In this paper a preliminary study on template updating techniques for face recognition in home environments is presented. In particular a new database has been created specifically for this application, where the face images acquired are characterized by a great variability in terms of pose and illumination but the number of subjects is quite limited and a large amount of images can be exploited for intensive incremental learning. The steps of database creation and the characteristics of the data collected are described in detail. We believe such a database could be very useful to develop and optimize face recognition approaches for smart home environments. Moreover some preliminary results on incremental learning are provided and analyzed to evaluate the effects of incremental template updating on the recognition performance.
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