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» Learning and Recognizing Human Dynamics in Video Sequences
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UIST
2009
ACM
15 years 4 months ago
Activity analysis enabling real-time video communication on mobile phones for deaf users
We describe our system called MobileASL for real-time video communication on the current U.S. mobile phone network. The goal of MobileASL is to enable Deaf people to communicate w...
Neva Cherniavsky, Jaehong Chon, Jacob O. Wobbrock,...
ICIP
2010
IEEE
14 years 7 months ago
People identification using shadow dynamics
People identification has numerous applications, ranging from surveillance/security to robotics. Face and body movement/gait biometrics are the most important tools for this task....
Yumi Iwashita, Adrian Stoica, Ryo Kurazume
AMDO
2006
Springer
15 years 1 months ago
Combined Head, Lips, Eyebrows, and Eyelids Tracking Using Adaptive Appearance Models
The ability to detect and track human heads and faces in video sequences is useful in a great number of applications, such as human-computer interaction and gesture recognition. Re...
Fadi Dornaika, Javier Orozco, Jordi Gonzàle...
CVPR
2003
IEEE
15 years 11 months ago
Finding and Tracking People from the Bottom Up
We describe a tracker that can track moving people in long sequences without manual initialization. Moving people are modeled with the assumption that, while configuration can var...
Deva Ramanan, David A. Forsyth
PAMI
2007
118views more  PAMI 2007»
14 years 9 months ago
Learning to Transform Time Series with a Few Examples
We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applie...
Ali Rahimi, Ben Recht, Trevor Darrell