A real time approach to the recognition of human activity based on the interaction with objects in domestic settings is presented. It is based on capturing partial images where the activity takes place using a color camera, and processing the images to recognize the present objects and their location changes. For object description and recognition, a histogram on a normalized chromaticity space has been selected. The interaction with the objects is classified as four types of possible actions regarding change in location (add, remove, move or unchanged). Activities are defined as receipts, where objects plays the role of ingredients, tools or substitutes. Sensed objects and actions are then used to analyze in real time the probability of the human activity that is being performed at the moment in a continuous activity sequence. Tests are carried on a automated kitchen scenario where proactive assistance wants to be implemented taking into account the early recognition user activity.

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