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Face Hallucination is, one of a learning-based super-resolution technique that can reconstruct a high-resolution image using only one low-resolution image. However, there are often some detailed high-frequency components of the reconstructed image that cannot be recovered using this method. In this study, we proposed a high-frequency compensated face hallucination method for enhancing reconstruction...
Incremental principal component analysis (IPCA) has been of great interest in computer vision and machine learning. In this paper, we introduce a new incremental learning procedure for principal component analysis (PCA). The proposed method can keep an accurate track of the mean of the data, and can deal with a set of new observed data in batch each time in subspace updating. Furthermore, a weighting...
Super-resolution (SR) enhancement from multi-frame low-resolution (LR) images (multi-frame super-resolution) has been a well-studied topic in the literature. Image registration is the most important part for multi-frame super-resolution, and accurate alignment of LR images would contribute a critical role for the final success of SR image reconstruction. In this paper, we propose to combine the Principle...
Image warping and morphing are important visual effect tools in entertainment industry and other research fields. We developed a prototypical automatic facial image manipulation system (AFIM) for face morphing and shape normalization (warping). In our AFIM system, there are two main functions: (1) warping a facial image to a target image (face shape normalization), (2) generation of inter- or intra-personal...
In this paper, we proposed an automatic facial caricaturing system based on multi-view Active Shape Model (ASM). The ASM is used for automatic extraction of feature points. But it is difficult to apply the conventional ASM to facial images with pose variations. We developed a multi-view ASM bank, which includes various ASMs corresponding to each pose. The multi-view ASMs can extract feature points...
At present there are many methods that could deal well with frontal view face recognition when there is sufficient number of representative training samples. There into, subspace learning method such as principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA) are a very hot research topic in this field. However, in some face recognition system, the...
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