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» A bottom-up framework for robust facial feature detection
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ICASSP
2011
IEEE
14 years 1 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
EAAI
2010
91views more  EAAI 2010»
14 years 9 months ago
A framework for on-line trend extraction and fault diagnosis
: Qualitative trend analysis (QTA) is a process-history-based data-driven technique that works by extracting important features (trends) from the measured signals and evaluating th...
Mano Ram Maurya, Praveen K. Paritosh, Raghunathan ...
DICTA
2003
14 years 11 months ago
3D Face Recognition Using Longitudinal Section and Transection
In this paper, a new practical implementation of a person verification system using features of longitudinal section and transection and other facial, rotation compensated 3D face ...
Yeung-hak Lee
HCI
2009
14 years 7 months ago
Responding to Learners' Cognitive-Affective States with Supportive and Shakeup Dialogues
This paper describes two affect-sensitive variants of an existing intelligent tutoring system called AutoTutor. The new versions of AutoTutor detect learners' boredom, confusi...
Sidney K. D'Mello, Scotty D. Craig, Karl Fike, Art...
MMM
2009
Springer
112views Multimedia» more  MMM 2009»
15 years 6 months ago
General Highlight Detection in Sport Videos
Abstract. Attention is a psychological measurement of human reflection against stimulus. We propose a general framework of highlight detection by comparing attention intensity dur...
Reede Ren, Joemon M. Jose