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Depression Assesment
This project aims to compute quantitative behavioral measures related to depression severity from facial expression, body gesture, and vocal prosody in clinical interviews.
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Facial Feature Detection
Detecting facial features in images. |
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Facial Expression Analysis
Automatic facial expression encoding, extraction and recognition, and expression intensity estimation for diverse applications: teleconferencing, human-computer interaction/interface. |
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Face Recognition
Recognizing people from images and video. |
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Quality of Life Technology Center
QoLT is a unique partnership between Carnegie Mellon and the University of Pittsburgh that brings together a cross-disciplinary team of technologists, clinicians, industry partners, end users, and other stakeholders to create revolutionary technologies that will improve and sustain the quality of life for all people. |
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Multimodal Diaries
Summarization of daily activity from multimodal data (audio, video, body sensors and computer monitoring) |
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Temporal Alignment of Human Behavior
Temporal alignment of two or more subjects recorded from heterogeneous sensors is a challenging problem. This project develops statistical techniques for spatio-temporal alignment of multidimensional time series.
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Temporal Segmentation of Human Behavior
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Deception Detection
Learning facial indicators of deception.
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Hot Flash Detection
Machine learning algorithms to detect hot flashes in women using physiological measures.
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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.
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Camera Assisted Meeting Event Observer
We are developing the Camera Assisted Meeting Event Observer (CAMEO) - a sensory system designed to provide an electronic agent with physical awareness of the real world. |
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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. |
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Indoor People Localization
Tracking multiple people in indoor environments with the connectivity of Bluetooth devices. |
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Reflective Agents with Distributed Adaptive Reasoning
The focus of the RADAR project is to build a cognitive assistant that embodies machine learning technology that is able to function without requiring expert tuning or specially trained users. |
Current projects