• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.88-95
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• 2022

Detecting anomalies in human movement is an important task in industrial applications, such as monitoring industrial disasters or accidents and recognizing unauthorized factory intruders. In this paper, we propose an abnormal worker movement detection system based on data stream processing and hierarchical clustering. In the proposed system, Apache Spark is used for streaming the location data of people. A hierarchical clustering-based anomalous trajectory detection algorithm is designed for detecting anomalies in human movement. The algorithm is integrated into Apache Spark for detecting anomalies from location data. Specifically, the location information is streamed to Apache Spark using the message queuing telemetry transport protocol. Then, Apache Spark processes and stores location data in a data frame. When there is a request from a client, the processed data in the data frame is taken and put into the proposed algorithm for detecting anomalies. A real mobility trace of people is used to evaluate the proposed system. The obtained results show that the system has high performance and can be used for a wide range of industrial applications.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.802-805
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• 2003

The aim of this paper is to provide a guide to those methods of train detection which are available, or are likely to become available, to the designer of train control or other relevant systems. In broad terms, train detection may be defined as the process of generating information which describes the location and movement of trains. Train detection information is difficult to define in isolation. Consider, for example, the train detection information required in a modern train control system. This may vary considerably : in a future high performance train control system, it might be necessary to know the precise position, direction of movement, speed, and possibly even the acceleration or braking, of all trains in the control area : in a less demanding application, it might be sufficient to know only the location of trains in terms of the occupation of sections of track.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.269-272
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• 2009

The environment of Ubiquitous in terms of improvement is being expanded to various fields and time enabled system. Thus, a real-time spatial information management system has been developed by integrating a human movement detection system into a SICS(Spatial Information Control System) engine that can integrally manage inside spatial information extracted from 3D CAD and outside spatial information of GIS. The add-on program was developed to extract spatial information necessary for the SICS engine from 3D CAD information, and a human movement detection system was developed. Test bed was operated for 2weeks and indoor human flow information was found out by zone. Also, the direction of future research was decided through a test bed.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1421-1431
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• 2005

There are two methods in 3-D sound reproduction: a surround system, like 3.1 channel method and a binaural system using 2-channel method. The binaural system utilizes the sound localization principle of a human using two ears. Generally, a crosstalk between each channel of 2-channel loudspeaker system should be canceled to produce a natural 3-D sound. To solve this problem, it is necessary to trace a head movement. In this paper, we propose a new algorithm to correctly trace the head movement of a listener. The Proposed algorithm is based on the detection of face and eye. The face detection uses the intensity of an image and the position of eyes is detected by a mathematical morphology. When the head of the listener moves, length of borderline between face area and eyes may change. We use this information to the tracking of head movement. A computer simulation results show That head movement is effectively estimated within +10 margin of error using the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.250-252
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• 2004

The aim of this paper is to provide a guide to those methods of train detection which are available, or are likely to become available, to the designer of train control or other relevant systems. In broad terms, train detection may be defined as the process of generating information which describes the location and movement of trains. Train detection information is difficult to define in isolation. Consider, for example, the train detection information required in a modern train control system. This may vary considerably : in a future high performance train control system, it might be necessary to know the precise position, direction of movement, speed, and possibly even the acceleration or braking, of all trains in the control area : in a less demanding application, it might be sufficient to know only the location of trains in terms of the occupation of sections of track.

• Journal of The Korean Digital Architecture Interior Association
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• v.8 no.2
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• pp.13-20
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• 2008

As buildings have been constructed higher and more complicated recently, the activities of the residents occurred in those multiplex buildings have also become more various. As a result, possibility and the size of the damage from the disaster like a fire are getting larger. So, many studies for preventing the damage in refuge situation are being conducted. In this study, a new process for finding the optimum refuge path is presented, which is different from existing methods. This new method operates by using the human movement detection system in the building for real time. And the process also shows the new way which can shorten the number of calculation for deciding the optimum refuge path. That new way is to make variables such as the velocity of smoke and person movement into a constant. Finally it will be applied to a multiplex building.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.266-284
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• 2009

The challenges of rapidly growing numbers of mobile nodes in IPv6-based networks are being faced by mobile computing researchers worldwide. Recently, IETF has standardized Mobile IPv6 and Fast Handover for Mobile IPv6(FMIPv6) for supporting IPv6 mobility. Even though existing literatures have asserted that FMIPv6 generally improves MIPv6 in terms of handover speed, they did not carefully consider the details of the whole handover procedures. Therefore, in conventional protocols, the handover process reveals numerous problems manifested by a time-consuming network layer based movement detection and latency in configuring a new care of address with confirmation. In this article, we study the impact of the address configuration and confirmation procedure on the IP handover latency. To mitigate such effects, we propose a new scheme which can reduce the latency taken by the movement detection, address configuration and confirmation from the whole handover latency. Furthermore, a mathematical analysis is provided to show the benefits of our scheme. In the analysis, various parameters are used to compare our scheme with the current procedures, while our approach is focused on the reduction of handover latency. Finally, we demonstrate total handover scenarios for the proposed techniques and discussed the major factors which contribute to the handover latency.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.355-365
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• 2000

The interferometric correlation, or coherence, is calculated to measure the variance of the interferometric phase and amplitude within the neighbourhood of any location within the image at a result of SAR (Synthetic Aperture Radar) interferometric process which utilizes the phase information of the images. The coherence contains additional information that is useful for detecting point targets which change their location in an area of interest (AOI). In this research, a RGB colour composite image was generated with a intensity image (master image), a intensity change image as a difference between master image and slave image, and a coherence image generated as a part of SAR interferometric processing. We developed a technique performing detection of a point target movement using SAR interferometry and applied it to suitable tandem pair images of ERS-1 and ERS-2 as test data. The possibility of change detection of a point target in the AOI could be identified with the technique proposed in this research.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1184-1192
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• 2004

A real-time pupil detection system that detects the pupil movement from the real-time video data achieved by the visual light camera for general purpose personal computer is proposed. It is implemented with three steps; at first, face region is detected using the Haar-like feature detection scheme, and then eye region is detected within the face region using the template-based scheme. Finally, pupil movement is detected within the eye region by convolution of the horizontal and vertical histogram profiling and Gaussian filter. As results, we obtained more than 90% of the detection rate from 2375 simulation images and the data processing time is about 160㎳, that detects 7 times per second.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.843-848
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• 2008

Most of face detection technique uses information from the face of the movement. The traditional face detection method is to use difference picture method ate used to detect movement. However, most do not consider this mathematical approach using real-time or real-time implementation of the algorithm is complicated, not easy. This paper, the first to detect real-time facial image is converted YCbCr and RGB video input. Next, you convert the difference between video images of two adjacent to obtain and then to conduct Glassfire Labeling. Labeling value compared to the threshold behavior Area recognizes and converts video extracts. Actions to convert video to conduct face detection, and detection of facial characteristics required for the extraction and use of AdaBoost algorithm.