What are the key computer vision techniques and algorithms used in expression detection?
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Computer vision techniques and algorithms used in expression detection include face detection, feature representation, and classification. Various methods have been proposed to address these stages. One approach is based on the Viola and Jones algorithm and principal component analysis . Another method involves the use of Hidden Markov Models for recognizing individual action units (AUs) or AU combinations, along with estimating expression intensity. This method utilizes facial feature point tracking, dense flow tracking with principal component analysis (PCA), and high gradient component detection . Additionally, geometric and transient optical flow features have been used for facial expression recognition, with photogrammetric techniques extracting three-dimensional (3-D) features and optical flow-based motion detection between consecutive images . Dimensionality reduction techniques such as principal component analysis and curvilinear component analysis, along with preprocessing using Gabor filters, have also been employed for expression differentiation .
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| Papers (4) | Insight |
|---|---|
| The key computer vision techniques and algorithms used in expression detection in the provided paper are Gabor filters, Principal Component Analysis (PCA), Curvilinear Component Analysis (CCA), and Support Vector Machine (SVM). | |
| The paper proposes a method for facial expression recognition using geometric and optical flow features. It does not mention specific computer vision techniques or algorithms used for expression detection. | |
| The paper mentions techniques such as eigenfaces, probabilistic eigenfaces, fisher face, support vector machines (SVM), nearest feature lines (NFL), and independent-component analysis for facial expression detection. | |
Open access 01 Jan 1998 | The key computer vision techniques and algorithms used in expression detection include facial feature point tracking, dense flow tracking with PCA, and high gradient component detection. |
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