• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.320-322
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• 2021

With the development of wireless Internet technology and the expansion of the game market, various forms of games are being developed that are mounted on various platforms, including mobile platforms. In this environment, ensuring the immersion of the game user's perspective will secure the game's competitiveness, so it is necessary to increase the immersion by satisfying each area presented by the Human Computer Interaction (HCI) theory. To this end, this high school implemented downhill games and experimented with kiosks by applying an interface that recognizes the human body's movements as a way to secure freedom and immersion of game users.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.913-918
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• 2007

Human motion analysis is an important research subject in human-robot interaction (HRI). However, before analyzing the human motion, silhouette of human body should be extracted from sequential images obtained by CCD camera. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. In this paper, we discuss the hybrid silhouette extraction method for detecting and tracking the human motion. The proposed method is to combine and optimize the temporal and spatial gradient information. Also, we propose some compensation methods so as not to miss silhouette information due to poor images. Finally, we have shown the effectiveness and feasibility of the proposed method through some experiments.

• Proceedings of the ESK Conference
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• 1998.04a
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• pp.167-172
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• 1998

Methods of evaluating the physiological activity of the living body are EEG, EOG, Heart rate, and Rectal temperature, etc. In the study of Hagiwara and Araki(1993), they found positive correlations among performance test, physiological measurement, and subjective feeling measurement. Human alertness of pilot directly influences on the flight performance that accomplishes a lot of vigilance task and procedure execution in flight. Accordingly, this paper deals with the quantitative and objective performance test based on tracking error and reaction time by means of the new computer test program into which the perception-motion system of human beings is applies. Throughout this experiment using performance thst, the results suggest that performance capability in state of sleep deprivation 2 hours and alcoholic 0.05 .apaprox. 0.06% in blood were more impaired than one in a normal state, and they further showed statistically significant differences between them, which were influenced by impairment factors of body regulation and pilot's grade. We also obtained the prediction value and the 95% confidence interval of tracking error and reaction time at the normal state for the purpose of distinguishing performance capability between the normal state and the abnormal state. And it is ecpected that the evaluation of human alertness using performance test will be applied to the quantitative assessment of an each pilot's realistic consciousness/attention, and will lead a flight commander to the accurate decision of mission approval prior to a flight.

• International Journal of Contents
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• v.16 no.3
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• pp.1-17
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• 2020

Human motion recognition is essential for user-centric services such as surveillance-based security, elderly condition monitoring, exercise tracking, daily calories expend analysis, etc. It is typically based on the movement data analysis such as the acceleration and angular velocity of a target user. The existing motion recognition studies are only intended to measure the basic information (e.g., user's stride, number of steps, speed) or to recognize single motion (e.g., sitting, running, walking). Thus, a new mechanism is required to identify the transition of single motions for assessing a user's consecutive motion more accurately as well as recognizing the user's body and surrounding situations arising from the motion. Thus, in this paper, we collect the human movement data through Android smartphones in real time for five targeting single motions and propose a mechanism to recognize a consecutive motion including transitions among various motions and an occurred situation, with the state transition model to check if a vulnerable (life-threatening) condition, especially for the elderly, has occurred or not. Through implementation and experiments, we demonstrate that the proposed mechanism recognizes a consecutive motion and a user's situation accurately and quickly. As a result of the recognition experiment about mix sequence likened to daily motion, the proposed adoptive weighting method showed 4% (Holding time=15 sec), 88% (30 sec), 6.5% (60 sec) improvements compared to static method.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1517-1527
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• 2011

This paper presents a motion capture based rehabilitation training system for a lower-limb paretic patient. The system evaluates the rehabilitation status of the patient by using the bend posture of the knees and the weight balance of the body. The posture of both legs is captured with a single camera using the planar mirror. The weight distribution is obtained by the Wii Balance Board. Self-occlusion problem in the tracking of the legs is resolved by using k-nearest neighbor based clustering with body symmetry and local-linearity of the posture data. To do this, we present data normalization and its symmetric property in the normalized vector space.

• Journal of Sensor Science and Technology
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• v.23 no.3
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• pp.149-157
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• 2014

This paper considers the ability of counting and positioning multi-targets by using a mobile UWB radar device. After a background subtraction process, distinguishing between clutters and human body signals, the position of targets will be computed using weighted Gaussian mixture methods. While computer vision offers many advantages, it has limited performance in poor visibility conditions (e.g., at night, haze, fog or smoke). UWB radar can provide a complementary technology for detecting and tracking humans, particularly in poor visibility or through-wall conditions. As we know, for 2D measurement, one method is the use of at least two receiver antennas. Another method is the use of one mobile radar receiver. This paper tried to investigate the position detection of the stationary human body using the movement of one UWB radar module.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.1-8
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• 2017

In this paper, we introduce a technique to retarget human motion data to the humanoid body in a constrained environment. We assume that the given motion data includes detailed interactions such as holding the object by hand or avoiding obstacles. In addition, we assume that the humanoid joint structure is different from the human joint structure, and the shape of the surrounding environment is different from that at the time of the original motion. Under such a condition, it is also difficult to preserve the context of the interaction shown in the original motion data, if the retargeting technique that considers only the change of the body shape. Our approach is to separate the problem into two smaller problems and solve them independently. One is to retarget motion data to a new skeleton, and the other is to preserve the context of interactions. We first retarget the given human motion data to the target humanoid body ignoring the interaction with the environment. Then, we precisely deform the shape of the environmental model to match with the humanoid motion so that the original interaction is reproduced. Finally, we set spatial constraints between the humanoid body and the environmental model, and restore the environmental model to the original shape. To demonstrate the usefulness of our method, we conducted an experiment by using the Boston Dynamic's Atlas robot. We expected that out method can help the humanoid motion tracking problem in the future.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.741-750
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• 2014

This paper presents a real-time motion restoration system for people who need remedial exercise of musculoskeletal based on Inverse Kinematics. A new approach is suggested to recognize a gesture based on restored human motion which is calculated the 3D positions of intermediate joints using 3D positions of body features estimated from images. For generating the 3D candidate positions of intermediate joints which cannot be extracted from images, we apply an Inverse Kinematics theory to compute the target position of intermediate joints. And we can reduce the number of candidate positions by applying the various physical constraints of body. Finally, we can generate the more accurate final position using the Kalman filter for a motion tracking and the relationship between the previous frame information and the candidate positions. The system provide motion information which are rotation angle and height in real-time, therefore the rehabilitation exercises can be performed based on the information and figured out proper exercise for individual status.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.51-59
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• 2012

This paper suggests an efficient method which tracks articulated human body modeled with markov network using disparity map derived from stereo images. The conventional methods which only use color information to calculate likelihood for energy function tend to fail when background has same colors with objects or appearances of object are changed during the movement. In this paper, we present a method evaluating likelihood with both disparity information and color information to find human body parts. Since the human body part are cylinder projected to rectangles in 2D image plane, we use the properties of distribution of disparity of those rectangles that do not have discontinuous distribution. In addition to that we suggest a conditional-messages-update that is able to reduce unnecessary message update of belief propagation. Since the message update has comprised over 80% of the whole computation in belief propagation, the conditional-message-update yields 9~45% of improvements of computational time. Furthermore, we also propose an another speed up method called three dimensional dynamic models assumed the body motion is continuous. The experiment results show that the proposed method reduces the computational time as well as it increases tracking accuracy.