This paper presents a 3D feature-based binocular tracking algorithm for tracking crowded people indoors. The algorithm consists of a two stage 3D feature points grouping method and a robust 3D feature-based tracking method. The two stage 3D feature points grouping method can use kernel-based ISODATA method to detect people accurately even though the part or almost full occlusion occurs among people in surveillance area. The robust 3D feature-based Tracking method combines interacting multiple model (IMM) method with a cascade multiple feature data association method. The robust 3D feature-based tracking method not only manages the generation and disappearance of a trajectory, but also can deal with the interaction of people and track people maneuvering. Experimental results demonstrate the robustness and efficiency of the proposed framework. It is real-time and not sensitive to the variable frame to frame interval time. It also can deal with the occlusion of people and do well in those cases that people rotate and wriggle.

The present research examines the relationship between texture processing and object processing in human vision. Recent computational studies have suggested a difference between the stages of processing. Texture processing can be performed by using statistical parameterization of the response of primary spatial filters. Object processing requires more complex and elaborate computation at a higher stage than texture processing. Our psychophysical experiments are conducted to clarify the relationship of the stages of texture processing and object processing, by focusing on same-object effect which facilitates and speeds attention shifts within the same object and also costs and delays attention shifts if the attention focus moves from one object to another. Texture is composed of lines parallel to, perpendicular to or inside of elongated rectangles used as objects. The same-object effect is measured with reaction time in a cued detection task. Vertical rectangles are used in xperiment 1 and horizontal ones are used in Experiment 2. Experiment 1 shows that the texture lines interrupt the same-object effect and that the interruption is nearly equal if texture lines are added both to the background and the inside of the objects. Experiment 2 yields the result same as Experiment 1. The interruption of the same-object effect by adding texture lines suggests that texture processing affects object processing.

In this study, we achieved predictable control of a wheelchair by changing the existing mapping method of the joystick, which considers the consecutive operations of a motor of a wheelchair, to a new mapping method that corresponds to the internal model of a human being. Since the existing method uses the polar coordinate system, it is not easy at all to use this method to predict either the direction of motion or the operating order for changing the position of the wheelchair according to the requirements of an operator. In order to improve the embodiment, we divided the existing joystick mapping method into two degrees of freedom-one in the vertical axis that can control the velocity and the other, in the horizontal axis for direction control. Based on this division, we implemented a wheelchair model that can be controlled by the electromyography (EMG) signal from the neck and the arm muscles of an operator. This was achieved by mapping the divided degrees of freedom onto the degrees of freedom of the neck and arm of the operator. In this case, since the operator controls the direction of motion by the joint of his/her neck, he/she can move the wheelchair in the desired direction; thus, a more intuitive human interface is implemented.

We describe attempts to have robots behave as embodied knowledge media that will permit knowledge to be communicated through embodied interactions in the real world. The key issue here is to give robots the ability to associate interactions with information content while interacting with a communication partner. Toward this end, we present two contributions in this paper. The first concerns the formation and maintenance of joint intention, which is needed to sustain the communication of knowledge between humans and robots. We describe an architecture consisting of multiple layers that enables interaction with people at different speeds. We propose the use of an affordance-based method for fast interactions. For medium-speed interactions, we propose basing control on an entrainment mechanism. For slow interactions, we propose employing defeasible interaction patterns based on probabilistic reasoning. The second contribution is concerned with the design and implementation of a robot that can listen to a human instructor to elicit knowledge, and present the content of this knowledge to a person who needs it in an appropriate situation. In addition, we discuss future research agenda toward achieving robots serving as embodied knowledge media, and fit the robots-as-embodied-knowledge-media view in a larger perspective of Conversational Informatics.

Since a human object is an important element of the moving pictures being processed by mobile terminals, establishing a human object extraction method encourages dissemination of new applications. In accordance with the requirement of mobile applications, this paper proposes a low-cost human object extraction method, which consists of a face object and a hair object extraction based on their color information and a simple body extraction utilizing the position information of the face object. In the proposed method, skin color and hair color are estimated through color space segmentation, and a human object is effectively extracted by using a radial active contour model. Simulation results of the human object extraction with the use of XScale processor claims that QCIF 15 fps video sequences can be processed in real time.

This paper analyzes automation surprises in human-machine systems with time information. Automation surprises are phenomena such that the underlying machine's behavior diverges from user's intention and may lead to critical situations. Thus, designing human-machine systems without automation surprises is one of fundamental issues to achieve reliable user interaction with the machines. In this paper, we focus on timed human-machine interaction and address their formal aspects. The presented framework is essentially an extension of untimed human-machine interaction and will cover the previously proposed methodologies. We employ timed automata as a model of human-machine systems with time information. Modeling the human-machine systems as timed automata enables one to deal with not only discrete behavior but also time constraints. Then, by introducing the concept of timed simulation of the machine model and the user model, conditions which guarantee the nonexistence of automation surprises are derived. Finally, we construct a composite model in which a machine model and a user model evolve concurrently and show that automation surprises can be detected by solving a reachability problem in the composite model.

iPat/OMP is an interactive parallelization assistance tool for OpenMP. In the present paper, we describe the design concept of iPat/OMP, the parallelization sequence achieved by the tool and its current implementation status. In addition, we present an evaluation of the performance of the implemented functionalities. The experimental results show that iPat/OMP can detect parallelism and create an appropriate OpenMP directive for several for-loops.

In this paper, we propose a construction method of three-dimensional deformable models that represent tree-shaped human organs, such as bronchial tubes, based on results obtained by statistically analyzing the distributions of bifurcation points in the tree-shaped organs. The models are made to be used as standard templates of tree-shaped organs in medical image recognition, and are formed by control points that can be uniquely identified as structural elements of organs such as bifurcation tracheae in bronchial tubes. They can be transfigured based on the statistical validity of relationships between the control points. The optimal state of that transfiguration is determined within the framework of energy minimization. Experimental results from bronchial tubes are shown on actual CT images.

This paper presents a new type of wearable teleoperation system that can be applied to the control of a humanoid robot. The proposed system has self-contained computing hardware with a stereo head-mounted display, a microphone, a set of headphones, and a wireless LAN. It also has a mechanism that tracks arm and head motion by using several types of sensors that detect the motion data of an operator, along with a simple force reflection mechanism that uses vibration motors at appropriate joints. For remote tasks, we use intelligent self-sensory feedback and autonomous behavior, such as automatic grasping and obstacle avoidance in a slave robot, and we feed the information back to an operator through a multimodal communication channel. Through this teleoperation system, we successfully demonstrate several teleoperative tasks, including object manipulation and mobile platform control of a humanoid robot.

Eye contact is an effective means of controlling human communication, such as in starting communication. It seems that we can make eye contact if we simply look at each other. However, this alone does not establish eye contact. Both parties also need to be aware of being watched by the other. We propose a method of bidirectional eye contact satisfying these conditions for human-robot communication. When a human wants to start communication with a robot, he/she watches the robot. If it finds a human looking at it, the robot turns to him/her, changing its facial expressions to let him/her know its awareness of his/her gaze. When the robot wants to initiate communication with a particular person, it moves its body and face toward him/her and changes its facial expressions to make the person notice its gaze. We show several experimental results to prove the effectiveness of this method. Moreover, we present a robot that can recognize hand gestures after making eye contact with the human to show the usefulness of eye contact as a means of controlling communication.

We are developing a helper robot that carries out tasks ordered by the user through speech. The robot needs a vision system to recognize the objects appearing in the orders. It is, however, difficult to realize vision systems that can work in various conditions. Thus, we have proposed to use the human user's assistance through speech. When the vision system cannot achieve a task, the robot makes a speech to the user so that the natural response by the user can give helpful information for its vision system. Our previous system assumes that it can segment images without failure. However, if there are occluded objects and/or objects composed of multicolor parts, segmentation failures cannot be avoided. This paper presents an extended system that tries to recover from segmentation failures using photometric invariance. If the system is not sure about segmentation results, the system asks the user by appropriate expressions depending on the invariant values. Experimental results show the usefulness of the system.

To develop human interfaces such as home information equipment, highly capable word learning ability is required. In particular, in order to realize user-customized and situation-dependent interaction using language, a function is needed that can build new categories online in response to presented objects for an advanced human interface. However, at present, there are few basic studies focusing on the purpose of language acquisition with category formation. In this study, taking hints from an analogy between machine learning and infant developmental word acquisition, we propose a taxonomy-based word-learning model using a neural network. Through computer simulations, we show that our model can build categories and find the name of an object based on categorization.

This paper proposes an adaptive noise canceller (ANC) with low signal-distortion for human-robot communication. The proposed ANC has two sets of adaptive filters for noise and crosstalk; namely, main filters (MFs) and subfilters (SFs) connected in parallel thereto. To reduce signal-distortion in the output, the stepsizes for coefficient adaptation in the MFs are controlled according to estimated signal-to-noise ratios (SNRs) of the input signals. This SNR estimation is carried out using SF output signals. The stepsizes in the SFs are determined based on the ratio of the primary and the reference input signals to cope with a wider range of SNRs. This ratio is used as a rough estimate of the input signal SNR at the primary input. Computer simulation results using TV sound and human voice recorded in a carpeted room show that the proposed ANC reduces both residual noise and signal-distortion by as much as 20 dB compared to the conventional ANC. Evaluation in speech recognition with this ANC reveals that with a realistic TV sound level, as good recognition rate as in the noise-free condition is achieved.

The recognition limit of luminance difference in the human visual system (HVS) has not been studied systematically. In this paper, surround adapted Weber-Fechner fraction is calculated based on the crispening effect. It is found that surround adapted fractions have reduced to 1/3 of the traditional Weber-Fechner fractions. As compared with Breitmeyer's experiments, the presented result is a reasonable one. It can be used as some guide to design the digital display system when a designer needs to decide bit count of digital signal in considering of the limit of brightness level, and as the inspection tool of display manufacturing of brightness smear, defect, and so on.

Recently, wearable devices which use the human body as a transmission channel have been developed. However, there has been a lack of information related the transmission mechanism of such devices in the physical layer. Electro-magnetic communication trials using human body as transmission media have more than a decade's history. However, most of the researches have been conducted by researchers who just want to utilize the fact and practically no physical mechanisms have been researched until recently. Hence, in previous study, the authors proposed calculation models of the wearable transmitter and the receiver attached to the arm using the FDTD method. Moreover, the authors compared the calculated received signal levels to the measured ones by using a biological tissue-equivalent phantom. However, there was little analysis on each component of the propagated signal. In this paper, the authors clarified the transmission mechanism of the wearable device using the human body as a transmission channel from the view point of the interaction between electromagnetic wave and the human body. First, the authors focused their attention on measuring the each component of the propagated signal using a shielded loop antenna. From these results, the favorable direction of electrodes of the transmitter was proposed to use the human body as a transmission channel. As a result, longitudinal direction is effective for sending the signal to the receiver, compared to the transversal direction. Next, the authors investigated the dominant signal transmission channel, because the question of whether the dominant signal channel is in or around the arm had remained unsettled. To clear this question, the authors proposed the calculation model of an arm wearing the transmitter and receiver placed into a hole of a conductor plate. The electric field distribution and received signal voltage was investigated as a function of the gap between the hole of the conductor plate and the surface of the arm. The result indicated that the dominant signal transmission channel is not inside but the surface of the arm because signal seems to be distributed as a surface wave.

Many immersive displays developed in previous researches are strongly influenced by the design concept of the CAVE, which is the origin of the immersive displays. In the view of human-scale interactive system for virtual environment (VE), the existing immersive systems are not enough to use the potential of a human sense further extent. The displays require more complicated structure for flexible extension, and are more restrictive to user's movement. Therefore we propose a novel multi-projector display for immersive VE with haptic interface for more flexible and dynamic interaction. The display part of our system named "D-vision" has a hybrid curved screen which consist of compound prototype with flat and curve screen. This renders images seamlessly in real time, and generates high-quality stereovision by PC cluster and two-pass technology. Furthermore a human-scale string-based haptic device will integrate with the D-vision for more interactive and immersive VE. In this paper, we show an overview of the D-vision and technologies used for the human-scale haptic interface.

Behavioral synchronization between speech and finger tapping provides a novel approach to improving speech recognition accuracy. We combine a sequence of finger tapping timings recorded alongside an utterance using two distinct methods: in the first method, HMM state transition probabilities at the word boundaries are controlled by the timing of the finger tapping; in the second, the probability (relative frequency) of the finger tapping is used as a 'feature' and combined with MFCC in a HMM recognition system. We evaluate these methods through connected digit recognition under different noise conditions (AURORA-2J). Leveraging the synchrony between speech and finger tapping provides a 46% relative improvement in connected digit recognition experiments.

The purpose of this study is to provide a new approach for detection using bio-impedance. This impedance is measured by the four-electrode method. As the impedance changes resulting from ankle, knee, and hip movements depended heavily on electrode placement, we determined the optimal electrode configurations for those movements by searching for high correlation coefficients, large impedance changes, and minimum interferences in ten subjects (Age: 204). Our optimal electrode configurations showed very strong relationships between the ankle joint angle and ankle impedance (γ = -0.9130.03), between the knee joint angle and knee impedance (γ = 0.9440.02), and between the hip joint angle and hip impedance (γ = 0.8230.08). This study showed the possibility that lower leg movement could be easily measured by impedance measurement system with two pairs of skin-electrodes.

In this paper, we introduce a new technology to extract the unique features from an iris image, which uses scale-space filtering. Resulting iris code can be used to develop a system for rapid and automatic human identification with high reliability and confidence levels. First, an iris part is separated from the whole image and the radius and center of the iris are evaluated. Next, the regions that have a high possibility of being noise are discriminated and the features presented in the highly detailed pattern are then extracted. In order to conserve the original signal while minimizing the effect of noise, scale-space filtering is applied. Experiments are performed using a set of 272 iris images taken from 18 persons. Test results show that the iris feature patterns of different persons are clearly discriminated from those of the same person.

This paper considers a motion planning method for humanoid robots. First, we review a modular state net which is a state net representing behavior of a part of the humanoid robots. Each whole body motion of the humanoid robots is represented by a combination of modular state nets for those parts. In order to obtain a feasible path of the whole body, a timed Petri net is used as an abstracted model of a set of all modular state nets. Next, we show an algorithm for constructing nonlinear dynamics which describes a periodic motion. Finally, we extend the state net in order to represent primitive periodic motions and their transition relation so that we can generate a sequence of primitive periodic motions satisfying a specified task.