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Active Appearance Models (AAMs) is a computer vision procedure for statistical
matching of object shape and appearance between images. The present work will analyze
how AAMs can be employed with RGB-Depth technology, so robots endowing a Kinect
sensor can perceive and recognize humans more effectively in order to unequivocally
identify them. This research is associated to the RoCKIn@Home challenge, an initiative
from the European RoCKIn project focusing on domestic service robots.
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