Nonlinear Color Space and Spatiotemporal MRF for Hierarchical Segmentation of Face Features in Video

Autor: Franck Luthon, Marc Lievin
Přispěvatelé: Laboratoire des images et des signaux (LIS), Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour (LIUPPA), Université de Pau et des Pays de l'Adour (UPPA)
Jazyk: angličtina
Rok vydání: 2004
Předmět:
Eye Movements
Computer science
Facial analysis
Lipreading
Video Recording
entropy power
Information Storage and Retrieval
02 engineering and technology
Eye
face feature
Facial recognition system
Pattern Recognition
Automated
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
motion
0202 electrical engineering
electronic engineering
information engineering
Segmentation
Computer vision
Markov random field
Signal Processing
Computer-Assisted
Computer Graphics and Computer-Aided Design
Markov Chains
020201 artificial intelligence & image processing
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Algorithms
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Color
Image processing
Color space
Sensitivity and Specificity
Image Interpretation
Computer-Assisted
Humans
liptracking
Face detection
Hue
Models
Statistical
business.industry
segmentation
Reproducibility of Results
020206 networking & telecommunications
Pattern recognition
Motion detection
Image segmentation
hue
Image Enhancement
Nonlinear Dynamics
Face
Artificial intelligence
business
Software
Zdroj: IEEE Transactions on Image Processing
IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2004, 13 (1), pp.63-71. ⟨10.1109/TIP.2003.818013⟩
ISSN: 1057-7149
DOI: 10.1109/TIP.2003.818013⟩
Popis: International audience; This paper addresses the design of the image processing stage for face analysis. In human computer interfaces, user-friendliness requires robustness and good quality in image processing. To cope with unsupervised lighting conditions and unknown speaker, two original preprocessing tools are introduced here: a logarithmic color transform and an entropy-based motion threshold. As regards the main processing stage, a hierarchical segmentation scheme based on Markov random fields is proposed, that combines color and motion observations within a spatiotemporal neighborhood. Relevant face regions are thereafter automatically segmented. The good quality of the label fields enables localization and tracking of the face. Geometrical measurements on facial feature edges, such as lips or eyes, are provided by an active contour postprocessing stage. Results are shown both on well-known test sequences, and also on typical sequences acquired from micro and motorized cameras. The robustness and accuracy of the extracted contours are promising for any real-time application aiming at facial communication in unsupervised viewing conditions.
Databáze: OpenAIRE
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