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In this paper, we describe a person's brain activity when he or she sees an emoticon at the end of a sentence. An emoticon consists of some characters that resemble the human face and expresses the sender's emotions. With the help of a computer network, we use e-mail, messaging, avatars, and so on, in order to communicate with a recipient. Moreover, we send an emotional expression by using an emoticon at the end of a sentence. In this research, we investigate the effect of an emoticon as nonverbal information, using an fMRI study. The experimental results show that the right and left inferior frontal gyrus were activated and we detect a sentence with an emoticon as the verbal and nonverbal information. © 2011 Wiley Periodicals, Inc. Electron Comm Jpn, 94(5): 17-24, 2011; Published online in Wiley Online Library (). DOI 10.1002/ecj.10311 [ABSTRACT FROM AUTHOR]

In this paper, we describe the brain activity associated with kanji characters expressing emotion, which are placed at the end of a sentence. Japanese use special kanji characters in brackets at the end of sentences in text messages, such as those sent through e-mail and messaging tools. Such kanji characters have the function of expressing the sender's emotions (such as amusement, laughter, sadness, tears), like emoticons. This is a very simple and effective way to convey the sender's emotions and thoughts to the recipient. In this research, we investigate the effects of emotive kanji characters by using an fMRI study. The experimental results show that both the right and left inferior frontal gyri, which have been implicated in verbal and nonverbal information, were activated. We found that sentences with an emotive kanji character were detected as containing both verbal and nonverbal information, and that sentences with emotive kanji characters enrich communication between the sender and the recipient. © 2011 Wiley Periodicals, Inc. Electron Comm Jpn, 94(5): 1-8, 2011; Published online in Wiley Online Library (). DOI 10.1002/ecj.10332 [ABSTRACT FROM AUTHOR]

This paper proposes a new method of similar image retrieval based on the spectral distribution of a multispectral image. The greatest advantage of multispectral imaging is that the color and reflectivity of the object can be determined accurately. In similar image retrieval these physical variables must be discriminated and accurately evaluated. However, in the conventional retrieval method, the color composition ratio is emphasized rather than evaluation of the color (as a physical variable). In the histogram intersection method, for example, which is a form of similarity calculation based on the histogram, the similarity is calculated from only the shape of the histogram, that is, the color composition ratio. Thus, the similarity may be understated simply because the composition ratio is different, which makes this approach unsuitable for multispectral image retrieval, in which the color similarity itself is to be evaluated. This paper proposes a method of retrieval which does not depend on the color composition ratio (a physical variable), but is based on the similarity of the physical variable itself. The method is based on the distance between images, which accurately represents the difference in the physical variables by vector quantization. The effectiveness of the proposed method is demonstrated by an experiment on similar image retrieval for multispectral images. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(11): 19–29, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20273 [ABSTRACT FROM AUTHOR]

In this paper, the authors propose a new object recognition algorithm called the kernel mutual subspace method. The mutual subspace method proposed by Maeda is a superior technique for implementing robust object recognition by performing a principal component analysis on multiple input images. However, like with the ordinary subspace method, a shortcoming of this technique is that performance deteriorates when the category distribution has a nonlinear structure. To solve this problem, the authors theoretically derived a new object recognition algorithm called the kernel mutual subspace method by applying the kernel nonlinear principal component analysis, which is known as a powerful nonlinear principal component analysis method, to the mutual subspace method. When the proposed technique was applied to an individual identification problem based on facial images, it was apparent that the relationship between the degrees of freedom of the object motion and the subspace dimensionality indicating a high recognition rate could be consistently explained through experiments that used the proposed method, which did not differ significantly from the conventional method at the highest precision. They also showed that the proposed technique could be effective for large-scale recognition problems and that its recognition dictionary has a more compact structure. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 88(6): 45–53, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20190 [ABSTRACT FROM AUTHOR]

Conventional features are robust for recognizing either deformed or degraded characters. Most conventional character recognition methods address either one or the other. This paper proposes a feature extraction method that is robust for both of them. Run-length compensation is introduced for approximately extracting directional run-lengths of strokes from degraded handwritten characters. This technique is applied to the conventional feature vector based on directional run-lengths. Experiments for handwritten characters with additive or subtractive noise show that the proposed feature is superior to conventional ones over a wide range of the degree of noise. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 1–9, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10643 [ABSTRACT FROM AUTHOR]

Regularization is widely utilized as an effective means of solving ill-posed problems, where the solution cannot be uniquely determined from the observed data alone. In most past studies, regularization is applied by setting the regularization parameter as a constant over the entire given image plane. The objective of this to derive an adequate solution adapted to the local properties of the object. A method is proposed in which the regularization parameter is determined for each local area of an image by the MDL (minimum description length) principle. More precisely, the following method is proposed. The description length, which represents the adequateness of the solution derived from the penalty functional and the stabilization functional, and the description length of the regularization parameter distribution on the image, are calculated. Then, the regularization parameter is estimated for each local area based on the MDL principle so that the sum of those description lengths is minimized. As a result, the regularization parameter is determined for each discontinuous area and each smooth area of the object. Lastly, the proposed method is applied to optical flow estimation, and its effectiveness is demonstrated by the results of experiments. © 1999 Scripta Technica, Syst Comp Jpn, 30(8): 61–71, 1999 [ABSTRACT FROM AUTHOR]

An adaptive orthogonal transform coding algorithm utilizing the classification technique is presented. Coding efficiency for natural images can be improved by adjusting coding parameters in accordance with the local property of images. ‘Classification’ is used to categorize small areas of an image into classes based on their characteristics. High coding efficiency results from changing coding parameters adaptively according to the classification index. Classification methods using ac energy, binary pattern and vector quantization index ere compared, and the advantage of the classification method with the vector quantization technique is shown. Also, an orthogonal transform coding algorithm with an adaptive variable length ceding method is proposed, and its structure and characteristics are described. A coding parameter normalization method to avoid mismatches between input images and coding parameters is also described. Coding experiments show excellent performance of this algorithm, for example, the number of hits for obtaining 40-dB SNR of monochrome ‘GIRL’ is 0.65 bits/pel, which is 20 percent smaller than conventional methods. [ABSTRACT FROM AUTHOR]

Compact and low-cost video coding equipment is indispensable for the economical realization of visual communication services such as traffic monitoring entertainment relay, etc. This paper describes an LSI oriented coding algorithm which is effective for the compact and economical realization of intra-frame coding equipment. First, an intra-frame combinational difference coding algorithm is proposed. The encoded picture quality obtained using this coding algorithm is sufficient even for complicated scenes of TV signals. The predictive coding circuit LSIs for realizing this coding algorithm are also developed. Moreover, the variable-length word multiplexing circuit is shown to be suitable for LSI, and LSIs for this are also developed, and its compactness is confirmed. A coding experiment was performed by using the developed equipment and it is shown that the equipment is capable of transmitting good quality ITV signals at a 32-Mb/s rate. [ABSTRACT FROM AUTHOR]

Most computer vision problems can be formulated as inverse problems which estimate original data from measured data. This paper proposes a vector field reconstructed method, where the stability and the accuracy of the solution is improved by adaptively controlling the resolution based on the variance of the observed data. First, a method is shown, which evaluates the variance term of the penalty functional in the regularization, based on errors in the observed data. It is shown by Fourier analysis that the aforementioned variance determines the local resolution of the solution. A method is proposed, where the regularization process is controlled so that sampling intervals are long in regions with large variance, and short in regions with small variance. The regularization parameter is decreased gradually with convergence according to the degree of variance. The proposed method is applied to estimate the motion field, and its effectiveness is verified. [ABSTRACT FROM AUTHOR]

In previous analysis of the motion image, the existence of the light source has not particularly been considered. In this paper, the optical model describing the relations among the light source, the object and the view point is introduced. The optical flow estimation problem is discussed based on the gradient method, using the constructed model. First, the relation between the light source and the object model is described as an optical model, and the constraint inherent in the considered scene is derived. As a result, it is shown that the optical flow can be estimated with a high precision also for the scene containing a light source. It is shown that the parameter, which has been considered as a correction term for improving the precision of the optical flow, is a physical parameter indicating the geometrical relation between the light source and the object, from the standpoint of the optical model, Then, not only can the optical flow be estimated with a high precision, but also the information concerning the incident direction from the light source and the reflection coefficients of the object can be newly restored. If the scene is of a simple structure, all parameters that describe the scene, i.e., the information concerning the location of the light source, the object and the camera, as well as the information concerning the shape of the object, and the reflection coefficient of the surface of the object can be estimated. The feasibility of the scene reconstruction is investigated using the CG techniques. [ABSTRACT FROM AUTHOR]

This paper proposes a motion field estimation algorithm based on a shading model from image sequences. Existing motion field estimation algorithm do not render motion field shaded objects with a sufficient degree of accuracy. A shading model is used analyze the scene of shaded objects so that constraint on motion and shade can be well understood and exploited. The proposed algorithm has been implemented and tested against synthetic images. Test results indicated that this algorithm reduces the motion estimation error by about 50 percent compared to the existing algorithm. Further more, the new algorithm also outperforms the old ones when tested against derived from a TV camera. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm that analyzes shading scenes with motion based on a shading model and estimates an incident direction of a light source illuminating an object. If the incident direction of a light source can be estimated, this means that an important environmental parameter of a scene is obtained which enables precise estimation of such parameter as shape and motion in the such. Computer simulations have been performed for computer-generated images and real images, and it was verified that the algorithm works correctly. [ABSTRACT FROM AUTHOR]

The present study investigated whether the perceived quality of a container affects water and snack intake and the subjective qualities of dyadic conversation between undergraduate students. In the experiment, thirty pairs of participants were randomly assigned to two conditions: the high-quality container (HQ) condition, in which participants were provided with high quality glasses from which to drink water, and the low-quality container (LQ) condition, in which participants used ordinary plastic cups. In each condition, pairs of participants were seated at a table and asked to engage in spontaneous and unstructured conversation about certain topics of their choice while consuming water and snacks. The results demonstrate that a greater amount of water was consumed in the LQ condition than in the HQ condition, while the halo effect of container quality increased the perceived quality of the snacks. Furthermore, the results of the self-evaluation for dyadic conversation revealed that the participants in the LQ condition more often reported their conversations to be cooperative, animated and less clumsy than did those in the HQ condition. These results suggest that the accessibility of a container as derived from its perceived quality affects participants’ water and snack consumption and the qualities of dyadic communication. [ABSTRACT FROM AUTHOR]

• Partner presence on unfamiliar food intake was observed. • Ratio of all kinds of unfamiliar food intake was higher in the pair condition. • Subjective evaluations of unfamiliar food did not differ between condition. • Social factors may influence unfamiliar food intake in the pair condition. The present study explored whether partner presence (pair vs. individual) affects unfamiliar food intake. In the experiment, participants were asked to taste pieces of 13 kinds of snacks, including three unfamiliar and ten neutral snacks, and were informed that they did not have to eat a snack if they did not want to. The total amounts and ratios of all kinds of snacks consumed for unfamiliar and neutral snacks were compared between participants in the pair condition and those in the individual condition. Results demonstrated that the ratio of participants who consumed all three kinds of unfamiliar snacks was higher in the pair condition than in the individual condition. Furthermore, the results of communication analyses showed that participants in the pair condition tried unfamiliar snacks even after the peer expressed a negative evaluation of a snack. These results suggest that social motivation such as risk-taking and conformity affect unfamiliar food intake in co-eating situations. [ABSTRACT FROM AUTHOR]