• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.23-30
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• 2005

As a human identification technique, gait recognition has recently gained significant attention. Silhouette-based gait recognition is one of the most popular methods. This paper aims to investigate features that determine the style of walking in silhouette-based gait recognition. Gait can be represented using two cues: static(shape) cue and dynamic(motion) cue. Most recently, research results have been reported in the literature that the characteristics of gait are mainly determined by static cue but not affected by dynamic cue. Unlike this, experimental results in this paper verifies that dynamic cue is as important as and in many cases more important than static cue. For experiments, we use two well-blown gait databases: UBC DB and Southampton Small DB. The images of UBC DB correspond to the 'ordinary' style of walking. The images of Southampton Small DB correspond to the 'disguised' (not ordinary by wearing special clothes or bags) style of walking. As results of experiments, the recognition rate was 100% by static cue and $95.2\%$ by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the recognition rate was $50.0\%$ by static cue and $55.8\%$ by dynamic cue. The risk against correct recognition was 0.91 by static cue and 0.97 by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the risk was 0.98 by static cue and 0.98 by dynamic cue. Consequently, the characteristics of ordinary gait are mainly determined by static cue but that of disguised gait by dynamic cue.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.6-11
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• 2011

In this paper, we propose a gait-based human identification system using eigenfeature regularization and extraction (ERE). First, a gait feature for human identification which is called gait energy image (GEI) is generated from walking sequences acquired from a camera sensor. In training phase, regularized transformation matrix is obtained by applying ERE to the gallery GEI dataset, and the gallery GEI dataset is projected onto the eigenspace to obtain galley features. In testing phase, the probe GEI dataset is projected onto the eigenspace created in training phase and determine the identity by using a nearest neighbor classifier. Experiments are carried out on the CASIA gait dataset A to evaluate the performance of the proposed system. Experimental results show that the proposed system is better than previous works in terms of correct classification rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.215-222
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• 2016

Research on gait recognition and its use is actively underway. This study suggests a method to recognize abnormal gaits of pedestrians. The purposes of the existing research to recognize normal steps are to measure physical activities and to validate people by their walks, but the purpose to recognize abnormal steps in this study is to insure the safe life of pedestrians. There are situations in which pedestrians are unaware of themselves vulnerable and can not ask for help. The purpose of this research is that even if pedestrians are unaware of themselves and there are no spontaneous requests for helps, it is intended for them to escape from dangers and difficulties by adopting the recent IOT technology. Hence, this study analyzes normal pace of pedestrians using the triaxial acceleration sensors, and takes ranges of their normal walking. And then, the steps of pedestrians are measured using the triaxial acceleration sensors, contrasted with their normal walking ranges, and determine whether their steps are normal or not. When it is out of the state for normal paces, a method to determine as abnormal paces is suggested.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.31-40
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• 2006

In this paper, we propose a gait recognition method based on gait silhouette sequences. Features of gait are affected by the variation of gait direction. Therefore, we synthesize silhouettes to canonical form by using planar homography in order to reduce the effect of the variation of gait direction. The planar homography is estimated with only the information which exist within the gait sequences without complicate operations such as camera calibration. Even though gait silhouettes are generated from an individual person, fragments beyond common characteristics exist because of errors caused by inaccuracy of background subtraction algorithm. In this paper, we use the Principal Component Analysis to analyze the deviated characteristics of each individual person. PCA used in this paper, however, is not same as the traditional strategy used in pattern classification. We use PCA as a criterion to analyze the amount of deviation from common characteristic. Experimental results show that the proposed method is robust to the variation of gait direction and improves separability of test-data groups.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.645-647
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• 2018

최근 IoT의 기술의 발달로 사용자 인식에 관한 연구가 주목을 받고 있다. 사용자 인식은 각 사용자만의 특징에 근거하여 특정 사용자를 인식하는 기술이다. 사용자 인식과 관련하여 홍채나 지문인식 등과 같은 생체 인식, 얼굴 인식 그리고 걸음걸이 인식 등에 관한 연구들이 진행되고 있다. 다양한 방식은 각각의 인식률을 높이기 위해 노력하고 있지만, 인식하고자 하는 사용자의 상황에 따라 인식률에 영향을 받게 된다. 본 연구에서는 다양한 방식을 여러 단계로 구성하여 다양한 상황에 놓인 사용자를 인식하기 위한 방법을 연구한다. 제안 시스템은 드론에서 촬영된 영상을 수신하는 것을 기반으로 하여 얼굴인식과 걸음걸이 인식을 이용한 방식이다. 1차적으로 사람의 얼굴을 탐지를 하고, 사람의 얼굴이 탐지되었을 때는 얼굴 인식을 수행한다. 탐지하지 못했을 경우 걸음걸이 인식을 수행하여 인식률을 향상시킨다.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.603-609
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• 2010

This paper introduces an objects recognition algorithm based on SURF(Speeded Up Robust Features) and GP(Genetic Programming) based gaits generation. Combining both methods, a recognition based intelligent walking for quadruped robots is proposed. The gait of quadruped robots is generated by means of symbolic regression for each joint trajectories using GP. A position and size of target object are recognized by SURF which enables high speed feature extraction, and then the distance to the object is calculated. Experiments for objects recognition and autonomous walking for quadruped robots are executed for ODE based Webots simulation and real robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1207-1210
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• 2021

본 본문은 사람의 걸음걸이를 분석을 하여 사람을 인식하는 시스템을 개발한다. mmWave 레이다 센서를 사용하여 사람의 걸음걸이를 인식하고 인식한 데이터를 바탕으로 어떤 사용자인지 분석한다. 데이터를 분석하여 등록된 사용자가 왔을 경우 개방하는 방식으로 출입을 통제하는 개폐 시스템을 사용하고 통신을 사용하여 스마트폰과 통신하여 문이 열리면 실시간으로 사용자가 볼 수 있게 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.622-627
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• 2014

This paper proposes a new method which improves recognition rate on the gait recognition system using wavelet transform, linear discriminant analysis and genetic algorithm. We use wavelet transform to obtain the four sub-bands from the gait energy image. In order to extract feature data from sub-bands, we use linear discriminant analysis. Distance values between training data and four sub-band data are calculated and four weights which are calculated by genetic algorithm is assigned at each sub-band distance. Based on a new fusion distance value, we conducted recognition experiments using k-nearest neighbors algorithm. Experimental results show that the proposed weight fusion method has higher recognition rate than conventional method.

• Korean Journal of Applied Biomechanics
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• v.19 no.4
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• pp.627-636
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• 2009

This study aims to provide a scientific basis for the abstract beauty of dance by analyzing the effects of controlling the breath during the walking motion of Korean dance. The objective of the study is to determine the significance of breathing during Korean dance, as it is externally expressed and technologically segmented, let alone the internal beauty of Korean dance. The results of this study show that the position of the body center and ASIS during the walking motion that uses breath was lower than that of the walking motion that does not use the breath. In addition, in each replacement of the knee joint and ankle joint, a narrow angle, in which bending is used a lot, appeared during the walking motion that uses the breath, but not during the walking gesture that does not use the breath. This occurred during the bending motion. In the first peak point, the vertical ground reaction force during the walking motion that uses the breath was higher than that during the walking motion that does not use the breath.