• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.222-225
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• 2000

Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.267-272
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• 2004

In this Paper, we present analysis on the dynamics of human swing and its realization by a miniaturized humanoid robot. Since the motion of legs is the most important in the swing, the swing system can be approximated as a double pendulum. Based on Lagrangian analysis, the leg motion is designed to make the swing motion as sustained oscillation. In order to detect the peak instant of the swing and to synchronize the leg motion with the swing, we use ADXL acceleration/inclination sensor. The miniaturized humanoid in this paper has total 20 DOFs including 6 DOFs in each leg, 34cm in height, and 2kg in weight. As a result of realization of the swing by the humanoid, the sustained oscillation is verified through experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.157-160
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• 2011

In this paper, We proposed the method of recognition and analysis of human activites using Motion vector in real-time surveillance system. We employs subtraction image techniques to detect blob(human) in the foreground. When MPEG-4 video recording EPZS(Enhanced Predicted Zonal Search) is detected the values of motion vectors were used. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Moving, Non-moving}, {Walking, Running}. Each step was separated using a step-by-step threshold values. We created approximately 150 conditions for the simulation. As a result, We showed a high success rate about 86~98% to distinguish each steps in simulation image.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1075-1082
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• 2007

In this paper, we propose the method of multiple human action recognition on video clip. For being invariant to the change of speed or size of actions, Spatial-Temporal Pyramid method is applied. Proposed method can minimize the complexity of the procedures owing to select Motion Gradient Histogram (MGH) based on statistical approach for action representation feature. For multiple action detection, Motion Energy Image (MEI) of binary frame difference accumulations is adapted and then we detect each action of which area is represented by MGH. The action MGH should be compared with pre-learning MGH having pyramid method. As a result, recognition can be done by the analyze between action MGH and pre-learning MGH. Ten video clips are used for evaluating the proposed method. We have various experiments such as mono action, multiple action, speed and site scale-changes, comparison with previous method. As a result, we can see that proposed method is simple and efficient to recognize multiple human action with stale variations.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.217-222
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• 1995

We propose some applications of image processing techniques to extract quantitative measurements by using a camera system developed in Korea university and Catholic Medical School. From now on the system will be called as KCMOTION. The purpose of this study is to provide basic kinematic and kinetic data for the analysis of human movements and to find the clinical usefulness and reliability of the proposed motion analysis system. Two tests, sit-to-stand (STS) movements and pendulum test, are conducted by the system. The aims of the tests are to identify variability and reliability of KCMOTION to give some quantitative comparisons to the other systems. The result of STS movement are compared to the LOCUS IIID motion analyzer by the ratio of maximum flexion movement per body weight to the actual maximum flexion extension torque per body weight. That result in 29 % and 33 % for hip and knee joint, respectively in KCMOTION and 27 % and 30 % in LOCUS IIID System. The results of the pendulum movements are compared to that of using Cybex and Electrogoniometer with relaxation index, amplitude ratio, swing number and swing time. The results of relaxation index and amplitude ratio of the KCMOTION are between those of the Cybex and Electrogoniometer. We also observed that the KCMOTION detect more natural movement, from the results of swing number and time.

• IE interfaces
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• v.14 no.1
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• pp.95-105
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• 2001

Previous work measurement methods need much time and effort of time study analysts because they have to measure required time through direct observations. In this study, we propose a method which efficiently measures standard times without involvement of human analysts using digital image processing techniques. This method consists of two main steps: motion representation step and cycle segmentation step. In motion representation step, we first detect the motion of any object distinct from its background by differencing two consecutive images separated by a constant time interval. The images thus obtained then pass through an edge detector filter. Finally, the mean values of coordinates of significant pixels of the edge image are obtained. Through these processes, the motions of the observed worker are represented by two time series data of worker location in horizontal and vertical axes. In the second step, called the cycle segmentation step, we extract the frames which have maximum or minimum coordinates in one cycle and store them in a stack, and calculate each cycle time using these frames. In this step we also consider methods on how to detect work delays due to unexpected events such as operator's escapement from the work area, or interruptions. To condude, the experimental results show that the proposed method is very cost-effective and useful for measuring time standards for various work environment.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.66-71
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• 2007

Development of a locomotive mechanism for the capsule type endoscopes will largely enhance their ability to diagnose disease of digestive organs. As a part of it, there should be provided a detection device of their position in human organs for the purpose of observation and motion control. In this paper, a permanent magnet outside human body was employed to project magnetic field on a capsule type endoscope, while its position dependent flux density was measured by three hall-effect sensors which were orthogonally installed inside the capsule. In order to detect the 2-D position data of the capsule with three hall-effect sensors including the roll, pitch and yaw angle, the permanent magnet was extra translated during the measurement. In this way, the 2-D coordinates and three rotation angles of a capsule endoscope on the same motion plane with the permanent magnet could be detected. The working principle and performance test results of the capsule position detection device were introduced in this paper showing that they could be also applied to 6-DOF position detection.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.575-582
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• 2022

In the manufacturing environment, research to minimize robot collisions with human beings have been widespread, but in order to interact with robots, it is important to precisely recognize and predict human actions. In this research, after enhancing performance by applying group normalization to the Hourglass model to detect the operator motion, the skeleton was estimated and data were created using this model. And then, three types of operator's movements were recognized using LSTM. As results of the experiment, the accuracy was enhanced by 1% using group normalization, and the recognition accuracy was 99.6%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.903-909
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• 2018

We propose laser scanner sensor system based walking pattern and tracking method of multiple human. This system uses laser scanners sensors and is applicable to wide and crowded area such as hospital and medical care center. The primary objective of this research is to promote the development of robust, repeatable and transferable software for security system that can automatically detect, track and follow people in public area. We developed the method of human identification for this system. Our method is following: 1. Best-walking pattern data are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the step length of walking human. It becomes possible to conduct human identification even in crowded scenes by estimating the movements of waling human' feet are periodic. In the experiment in the station, some effectiveness of this method became clear.

• Smart Media Journal
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• v.5 no.3
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• pp.49-53
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• 2016

Related researches are progressing that method of non-contact method using the electromagnetic field on the human body by detecting the motion recognition signal is the limitations of time and space, so less than the existing systems. In this paper, we designed the circuit system that can implement the hardware that can detect the electric field signal of the human body non-contact method to increase the recognition rate to screen this digital waveform. The PCB design Used to automatically increase of composition of the circuit and the linkage of the comparator digital waveform with circuit simulation of the system. At same time for evaluate the characteristics of the whole circuit system.