• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.2
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• pp.133-138
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• 2014

In this paper, a simple but efficient gait recognition method using spatial-temporal silhouette analysis is proposed. For each image sequence, a background subtraction algorithm and a PBAS(pixel based adaptive segmenter) procedure are first used to segment the moving silhouettes of a walking figure. Then, to identify people, the step count and stride length of walking figure is obtained in silhouette images. Experimental results on a CASIA dataset including 124 subjects demonstrate the validity of the proposed method. Also, the proposed system are believed to have a sufficient feasibility for the application to gait recognition.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.237-239
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• 2021

본 논문에서는 YOLO 시스템을 사용하여 보조 보행 기구를 인식 한 후 자동문 속도 조절에 대한 방법을 제안한다. Visual studio, OpenCV, CUDA를 활용하여 보조 보행 기구를 인식이 가능하게 신경망 훈련 및 학습 한 데이터를 기반으로 Raspberry Pi, 카메라 모듈을 활용하여 실시간 모니터링을 통해 보조 보행 기구를 인식하여 자동문의 속도를 조절을 구현했다. 이로써 거동이 불편한 장애인은 원활하게 건물 출입이 가능하다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1361-1368
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• 2020

The system for counting the number of people has traditionally been implemented in various ways. Existing systems include infrared sensors, lasers, cameras, etc. In the case of such an existing system, there are restrictions on space such as ceilings and sides of walls. In this paper, we propose a method of detecting the footsteps of pedestrians using a piezoelectric mat containing a number of piezoelectric sensors and counting the number of pedestrians passing simultaneously by using the data collected from the piezoelectric mat. When pedestrians pass over piezoelectric mats, the collected sensor data was aggregated using SPI communication and transmitted to PC server using TCP/IP communication. Performance analysis shows that approximately 600 step data can be recognized with 99% accuracy. This is to overcome the shortcomings of other counting systems.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.2
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• pp.139-144
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• 2013

Various types of disease in the nervous and musculoskeletal system can change gait, and the gait analysis is very important in determining the progression of the disease. Most methods of analyzing gait are subject to high-priced equipment and spatial restrictions. This study used smart phone images and the walking track analysis program to make a comparative analysis with the existing gait analysis on the basis of the stride length measurements and the changes in the knee joint angle for walking. The test necessary to analyze gait was conducted in seven healthy men, and data about the angle of right and left knee joints and stride length were used to analyze gait. The gait analysis in this study obtained the similar results to the existing ones. The use of the methods suggested in this study will enable gait analysis to be made without high-priced equipment and spatial restrictions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.7
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• pp.479-490
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• 2014

A lower extremity exoskeleton is a robot device that attaches to the lower limbs of the human body to augment or assist with the walking ability of the wearer. In order to improve the wearer's walking ability, the robot senses the wearer's walking locomotion and classifies it into a gait-phase state, after which it drives the appropriate robot motions for each state using its actuators. This paper presents a method by which the robot senses the wearer's locomotion along with a novel classification algorithm which classifies the sensed data as a gait-phase state. The robot determines its control mode using this gait-phase information. If erroneous information is delivered, the robot will fail to improve the walking ability or will bring some discomfort to the wearer. Therefore, it is necessary for the algorithm constantly to classify the correct gait-phase information. However, our device for sensing a human's locomotion has very sensitive characteristics sufficient for it to detect small movements. With only simple logic like a threshold-based classification, it is difficult to deliver the correct information continually. In order to overcome this and provide correct information in a timely manner, a probabilistic gait-phase classification algorithm is proposed. Experimental results demonstrate that the proposed algorithm offers excellent accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.46-52
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• 2004

In this paper, we introduce a case study of developing a miniature humanoid robot which has 16 degrees of freedom, 42 cm heights, and 1.5kg weights. For easy implimentation, the integrated RC-servo motors are adopted as actuators and a digital camera is equipped on its head. So, it can transmit vision data to a remote host computer via wireless modem. The robot can perform staircase walking as well as straight walking and turning to any direction. The user-interface program running on the host computer contains a robot graphic simulator and a motion editor which are used to generate and verify the robot's walking motion. The experimental results show that the robot has various walking capability including straight walking, turning, and stairs walking.

• Journal of IKEEE
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• v.19 no.2
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• pp.155-159
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• 2015

In this paper, we propose a method for pedestrian detection in real time video and reducing the calculation time of the HOG features for pedestrian detection. When the pedestrian is detected in real-time image, the next frame is detected by using a previously detected region information. In addition, we used a PSO to detect a pedestrian may appear in a region other than a pedestrian is detected quickly. the performance was measured for MIT, INRIA dataset, showed a performance increase of about 82% than the conventional method.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.83-89
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• 2021

In this paper, we propose an algorithm that provide services to consumers who want to conduct business by scientifically and systematically analyzing the number of pedestrians in a specific area over a specific period of time. In this paper, we proposed the algorithm to analyze the commercial area using the pedestrian-detect algorithm in the particular region using YOLO, one of the deep learning techniques. And with one image per minute in the images, the number of pedestrians is identified and this information is used for the analysis of business district on interesting area and time, systematically and objectively.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.59-66
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• 2016

For the performance experiments of databases systems with moving object databases, we need moving object trajectory data sets. For example, benchmark data sets of moving object trajectories are required for experiments on query processing of moving object databases. For those reasons, several tools have been developed for generating moving objects in Euclidean spaces or road network spaces. Indoor space differs from outdoor spaces in many aspects and moving object generator for indoor space should reflect these differences. Even some tools were developed to produce virtual moving object trajectories in indoor space, the movements generated by them are not realistic. In this paper, we present a moving object generation tool for indoor space. First, this tool generates trajectories for pedestrians in an indoor space. And it provides a parametric generation of trajectories considering not only speed, number of pedestrians, minimum distance between pedestrians but also type of spaces, time constraints, and type of pedestrians. We try to reflect the patterns of pedestrians in indoor space as realistic as possible. For the reason of interoperability, several geospatial standards are used in the development of the tool.