Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence Jg. 29; H. 6; S. 915 - 928
Hauptverfasser: Guoying Zhao, Pietikainen, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Los Alamitos, CA IEEE 01.06.2007
IEEE Computer Society
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Applied sciences
Artificial Intelligence
Biometry - methods
Computation
Computer science; control theory; systems
Computer Security
Dynamics
Exact sciences and technology
Face - anatomy & histology
Face - physiology
Face recognition
Facial
Facial Expression
facial image analysis
Gray-scale
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image motion analysis
Image recognition
Image texture analysis
local binary pattern
Mathematical models
motion
Motion analysis
Pattern analysis
Pattern recognition
Pattern Recognition, Automated - methods
Pattern recognition. Digital image processing. Computational geometry
Recognition
Reproducibility of Results
Robustness
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Spatial databases
Surface layer
Temporal texture
Texture
Video Recording - methods
Texture analysis
Motion estimation
Grey level image
Image processing
motion
Local theory
Pattern recognition
facial image analysis
Texture
Image analysis
Gray scale
local binary pattern
Facies
Database
Robustness
Localization
Cooccurrence analysis
Pattern analysis
Motion analysis
Artificial intelligence
Facial expression
Temporal texture
ISSN:0162-8828, 2160-9292, 1939-3539
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation
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ISSN:0162-8828
2160-9292
1939-3539
DOI:10.1109/TPAMI.2007.1110