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Generating photo-realistic images from multiple style sketches is one of challenging tasks in image synthesis with important applications such as facial composite for suspects. While machine learning techniques have been applied for solving this problem, the requirement of collecting sketch and face photo image pairs would limit the use of the learned model for rendering sketches of different styles...
Cross-resolution face recognition tackles the problem of matching face images with different resolutions. Although state-of-the-art convolutional neural network (CNN) based methods have reported promising performances on standard face recognition problems, such models cannot sufficiently describe images with resolution different from those seen during training, and thus cannot solve the above task...
We propose a new pretreatment for pedestrian detection with convolutional networks. It is widely known that the phenomenon of overlapping feature distribution is common, which leads to overfitting problem. We present a method that divide one category that have overlapping distributed features into multi-subcategories. By this means smooth boundaries can be easily found to separate different subcategories,...
This research proposes a novel Bayesian sparse representation (BSR) method along with extracting facial parameters of SIFT to create sparse dictionaries, which are invariant to rotation, scale, and shift. By using K-means and information theory, a new dictionary called extended dictionary is developed. Compared with conventional orthogonal matching pursuit (OMP) algorithm, the proposed system that...
Feature point detection is an important pre-processing step for quantitative evaluation of facial paralysis. Since the conventional methods such as active shape model (ASM) or active appearance model (AAM) are trained by using normal face and they are not possible to detect the feature points accurately for the face with paralysis. In this paper, we propose an automatic and accurate feature point...
This paper proposes a collaborative vision network that leverages a personal webcam and cameras of the workplace to provide feedback relating to an office-worker's adherence to ergonomic guidelines. This can lead to increased well-being for the individual and better productivity in their work. The proposed system is evaluated with a recorded multi-camera dataset from a regular office environment....
Public speaking is a non-trivial task since it is affected by how nonverbal behaviors are expressed. Practicing to deliver the appropriate expressions is difficult while they are mostly given subconsciously. This paper presents our empirical study on the nonverbal behaviors of presenters. Such information was used as the ground truth to develop an intelligent tutoring system. The system can capture...
Arousal is essential in understanding human behavior and decision-making. In this work, we present a multimodal arousal rating framework that incorporates minimal set of vocal and non-verbal behavior descriptors. The rating framework and fusion techniques are unsupervised in nature to ensure that it can be readily-applicable and interpretable. Our proposed multimodal framework improves correlation...
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...
Recently, analysis of facial morphology and its relationship to genes has received considerable attention. In this paper, we present a scheme of 3D shape alignment for the morphological study of human face. We employ the Cylindrical Polar transform to sample the original 3D shape data which was obtained using the 3D laser scanner. By mapping the sampled data to a 2D image, we can obtain the shape...
Active Appearance Model (AAM) is a popular technique for facial feature point extraction. However, conventional AAM is always viewpoint-generic, which lowers the fitting accuracy. In this paper, a viewpoint-specific AMM is proposed for robust facial point extraction under multi-viewpoint. We investigate three viewpoints, such as 0 degrees, 30 degrees, 60 degrees. The experimental results show a briefly...
We proposed an image based quantitative evaluation method for Facial Paralysis. We selected a left cheek point and a right cheek point as a pair of landmarks for quantitative analysis. We first calculated both moving distances of each landmark in horizontal direction and vertical direction when becoming expression face from the natural face. We showed the movement difference between the left landmark...
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...
The matrix based data representation has been recognized to be effective for face recognition because it can deal with the undersampled problem. One of the most popular algorithms, the two dimensional linear discriminant analysis (2DLDA), has been identified to be effective to encode the discriminative information for training matrix represented samples. However, 2DLDA does not converge in the training...
The hue component of face area in coal mine surveillance images is not true of normal school because of nonlinear characteristic of image sample device in dim-lightening surroundings, and its contrast is clearer than that of non-face area. The skin-color of miner's faces surveillance images of multi angles can be segmented fleetly with the segmentation parameter of hue component which is initialized...
Facial pose synthesis has many useful applications in practice. How to synthesize facial pose images robustly and simply is still a challenging problem. In this paper we proposed a tensor-based subspace learning method (TSL) that makes possible the synthesis of human multi-pose facial images from a single 2D image. We organize 2D multi-pose images in a tensor form and apply tensor decomposition to...
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...
Face recognition is an important technology for managing security, human interface, and so on. Though face recognition techniques have been used in many fields, it still has several problems to be solved, such as robustness to variations of pose, illumination and expression. In this paper, we focus our research on pose-robustness and propose a pose-robust face recognition method based on 3D reconstruction...
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...
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