Sundara Venkataraman

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We have developed a method for distinguishing between correctly labeled and mislabeled data sampled from video sequences and used in the construction of a facial expression recognition classifier. The novelty of our approach lies in training a single, optimal classifier type (a support vector machine, or SVM) on multiple representations of the data,(More)
Application of computer vision to track changes in human facial expressions during long-duration spaceflight may be a useful way to unobtrusively detect the presence of stress during critical operations. To develop such an approach, we applied optical computer recognition (OCR) algorithms for detecting facial changes during performance while people(More)
Stress recognition from facial image sequences is a subject that has not received much attention although it is an important problem for a host of applications such as security and human-computer interaction. This class of problems and the related software are instances of Dynamic Data Driven Application Systems (DDDAS). This paper presents a method to(More)
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