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» Eye Tracking Using Markov Models
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FLAIRS
2010
13 years 10 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
PR
2000
189views more  PR 2000»
13 years 7 months ago
LAFTER: a real-time face and lips tracker with facial expression recognition
This paper describes an active-camera real-time system for tracking, shape description, and classi"cation of the human face and mouth expressions using only a PC or equivalen...
Nuria Oliver, Alex Pentland, François B&eac...
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 7 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
RAS
2000
187views more  RAS 2000»
13 years 7 months ago
Detection, tracking, and classification of action units in facial expression
Most of the current work on automated facial expression analysis attempt to recognize a small set of prototypic expressions, such as joy and fear. Such prototypic expressions, how...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...
NIPS
2008
13 years 9 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...