Toward Robust Features for Remote Audio-Visual Classroom
نویسندگان
چکیده
We present two studies on robustness of feature extractions for an remote classroom intelligent autopilot: (1) robust feature extractions and (2) a simple automated calibration of webcams. For the robust feature extractions, use of quantified vectors is studied as feature extractions of fuzzy classifiers in Perceptual State Machine, i.e. our core Computational Intelligence model for this intelligent autopilot. The simple automated calibration of devices is studied mainly for the sake of maximizing device utility. Those studies have shown promising results for actual use of this intelligent autopilot in ordinary classrooms that are not necessarily ideal for teleconfer-
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