A novel work for Ambient Assisted Living applications is presented here. More specifically, this paper focuses on activity recognition from recordings of daily living captured by wearable cameras. It constructs a discriminant object centric motion descriptor for representing the micro-actions within the viewpoint of the action maker so as to later define the activity that he/she performs. The accumulation of these activities build patterns over time that can be used to study the behavior of the end-users, which is very useful for health application and monitoring of patients inside their own dwellings or their behavior inside a controlled environment.