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[Lab image] Human Sensing
Heads: Jessica K Hodgins, Jeffrey Cohn, Takeo Kanade, and Fernando De la Torre Frade
Contact: Fernando De la Torre Frade (ftorre@cs.cmu.edu)

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

For more information, see this lab's homepage.

Jump to: Lab Description | Personnel | Projects | Publications

Lab Description

The goal of the Human Sensing Lab is to develop new machine learning algorithms to model and understand human behavior from sensory data (e.g. video, motion capture, audio). Our work is motivated by applications in the fields of human health, biometrics and human-machine interface. For more information see www.humansensing.cs.cmu.edu

Personnel [Past members]

Name Title Email Address
Joan Campoy Research Associate tm08308@salle.url.edu
Sehun Chun Visiting Post-Doctoral Fellow sehun_chun@brown.edu
Jeffrey's personal homepage Jeffrey Cohn Adjunct Faculty (Adjunct) jeffcohn@cs.cmu.edu
Fernando's personal homepage Fernando De la Torre Frade Research Scientist ftorre@cs.cmu.edu
Jessica K Hodgins Faculty, RI/CS jkh@cs.cmu.edu
Takeo's personal homepage Takeo Kanade U.A. and Helen Whitaker University Prof., RI/CS tk@cs.cmu.edu
Javier Montano Martinez Research Associate I jmontano.84@gmail.com
David Monzo Ferrer Visiting Scholar damonfer@gmail.com
Minh's personal homepage Minh Hoai Nguyen PhD Student, RI minhhoan@andrew.cmu.edu
Tomas Simon Kreuz Research Associate tsimon@andrew.cmu.edu
James's personal homepage James Tolbert, II Graduate Assistant jatolber@andrew.cmu.edu
Feng Zhou Research Associate I zhfe99@gmail.com

Current Projects [Past 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.
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.
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.
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 Data Collection - A multimodal database of subjects performing the tasks involved in cooking, captured with several sensors (audio, video, motion capture, accelerometer/gyroscope).
Multimodal Diaries - Summarization of daily activity from multimodal data (audio, video, body sensors and computer monitoring)
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.
Temporal Segmentation of Human Motion - Temporal segmentation of human motion
 

Recent publications [View all 147 publications]

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