Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

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Detecting faces in images: a survey

The measurement of meaning

to the Human Visual System (HVS).- Visual Attention.- Neurological Substrate of the HVS.- Visual Psychophysics.- Taxonomy and Models of Eye Movements.- Eye Tracking Systems.- Eye Tracking Techniques.- Head-Mounted System Hardware Installation.- Head-Mounted System Software Development.- Head-Mounted System Calibration.- Table-Mounted System Hardware Installation.- Table-Mounted System Software Development.- Table-Mounted System Calibration.- Eye Movement Analysis.- Eye Tracking Methodology.- Experimental Design.- Suggested Empirical Guidelines.- Case Studies.- Eye Tracking Applications.- Diversity and Types of Eye Tracking Applications.- Neuroscience and Psychology.- Industrial Engineering and Human Factors.- Marketing/Advertising.- Computer Science.- Conclusion.

Eye Tracking Methodology: Theory and Practice

Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others relate to coping with fixed focus limitations of cell phone cameras, e.g., in reading digital watermark data. Still others concern user interface improvements. A great number of other features and arrangements are also detailed.

Methods and Systems for Content Processing

Museums hold a wide variety of cultural properties and they organize exhibitions for the public. In history museums, a
number of interpretive materials are necessary to present a specific historical theme. However, due to limitation of
space, the number of displayed materials is severely restricted. There are various types of guidance systems in
museums, however, most systems have not yet responded to visitors' needs. Therefore, a useful guidance system is
necessary to satisfy their needs and also to enhance their understandings of the exhibitions. In order to create such
guidance system, applications of imaging technology can become a solution to overcome these restrictions and meet the
requirements.
In this research, a visual guidance system using a data projector was examined in the National Museum of
Japanese History. In the kimono (traditional Japanese clothing) section, the projector was used to simulate color
changes of the materials under different illuminants. The projector also highlighted areas where annotations were
featured in the kimono. The validity of using the projector system was confirmed by results from an interview survey.
To further develop this visual guidance system, an augmented reality system consisted of cooperation between the
projector and a digital camera was also examined.

An application of projection imaging systems for museum exhibitions

An evaluation of the image quality of a digitized color image based on the power spectrum ratio

In the cosmetics industry, skin color is very important because skin color gives a direct impression of the face. In particular, many people suffer from melanin pigmentation such as liver spots and freckles. However, it is very difficult to evaluate melanin pigmentation using conventional colorimetric values because these values contain information on various skin chromophores simultaneously. Therefore, it is necessary to extract information of the chromophore of individual skins independently as density information. The isolation of the melanin component image based on independent component analysis (ICA) from a single skin image was reported in 2003. However, this technique has not developed a quantification method for melanin pigmentation. This paper introduces a quantification method based on the ICA of a skin color image to isolate melanin pigmentation. The image acquisition system we used consists of commercially available equipment such as digital cameras and lighting sources with polarized light. The images taken were analyzed using ICA to extract the melanin component images, and Laplacian of Gaussian (LOG) filter was applied to extract the pigmented area. As a result, for skin images including those showing melanin pigmentation and acne, the method worked well. Finally, the total amount of extracted area had a strong correspondence to the subjective rating values for the appearance of pigmentation. Further analysis is needed to recognize the appearance of pigmentation concerning the size of the pigmented area and its spatial gradation.

Quantification method for the appearance of melanin pigmentation using independent component analysis

A new measurement method of EOTF (Electro Optical Transfer Function) based on the PCA (Principal Component Analysis) is proposed for colorimetry of RLCD (Reflective type Liquid Crystal Display). Spectral radiance of primary color with different reflectance displayed onto the RLCD under D65 illuminant were measured and analyzed by PCA. It is shown that the reflectance spectra of arbitrary color on the RLCD can be estimated with high accuracy by using those obtained eigen vectors. The new model named PCA model is compared to the conventional GOG (Gain Offset Gamma) model. As a result, it is shown that the PCA model is very significant to the colorimetry of both RLCD and CRT. Introduction In recent years, many kinds of display and printer have been developed to get color image with high quality. Therefore, it is increased to exchange and transform color picture between different devices, particularly from color image onto the CRT and LCD to printer. Therefore it has become increasingly important to do the research on the color management and it is required to develop accurate method for colorimetry of CRT and LCD. One of the most important characteristics of EOTF is a transfer function from digital data to XYZ tristimulus values and spectral radiance of display devices. GOG-model defined as Eq.1 has been widely used to colorimetry of CRT.

Yoichi Miyake

Papers

An application of projection imaging systems for museum exhibitions

An evaluation of the image quality of a digitized color image based on the power spectrum ratio

Quantification method for the appearance of melanin pigmentation using independent component analysis

Evaluation of Image Quality on Reflective-type LCD: Calibration Based on the PCA.

Gonio-spectral based digital archiving and reproduction system for electronic museum