We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a "touch and connect" intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

Human detection has witnessed significant development in recent years. The introduction of cascade structure and integral histogram has greatly improved detection speed. But real-time detection is still only possible for sparse scan of 320 240 sized images. In this work, we propose a matrix-based structure to reorganize the computation structure of window-scanning detection algorithms, as well as a new pre-processing method called Hierarchical HOG Matrices (HHM) in place of integral histogram. Our speed-up scheme can process 320 240 sized images by dense scan (≈ 12000 windows per image) at the speed of about 30 fps, while maintaining accuracy comparable to the original HOG + cascade method.

Visual adaptation is a universal phenomenon associated with human visual system. This adaptation affects not only the perception of low-level visual systems processing color, motion, and orientation, but also the perception of high-level visual systems processing complex visual patterns, such as facial identity and expression. Although it remains unclear for the mutual interaction mechanism between systems at different levels, this issue is the key to understand the hierarchical neural coding and computation mechanism. Thus, we examined whether the low-level adaptation influences on the high-level aftereffect by means of cross-level adaptation paradigm (i.e. color, figure adaptation versus facial identity adaptation). We measured the identity aftereffects within the real face test images on real face, color chip and figure adapting conditions. The cross-level mutual influence was evaluated by the aftereffect size among different adapting conditions. The results suggest that the adaptation to color and figure contributes to the high-level facial identity aftereffect. Besides, the real face adaptation obtained the significantly stronger aftereffect than the color chip or the figure adaptation. Our results reveal the possibility of cross-level adaptation propagation and implicitly indicate a high-level holistic facial neural representation. Based on these results, we discussed the theoretical implication of cross-level adaptation propagation for understanding the hierarchical sensory neural systems.

We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

The topic of Human Computer Interaction (HCI) has been gathering more and more scientific attention of late. A very important, but often undervalued area in this field is human engagement. That is, a person's commitment to take part in and continue the interaction. In this paper we describe work on a humor-equipped casual conversational system (chatterbot) and investigate the effect of humor on a user's engagement in the conversation. A group of users was made to converse with two systems: one with and one without humor. The chat logs were then analyzed using an emotive analysis system to check user reactions and attitudes towards each system. Results were projected on Russell 's two-dimensional emotiveness space to evaluate the positivity/negativity and activation/deactivation of these emotions. This analysis indicated emotions elicited by the humor-equipped system were more positively active and less negatively active than by the system without humor. The implications of results and relation between them and user engagement in the conversation are discussed. We also propose a distinction between positive and negative engagement.

Objective assessment of image and video quality should be based on a correct understanding of subjective assessment by human observers. Previous models have incorporated the mechanisms of early visual processing in image quality metrics, enabling us to evaluate the visibility of errors from the original images. However, to understand how human observers perceive image quality, one should also consider higher stages of visual processing where perception is established. In higher stages, the visual system presumably represents a visual scene as a collection of meaningful components such as objects and events. Our recent psychophysical studies suggest two principles related to this level of processing. First, the human visual system integrates shape and color signals along perceived motion trajectories in order to improve visibility of the shape and color of moving objects. Second, the human visual system estimates surface reflectance properties like glossiness using simple image statistics rather than by inverse computation of image formation optics. Although the underlying neural mechanisms are still under investigation, these computational principles are potentially useful for the development of effective image processing technologies and for quality assessment. Ideally, if a model can specify how a given image is transformed into high-level scene representations in the human brain, it would predict many aspects of subjective image quality, including fidelity and naturalness.

Adjustment of a certain parameter in the course of performing a trajectory task such as drawing or gesturing is a common manipulation in pen-based interaction. Since pen tip information is confined to x-y coordinate data, such concurrent parameter adjustment is not easily accomplished in devices using only a pen tip. This paper comparatively investigates the performance of inherent pen input modalities (Pressure, Tilt, Azimuth, and Rolling) and Key Pressing with the non-preferred hand used for precision parameter manipulation during pen sliding actions. We elaborate our experimental design framework here and conduct experimentation to evaluate the effect of the five techniques. Results show that Pressure enabled the fastest performance along with the lowest error rate, while Azimuth exhibited the worst performance. Tilt showed slightly faster performance and achieved a lower error rate than Rolling. However, Rolling achieved the most significant learning effect on Selection Time and was favored over Tilt in subjective evaluations. Our experimental results afford a general understanding of the performance of inherent pen input modalities in the course of a trajectory task in HCI (human computer interaction).

To realize the harmonious cooperation with the operator, the man-machine cooperative system must be designed so as to accommodate with the characteristics of the operator's skill. One of the important considerations in the skill analysis is to investigate the switching mechanism underlying the skill dynamics. On the other hand, the combination of the feedforward and feedback schemes has been proved to work successfully in the modeling of human skill. In this paper, a new stochastic switched skill model for the sliding task, wherein a minimum jerk motion and feedback schemes are embedded in the different discrete states, is proposed. Then, the parameter estimation algorithm for the proposed switched skill model is derived. Finally, some advantages and applications of the proposed model are discussed.

The Finite-Difference Time-Domain (FDTD) technique is presented in this paper as an estimation method for radio propagation prediction in large and complex wireless local area network (WLAN) environments. Its validity is shown by comparing measurements and Ray-trace method with FDTD data. The 2 GHz (802.11b/g) and 5 GHz (802.11a) frequency bands are used in both the calculations and experiments. The electric field (E-field) strength distribution has been illustrated in the form of histograms and cumulative ratio graphs. By using the FDTD method to vary the number of human bodies in the environment, the effects on E-field distribution due to human body absorption are also observed for 5 GHz WLAN design.

For the acquisition of visual information, the nonuniform sampling process by photoreceptors on the retina occurs at the earliest stage of visual processing. From objects of interest, the human eye receives high visual resolution through nonuniform distribution of photoreceptors. Therefore, this paper proposes auto exposure and focus algorithms for the real-time video camera system based on the visual characteristic of the human eye. For given moving objects, the visual weight is modeled for quantifying the visual importance and the associated auto exposure and focus parameters are derived by applying the weight to the traditional numerical expression, i.e., the DoM (Difference of Median) and Tenengrad methods for auto focus.

Wireless communication devices in the field of medical implant, such as cardiac pacemakers and capsule endoscopes, have been studied and developed to improve healthcare systems. Especially it is very important to know the range and position of each device because it will contribute to an optimization of the transmission power. We adopt the time-based approach of position estimation using ultra wideband signals. However, the propagation velocity inside the human body differs in each tissue and each frequency. Furthermore, the human body is formed of various tissues with complex structures. For this reason, propagation velocity is different at a different point inside human body and the received signal so distorted through the channel inside human body. In this paper, we apply an adaptive template synthesis method in multipath channel for calculate the propagation time accurately based on the output of the correlator between the transmitter and the receiver. Furthermore, we propose a position estimation method using an estimation of the propagation velocity inside the human body. In addition, we show by computer simulation that the proposal method can perform accurate positioning with a size of medical implanted devices such as a medicine capsule.

In this paper, a perceptually adaptive watermarking scheme for color images is proposed in order to achieve robustness and transparency. A new just noticeable distortion (JND) estimator for color images is first designed in the wavelet domain. The key issue of the JND model is to effectively integrate visual masking effects. The estimator is an extension to the perceptual model that is used in image coding for grayscale images. Except for the visual masking effects given coefficient by coefficient by taking into account the luminance content and the texture of grayscale images, the crossed masking effect given by the interaction between luminance and chrominance components and the effect given by the variance within the local region of the target coefficient are investigated such that the visibility threshold for the human visual system (HVS) can be evaluated. In a locally adaptive fashion based on the wavelet decomposition, the estimator applies to all subbands of luminance and chrominance components of color images and is used to measure the visibility of wavelet quantization errors. The subband JND profiles are then incorporated into the proposed color image watermarking scheme. Performance in terms of robustness and transparency of the watermarking scheme is obtained by means of the proposed approach to embed the maximum strength watermark while maintaining the perceptually lossless quality of the watermarked color image. Simulation results show that the proposed scheme with inserting watermarks into luminance and chrominance components is more robust than the existing scheme while retaining the watermark transparency.

The medical care day by day and more and more is associated with and reliant upon concepts and advances of electronics and electromagnetics. Numerous medical devices are implanted in the body for medical use. Tissue implanted devices are of great interest for wireless medical applications due to the promising of different clinical usage to promote a patient independence. It can be used in hospitals, health care facilities and home to transmit patient measurement data, such as pulse and respiration rates to a nearby receiver, permitting greater patient mobility and increased comfort. As this service permits remote monitoring of several patients simultaneously it could also potentially decrease health care costs. Advancement in radio frequency communications and miniaturization of bioelectronics are supporting medical implant applications. A central component of wireless implanted device is an antenna and there are several issues to consider when designing an in-body antenna, including power consumption, size, frequency, biocompatibility and the unique RF transmission challenges posed by the human body. The radiation characteristics of such devices are important in terms of both safety and performance. The implanted antenna and human body as a medium for wireless communication are discussed over Medical Implant Communications Service (MICS) band in the frequency range of 402-405 MHz.

The body area network (BAN) has attracted attention because of its potential for high-grade wireless communication technology and its safety and high durability. Also, human area transmission of a BAN propagating at an ultra-wide band (UWB) has been demonstrated recently. When considering the efficiency of electromagnetic (EM) propagation inside the human body for BAN and hyperthermia treatment using RF, it is important to determine the mechanism of EM dissipation in the human body. A body heating system for hyperthermia must deposit EM energy deep inside the body. Also, it is important that the EM field generated by the implant system is sufficiently strong. In this study, the specific absorption rate (SAR) distribution is simulated using an EM simulator to consider the biological transmission mechanism and its effects. To utilize the EM field distribution using an implant system for hyperthermia treatment, the SAR distribution inside the human body is simulated. As a result, the SAR distribution is concentrated on the surface of human tissue, the muscle-bolus interface, the pancreas, the stomach, the spleen and the regions around bones. It can also be concentrated in bone marrow and cartilage. From these results, the appropriate location for the implant system is revealed on the basis of the current distribution and differences in the wave impedance of interfacing tissues. The possibility of accurate data transmission and suitable treatment planning is confirmed.

In human-machine systems, a user gets abstracted information of a machine via an interface and operates it referring to a manual. If a manual has an erroneous description leading to automation surprises, the user may be lost in his/her operations so that he/she may make a serious human error. In this paper, we propose an algorithm for generating a manual by which automation surprises never occur. We model the machine and the interface as a discrete event system and a mapping from machine's state to a display of the interface, respectively. First, we represent a manual as a finite language and model behavior of the system operated by the user with the manual as a tree called an operational tree. Next, we characterize three automation surprises using the tree. Finally, we propose an algorithm for generating an operational tree by which the machine reaches a target state.

A system which employs a stylus as an input device is suitable for creative activities like writing and painting. However, such a system does not always provide the user with a GUI that is easy to operate using the stylus. In addition, system usability is diminished because the stylus is not always integrated into the system in a way that takes into consideration the features of a pen. The purpose of our research is to improve the usability of a system which uses a stylus as an input device. We propose shortcut actions, which are interaction techniques for operation with a stylus that are controlled through a user's hand motions made in the air. We developed the Context Sensitive Stylus as a device to implement the shortcut actions. The Context Sensitive Stylus consists of an accelerometer and a conventional stylus. We also developed application programs to which we applied the shortcut actions; e.g., a drawing tool, a scroll supporting tool, and so on. Results from our evaluation of the shortcut actions indicate that users can concentrate better on their work when using the shortcut actions than when using conventional menu operations.

Wavelet tree based watermarking algorithms are using the wavelet coefficient energy difference for copyright protection and ownership verification. WTQ (Wavelet Tree Quantization) algorithm is the representative technique using energy difference for watermarking. According to the cryptanalysis on WTQ, the watermark embedded in the protected image can be removed successfully. In this paper, we present a novel differential energy watermarking algorithm based on the wavelet tree group modulation structure, i.e. WTGM (Wavelet Tree Group Modulation). The wavelet coefficients of host image are divided into disjoint super trees (each super tree containing two sub-super trees). The watermark is embedded in the relatively high-frequency components using the group strategy such that energies of sub-super trees are close. The employment of wavelet tree structure, sum-of-subsets and positive/negative modulation effectively improve the drawbacks of the WTQ scheme for its insecurity. The integration of the HVS (Human Visual System) for WTGM provides a better visual effect of the watermarked image. The experimental results demonstrate the effectiveness of our algorithm in terms of robustness and imperceptibility.

Image enhancement plays an important role in many machine vision applications on images captured in low contrast and low illumination conditions. In this study, we propose a new method for image enhancement based on analysis on embedded surfaces of images. The proposed method gives an insight into the relationship between the image intensity and image enhancement. In our method, scaled surface area and the surface volume are proposed and used to reconstruct the image iteratively for contrast enhancement, and the illumination of the reconstructed image can also be adjusted simultaneously. On the other hand, the most common methods for measuring the quality of enhanced images are Mean Square Error (MSE) or Peak Signal-to-Noise-Ratio (PSNR) in conventional works. The two measures have been recognized as inadequate ones because they do not evaluate the result in the way that the human vision system does. This paper also presents a new framework for evaluating image enhancement using both objective and subjective measures. This framework can also be used for other image quality evaluations such as denoising evaluation. We compare our enhancement method with some well-known enhancement algorithms, including wavelet and curvelet methods, using the new evaluation framework. The results show that our method can give better performance in most objective and subjective criteria than the conventional methods.

A new type of humanoid robot arm which can coexist and be interactive with human beings are looked for. For the purpose of implementation of human smooth and fast movement to a pneumatic robot, the author used a humanoid robot arm with pneumatic agonist-antagonist actuators as endoskeletons which has control mechanism in the stiffness of each joint, and the controllability was experimentally discussed. Using Kitamori 's method to experimentally decide the control gains and using I-PD controller, three joints of the humanoid robot arm were experimentally controlled. The damping control algorithm was also adopted to the wrist joint, to modify the speed in accordance with the power. The results showed that the controllability to step-wise input was less than one degree in error to follow the target angles, and the time constant was less than one second. The simultaneous input of command to three joints was brought about the overshoot of about ten percent increase in error. The humanoid robot arm can generate the calligraphic motions, moving quickly at some times but slowly at other times, or particularly softly on some occasions but stiffly on other occasions at high accuracy.

In this paper, we show that motion sharpening phenomenon can be explained as a form of visual masking for a special case where a video sequence is composed of alternate frames with different level of sharpness. A frame of higher sharpness behaves to mask the ambiguity of a subsequent frame of lower sharpness and hence preserves the perceptive quality of the whole sequence. Borrowing the mechanism for visual masking, we formulated a quantitative model for deriving the minimum spatial frequency conditions which preserves the subjective quality of the frames being masked. The quantitative model takes into account three fundamental properties of the video signals, namely the size of motion, average luminance and the power of each frequency components. The psychophysical responses towards the changes of these properties are obtained through subjective assessment tests using video sequences of simple geometrical patterns. Subjective experiments on natural video sequences show that more than 75% of viewers could make no distinction between the original sequence and the one processed using the quantitative model.