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Inactive Projects

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		Component Analysis Head: Fernando De la Torre Frade Contact: Fernando De la Torre Frade Associated center(s) / consortia:  Vision and Autonomous Systems Center (VASC) Lab Homepage

Current Projects
		Deception Detection Learning facial indicators of deception
		Depression Assessment This project aims to compute quantitative behavioral measures related to depression severity from facial expression, body gestures, and vocal prosody in clinical interviews.
		Face Recognition Recognizing people from images and videos.
		Face Recognition Across Illumination Recognizing people from faces: video and still iamges.
		Face Recognition Across Pose Recognizing people from different poses.
		Facial Asymmetry as a Biometric We are investigating the effect of facial asymmetry measurement statistics as a biometric under expression variations.
		Facial Expression Analysis Automatic facial expression encoding, extraction and recognition, and expression intensity estimation for the applications of MPEG4 application: teleconferencing, human-computer interaction/interface.
		Facial Feature Detection Detecting facial features in images.
		Feature Selection Feature selection in component analysis.
		Forecasting the Anterior Cruciate Ligament Rupture Patterns Use of machine learning techniques to predict the injury pattern of the Anterior Cruciate Ligament (ACL) using non-invasive methods.
		Hot Flash Detection Machine learning algorithms to detect hot flashes in women using physiological measures.
		Image Alignment Image alignment with parameterized appearance models.
		Indoor People Localization Tracking multiple people in indoor environments with the connectivity of Bluetooth devices.
		Intelligent Diabetes Assistant We are working to create an intelligent assistant to help patients and clinicians work together to manage diabetes at a personal and social level. This project uses machine learning to predict the effect that patient specific behaviors have on blood glucose.
		Multimodal Diaries Summarization of daily activity from multimodal data (audio, video, body sensors and computer monitoring)
		Unification of Component Analysis This project aims to find the fundamental set of equations that unifies all component analysis methods.