Human Interactive E-learning Systems using Head Posture Images
نویسنده
چکیده
This paper explains a novel approach to human interactive e-learning systems using head posture images. Students’ face and hair information are used to identify a human presence and estimate the gaze direction. We then define the human-computer interaction level and test the definition using ten students and seventy different posture images. The experimental results show that head posture images provide adequate information for increasing human-computer interaction in e-learning systems. Keywords—E-learning, image segmentation, human-presence, gaze-direction, human-computer interaction, LabVIEW
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