; camera; eye tracking; first-person vision; head motion; surveillance metaphor; wearable sensor; Behavioral science; Computer vision; Image matching; Intelligent systems; Object recognition; Quality assessment; Service robots; Surveillance; Tracking; Videos; Wearable sensors; Computer vision; eye tracking; object recognition; quality of life technologies;