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We argue that to make robust computer vision algorithms for face analysis and recognition, these should be based on configural and shape features. In this model, the most important task to be solved by computer vision researchers is that of accurate detection of facial features, rather than recognition. We base our arguments on recent results in cognitive science and neuroscience. In particular, we...
This paper presents a real-time video event recognition system for controlled environments. It is able to recognize human activities and interactions with the objects of the environment by exploiting different cues like trajectory analysis, skin detection and people recognition of the foreground blobs of the scene. Time variations of these features are studied and combined using Bayesian inference...
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