Kazunori Kotani

Objective picture quality scale (PQS) for image coding

A new methodology for the determination of an objective metric for still image coding is reported. This methodology is applied to obtain a picture quality scale (PQS) for the coding of achromatic images over the full range of image quality defined by the subjective mean opinion score (MOS). This PQS takes into account the properties of visual perception for both global features and localized disturbances. The PQS closely approximates the MOS, with a correlation coefficient of more than 0.92, as compared to 0.57 obtained using the conventional weighted mean-square error (WMSE). Extensions and applications of the methodology and of the resulting metric are discussed.

Estimation of eyeglassless facial images using principal component analysis

For facial image analysis, facial parts such as eyes, nose, and mouth are generally focused and used. When these facial parts are hindered by additional objects (eyeglasses, beard, injury, etc.), the feature extraction from facial image will not be accurate. In this paper, we focus on the eyeglass faces because they account for 40% of population in Japan, and present a method of the removal of eyeglass frame in facial images with eyeglasses using principal component analysts. Two approaches are discussed for removal of eyeglasses in facial image. The first method calculates basis vectors from many eyeglassless facial images and one eyeglass facial image, and reconstructs the facial image with the basis vectors which include no feature of eyeglass frame. The second method calculates basis vectors from a set of eyeglassless facial images, and reconstructs the facial image using the values of inner product of the basis vectors and an eyeglass facial image. The former obtains the images which restrain. The features of eyeglass frame while loses the facial individuality a little. The latter obtains a natural eyeglassless facial image.

Block Distortion in Orthogonal Transform Coding--Analysis, Minimization, and Distortion Measure

Psychophysical considerations show that the block-shaped distortion peculiar to orthogonal transform coding (OTC) is ten times more objectionable than random noise distortion. Minimizing the blockshaped distortion is considered here by analyzing the process of generation of coding errors, and the required characteristics of the orthogonal transform function (OTF) are clarified. Computer simulations substantiate its validity. Graphical illustration and measures of the block-shaped distortion are proposed and substantiated. With the aid of these measures, one can evaluate the performance of OTC or a new OTF, if proposed, without conducting visual assessment tests.

Marching cubes method with connectivity

In this paper, we solve the topological problem of isosurfaces generated by the marching cubes method using the approach of combinatorial topology. For each marching cube, we examine the connectivity of polyhedral configuration in the sense of combinatorial topology. For the cubes where the connectivities are not considered, we modify the polyhedral configurations with the connectivity and construct polyhedral isosurfaces with the correct topologies.

Comparison of image coding techniques with a picture quality scale

A newly developed picture quality scale (PQS) provides a numerical measure of image quality for monochrome images well correlated with the mean opinion score. In this paper, we report some results on the evaluation and comparison of image coding methods with such an objective quality measure. The emphasis is given here to the evaluation of the quality of JPEG coding standard. We also review and discuss the important new areas of research that an objective distortion measure now makes possible.

Facial individuality and expression analysis by eigenspace method based on class features or multiple discriminant analysis

This paper presents two methods for the analysis of facial individuality and expression; an eigenspace method based on class features (EMC) and multiple discriminant analysis (MDA). Those methods are used since they derive eigenvectors by which we may extract facial individuality or expression information from a given facial image. The facial individuality and expression analysis can be achieved by projecting the facial image onto the subspace spanned by a set of those eigenvectors. We apply EMC and MDA to the classification of facial images into 50 classes of individuals or into seven classes of facial expressions, and verify their effectiveness with some experimental results.

Facial Expression Recognition by Supervised Independent Component Analysis Using MAP Estimation

Permutation ambiguity of the classical Independent Component Analysis (ICA) may cause problems in feature extraction for pattern classification. Especially when only a small subset of components is derived from data, these components may not be most distinctive for classification, because ICA is an unsupervised method. We include a selective prior for de-mixing coefficients into the classical ICA to alleviate the problem. Since the prior is constructed upon the classification information from the training data, we refer to the proposed ICA model with a selective prior as a supervised ICA (sICA). We formulated the learning rule for sICA by taking a Maximum a Posteriori (MAP) scheme and further derived a fixed point algorithm for learning the de-mixing matrix. We investigate the performance of sICA in facial expression recognition from the aspects of both correct rate of recognition and robustness even with few independent components.

Extraction of Discriminative Patterns from Skeleton Sequences for Human Action Recognition

Emergence of novel techniques, such as the invention of MS Kinect, enables reliable extraction of human skeletons from action videos. Taking skeleton data as inputs, we propose an approach in this paper to extract the discriminative patterns for efficient human action recognition. Each action is considered to consist of a series of unit actions, each of which is represented by a pattern. Given a skeleton sequence, we first automatically extract the key-frames for unit actions, and then label them as different patterns. We further use a statistical metric to evaluate the discriminative capability of each pattern, and define the bag of reliable patterns as local features for action recognition. Experimental results show that the extracted local descriptors could provide very high accuracy in the action recognition, which demonstrate the efficiency of our method in extracting discriminative patterns.

Objective picture quality scale for color image coding

This paper considers an objective picture quality scale for color images (PQScolor). PQScolor approximates the mean opinion score satisfactorily, it takes into account the color perception by using color difference and the properties of visual perception for global features and for localized disturbances. There are two type systems, PQScolor1 is based on Godloves color difference and PQScolor2 is based on H, V, C signal difference. The correlation coefficient between PQScolor (1, 2) and MOS is more than 0.9, which is very high compared to the value 0.34 obtained for the mean color difference scale.

Extraction of a symmetric object for eyeglass face analysis using active contour model

This paper shows an extraction method of a symmetric object for eyeglass face analysis using an active contour model. A contour of eyeglasses hinders a face analysis and synthesis which treats contours of facial parts or partial regions of the face such as eyes, mouth, cheek, eyelid and so on. Methods of active contours extract object contour well. We show an active contour model which is adapted to extract a contour of symmetric object, especially we focus on extracting eyeglass frame using snakes. We study to obtain parameters of snakes by genetic algorithm. We show the good results of applying the snakes in an actual facial image, and synthesize an expressive face with eyeglasses as an application.