• PNF and Movement
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• v.7 no.4
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• pp.31-36
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• 2009

Many daily activities require people to complete a motor task while walking. Substantial gait decrements during simultaneous attention to a variety of cognitive tasks have been shown by a group of severely injured neurological patients of mixed etiology. And previous studies have shown that the attentional load of a walking-associated task increased with its level of difficulty. The purpose of this study was to analyze subjects' gait changes are affected by the effects of arithmetic task difficulty and performance level. Participants performed a walking task alone, three different Arithmetic tasks while seated, and among them, two kinds of the simillar Arithmetic tasks in combination with walking. Reaction time and accuracy were recorded for two of the Arithmetic tasks. The mean values of the gait were measured using a Timed Up and Go test among 11 with post-stroke patients while walking with and without forward counting (WFC) and backward counting(WBC).There was significant Arithmetic Task Difficulty level between the 10-forward counting task condition(FC) and the 10-backward counting task condition(BC)(p=0.008). The mean values of T.U.G time were significantly higher under backward counting dual-task condition than during a simple walking task(p=0.009) and WFC(p=0.009). The change in T.U.G time during WFC was higher when compared with the change during a simple walking, but there was no significant difference (p=0.246). This study suggesting that a high interference could be linked with a high level of difficulty, whereas adaptive task enabled participants to perfectly share their attention between two concurrent tasks. Future research should determine whether dual task training can reduce gait decrements in dual task situations in people after stroke. And the dual-task-based exercise program is feasible and beneficial for improving walking ability in subjects with stroke.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.417-418
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• 2014

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1023-1024
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• 2008

This paper proposes a pedestrian counting system using line laser. By using a line laser and IR filter, the shapes of pedestrians are easily obtained without complex preprocessing. Also, the directions of pedestrians were able to distinguish by employing gradient information. In the experiment, the proposed method successfully counted the number of people with accuracy of about 97% and with processing time of 24ms per frame.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.612-623
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• 2022

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in a specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. In this paper we present a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.24-34
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• 2021

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. This paper explains the floating population measuring system from the perspective of general consumers(non-experts) who uses current population data. Specifically, it presents a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests

• Fire Science and Engineering
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• v.31 no.6
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• pp.53-59
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• 2017

The purpose of this study is to verify the suitability of the current standards by predicting the density of the occupant load density for discount stores. An internal data survey as well as an actual survey using a People Counting System (PCS) were employed to ascertain the number of occupants and 95% confidence interval of nationwide discount stores. According to the results of the actual survey, the time and days on which the maximum number of occupants were reached was from 16:00 to 18:00 and Christmas Eve and the weekend before New Year's Day, respectively. From the results of the maximum number of occupants, a regression equation was derived from the relationship between the internal data and the amount of sales, and this equation was verified in a previous study. Thus, the internal data of 50 discount stores were analyzed using this process. As a result, the 95% confidence interval was determined to be $2.7{\sim}2.9m^2/pers.$ and the error level was not large compared to the domestic and foreign standards. Therefore, this study proposes that a conservative estimate of the standard occupant load density for discount stores is $2.7m^2/pers.$

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.195-198
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• 2003

Monitoring and analyzing people in video images are important and attract attention from many researchers in computer vision field. In this paper, we propose a new technique by which people overlapped one another in an image can be extracted and counted. After extracting moving people from video images as foreground, their heads are searched by Hough Transform inside the foreground. Since heads are comparatively stable in spite of motion in video images, semicircles along the head tops can be important features to be found in an edge map. In our experiment, the technique successfully separated people who existed at the same vertical positions, which was Impossible by existing techniques. Meanwhile, it showed high dependency on edge information and false results were obtained when the rather were rather incomplete.

• Journal of Radiation Protection and Research
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• v.40 no.4
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• pp.211-215
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• 2015

In case of radiation emergencies, radioactive materials released into environments can cause internal exposure of members of the public. Even though whole body counters are widely used for direct measurement of internally deposited radionuclides, those are not likely to be used at the field to rapidly screen internal exposure. In this study, we estimated the counting efficiencies of portable NaI detector for different size BOMAB phantoms using Monte Carlo transport code to apply handheld gamma spectrometers for rapid screening of internal exposure following radiological accidents. As a result of comparison for two counting geometries, counting efficiencies for sitting model were about 1.1 times higher than those for standing model. We found, however, that differences of counting efficiencies according to different size are higher than those according to counting geometry. Therefore, we concluded that when we assess internal exposure of small size people compared to the reference male, the body size should be considered to estimate more accurate radioactivity in the human body because counting efficiencies of 4-year old BOMAB phantom were about 2.4~3.1 times higher than those of reference male BOMAB phantom.

• Journal of Sensor Science and Technology
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• v.11 no.1
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• pp.28-38
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• 2002

People are important targets for video surveillance and monitoring(VSAM) but difficult to be analyzed. In this paper, a technique to count people in image sequences is dealt as a prerequisite procedure for automatic tracking and behaviour analysis. A group of people is divided at local minima of the line connecting the highest pixels on the binary image of the people extracted from the image taken by a stationary video camera. As the properties of the divided regions vary according to the relative positions of the people in a group, different states are assigned for the completely occluded, partially occluded, completed separated individual, and wrongly divided regions. By analyzing the transition of the states of divided regions, the number of people on the site monitored is estimated. The technique is checked in real experimental situations.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.70-77
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• 2017

Recently, Internet of Things (IoT) and deep learning techniques have affected video surveillance systems in various ways. The surveillance features that perform detection, tracking, and classification of specific objects in Closed Circuit Television (CCTV) video are becoming more intelligent. This paper presents real-time algorithm that can run in a PC environment using only a low power CPU. Traditional tracking algorithms combine background modeling using the Gaussian Mixture Model (GMM), Hungarian algorithm, and a Kalman filter; they have relatively low complexity but high detection errors. To supplement this, deep learning technology was used, which can be trained from a large amounts of data. In particular, an SRGB(Sequential RGB)-3 Layer CNN was used on tracked objects to emphasize the features of moving people. Performance evaluation comparing the proposed algorithm with existing ones using HOG and SVM showed move-in and move-out error rate reductions by 7.6 % and 9.0 %, respectively.