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A probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions
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Outgoing claims: the papers this work cites, builds on, or argues with.
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The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields
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Real-time lip tracking for audio-visual speech recognition applications
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Contour tracking by stochastic propagation of conditional density
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Learning dynamics of complex motions from image sequences
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A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
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Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
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A tutorial on hidden Markov models and selected applications in speech recognition
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Image mosaicing for tele-reality applications
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Learning parameterized models of image motion
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Learning and recognizing human dynamics in video sequences
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Multi-modal tracking of faces for video communications
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Temporal classification of natural gesture and application to video coding
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A mixed-state condensation tracker with automatic model-switching
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Parameterized modeling and recognition of activities
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Recognition and interpretation of parametric gesture
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Stochastic Simulation Algorithms for Dynamic Probabilistic Networks
What points at this work
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Trajectory Guided Recognition Of Hand Gestures Having Only Global Motions
inferred← citeshttps://doi.org/10.5302/j.icros.2012.18.4.328openalex-snapshot
A Robust Fingertip Extraction and Extended CAMSHIFT based Hand Gesture Recognition for Natural Human-like Human-Robot Interaction
inferred← citeshttps://doi.org/10.5772/14261openalex-snapshot
A Block Matching Technique for Object Tracking Based on Peripheral Increment Sign Correlation Image
inferred← citeshttps://doi.org/10.5772/4958openalex-snapshot
Manipulative Action Recognition for Human-Robot Interaction
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