• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.1-11
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• 2015

A concept of Deep Level Situation Understanding is proposed to realize human-like natural communication (called casual communication) among multi-agent (e.g., humans and robots/machines), where the deep level situation understanding consists of surface level understanding (such as gesture/posture understanding, facial expression understanding, speech/voice understanding), emotion understanding, intention understanding, and atmosphere understanding by applying customized knowledge of each agent and by taking considerations of thoughtfulness. The proposal aims to reduce burden of humans in humans-robots interaction, so as to realize harmonious communication by excluding unnecessary troubles or misunderstandings among agents, and finally helps to create a peaceful, happy, and prosperous humans-robots society. A simulated experiment is carried out to validate the deep level situation understanding system on a scenario where meeting-room reservation is done between a human employee and a secretary-robot. The proposed deep level situation understanding system aims to be applied in service robot systems for smoothing the communication and avoiding misunderstanding among agents.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.69-80
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• 2018

Sensory devices have been developed to help people with disabled or weakened sensory functions. Such devices play a role in collecting and transferring data for the five senses (vision, sound, smell, taste, and tactility) and also stimulating nerves. To provide brain or prosthesis devices with more sophisticated senses, hyper sensory devices with a high resolution comparable to or even better than the human system based on individual neuron cells are essential. As for data collecting components, technologies for sensors with higher resolution and sensitivity, and the conversion of algorithms from physical sensing data to human neuron signals, are needed. Converted data can be transferred to neurons that are responsible for human senses through communication with high security, and neural interfaces with high resolution. When communication deals with human data, security is the most important consideration, and intra-body communication is expected to be a candidate with high priority. To generate sophisticated human senses by modulating neurons, neural interfaces should modulate individual neurons, and therefore a high resolution compared to human neurons (~ several tens of um) with a large area covering neuron cells for human senses (~ several tens of mm) should be developed. The technological challenges for developing sensory devices with human and even beyond-human capabilities have been tackled by various research groups, the details of which are described in this paper.

• Proceedings of the KSPS conference
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• 2006.05a
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• pp.135-138
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• 2006

The communication method between human and robot is one of the important parts for a human-robot interaction. And speech is easy and intuitive communication method for human-being. By using speech as a communication method for robot, we can use robot as familiar way. In this paper, we developed TTS for human-robot interaction. Synthesis algorithms were modified for an efficient utilization of restricted resource in robot. And synthesis database were reconstructed for an efficiency. As a result, we could reduce the computation time with slight degradation of the speech quality.

• Journal of Information Management
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• v.33 no.2
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• pp.49-66
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• 2002

In this paper, the recent trends of user-centered information communication are reviewed, especially focused on Computer-Mediated Communication(CMC) based on internet, Human Factors Engineering, and Human-Computer Interaction(HCI). The result is that human-centered information communication process has influence on the extension of user interface.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.9-16
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• 2018

In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.

• Korean journal of communication and information
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• v.68
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• pp.34-64
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• 2014

This paper analyzed the modes of human communication of the Korean enlightenment era through 9 new-style novels with the assumption that the fictitious world of novels reflect the social realities of that time. The most noticeable fact was that the communication environment of that time were remarkably diversified with the new media, such as newspaper, printed book, postal system, telegraph, telephone, and photo. But the communication of most people was mainly relied on traditional oral communication. In oral communication the hierarchical relationship and age were the most important variable as usual but the formality and etiquette were weakened than Late Chosun Dynasty. The distribution of written culture was enlarged especially by women and lower class. The contact with the foreign cultures which had become possible after the opening of ports brought about intercultural communication. In conclusion it can be said that the communication of people in the enlightenment era was mainly by oral communication but the reliance on the media was enlarged gradually.

• ETRI Journal
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• v.40 no.4
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• pp.511-521
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• 2018

The ability to realize human-motion imitation using robots is closely related to developments in the field of artificial intelligence. However, it is not easy to imitate human motions entirely owing to the physical differences between the human body and robots. In this paper, we propose a work chain-based inverse kinematics to enable a robot to imitate the human motion of upper limbs in real time. Two work chains are built on each arm to ensure that there is motion similarity, such as the end effector trajectory and the joint-angle configuration. In addition, a two-phase filter is used to remove the interference and noise, together with a self-collision avoidance scheme to maintain the stability of the robot during the imitation. Experimental results verify the effectiveness of our solution on the humanoid robot Nao-H25 in terms of accuracy and real-time performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1777-1778
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• 2007

In this paper, We design and implement a humanoid robot, With Educational purpose, which can collaborate and communicate with human. We present an affective human-robot communication system for a humanoid robot, D2, which we designed to communicate with a human through dialogue. D2 communicates with humans by understanding and expressing emotion using facial expressions, voice, gestures and posture. Interaction between a human and a robot is made possible through our affective communication framework. The framework enables a robot to catch the emotional status of the user and to respond appropriately. As a result, the robot can engage in a natural dialogue with a human. According to the aim to be interacted with a human for voice, gestures and posture, the developed Educational humanoid robot consists of upper body, two arms, wheeled mobile platform and control hardware including vision and speech capability and various control boards such as motion control boards, signal processing board proceeding several types of sensors. Using the Educational humanoid robot D2, we have presented the successful demonstrations which consist of manipulation task with two arms, tracking objects using the vision system, and communication with human by the emotional interface, the synthesized speeches, and the recognition of speech commands.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.509-514
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• 2006

Human action recognition is an active research area in computer vision. In this paper, we present a robust method for human action recognition by using combined information of human body shape and motion information with multiple views image sequence. The principal component analysis is used to extract the shape feature of human body and multiple block motion of the human body is used to extract the motion features of human. This combined information with multiple view sequences enhances the recognition of human action. We represent each action using a set of hidden Markov model and we model each action by multiple views. This characterizes the human action recognition from arbitrary view information. Several daily actions of elderly persons are modeled and tested by using this approach and they are correctly classified, which indicate the robustness of our method.