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This paper proposes an efficient expression invariant algorithm for 3D face recognition of subjects. The proposed algorithm uses a surface-based approach to extract automatically and to define geometrically the facial features like eyebrows, nose and lips. These extracted features are used to obtain some unique control points that can be used for matching. The algorithm is tested on Binghamton University...
It has been shown by researchers that using a multimodality approach can help in identifying better clusters in an image collection. The multimodal image features include low-level image features and available text annotations. This approach helps in identifying inherent relationships among different types of features associated with an image. In our approach, we divide images into small tiles and...
In classical image classification approaches, low-level features have been used. But the high dimensionality of feature spaces poses a challenge in terms of feature selection and distance measurement during the clustering process. In this paper, we propose an approach to generate visual keyword and combine both visual and text keywords of the image to form a multimodal vector for image classification...
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