• Journal of Platform Technology
• /
• v.12 no.3
• /
• pp.62-70
• /
• 2024

Recent surveillance systems employ multiple sensors, such as cameras and radars, to enhance the accuracy of intrusion detection. However, object recognition through camera (RGB, Thermal) sensors may not always be accurate during nighttime, in adverse weather conditions, or when the intruder is camouflaged. In such situations, it is possible to detect intruders by utilizing the trajectories of objects extracted from camera or radar sensors. This paper proposes a method to detect intruders using only trajectory information in environments where object recognition is challenging. The proposed method involves training an LSTM-Attention based trajectory classification model using normal and abnormal (intrusion, loitering) trajectory data of animals and humans. This model is then used to identify abnormal human trajectories and perform intrusion detection. Finally, the validity of the proposed method is demonstrated through experiments using real data.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.4
• /
• pp.272-279
• /
• 2008

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see realtime operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST company. Thus, our algerian in the paper can be useful in PMP(portable multimedia player) or other portable players.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.4
• /
• pp.405-410
• /
• 2006

This paper presents the design of a USB home controller and a home control system that specially is focused on controlling home appliances as a part of home network systems, the implementation of the USB device access class in an OSGi service platform and a home security system as an application. Designed USB home controllers are able to control various home appliances. They can be used not only to control big home appliances like a boiler but also to control small home appliances like a toaster because they are low-cost solutions. The USB home controller supports real time control using the interrupt transfer of the USB specification. And It is easy to use by homemakers who have no technical knowledge of the system because they just plug and unplug it in a home server then it automatically joins and leaves a home control system. This technique is based on hot-plug and the USB Device Access class in an OSGi Service Platform. The USB Device Access class supports the coordination of automatic detection and attachment of the USB home controller on an OSGi Service Platform, and it downloads and installs device drivers on demand. For an application, we implemented and tested a home security system using two USB home controllers and a CDMA module.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.2
• /
• pp.13-20
• /
• 2014

In this paper, we implemented the object scanning with nxtOSEK which is an open source platform. nxtOSEK consists of device driver of leJOS NXJ C/Assembly source code, TOPPERS/ATK(Automotive real time Kernel) and TOPPERS/JSP Real-Time Operating System source code that includes ARM7 specific porting part, and glue code make them work together. nxtOSEK can provide ANSI C by using GCC tool chain and C API and apply for real-time multi tasking features. We experimented the 3D scanning with ultra sonic and laser sensor which are made directly by laser module diode and experimented the measurement of scanning the object by knowing x, y, and z coordinates for every points that it scans. In this paper, the laser module is the dimension of $6{\times}10[mm]$ requiring 5volts/5[mW], and used the laser light of wavelength in the 650[nm] range. For detecting the object, we used the beacon detection algorithm and as the laser light swept the objects, the photodiode monitored the ambient light at interval of 10[ms] which is called a real time. We communicated the 3D scanning platform via bluetooth protocol with host platform and the results are displayed via DPlot graphic tool. And therefore we enhanced the functionality of the 3D scanner for identifying the image scanning with laser sensor modules compared to ultra sonic sensor.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.11
• /
• pp.2275-2280
• /
• 2009

u-Healthcare service is one of attractive applications in ubiquitous environment. In this paper, we propose a method to recognize exercises using a new accelerometer based body-attached platform for supporting u-Healthcare service. The platform consists of a device for measuring accelerometer data and a device for receiving the data. The former measures a user's motion data using a 3-axis accelerometer. The latter transmits the accelerometer data to a computer for recognizing the user's exercise. The algorithm for exercise recognition classifies the type of exercise using principle components analysis(PCA) from the accelerometer data transformed by discrete fourier transform(DFT), and estimates the repetition count of the recognized exercise using a peak detection algorithm. We evaluate the performance of the algorithm from the accuracy of the recognition of exercise type and the error rate of the estimation of repetition count. In our experimental result, the algorithm shows the accuracy about 98%.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.559-575
• /
• 2023

3D human pose estimation is widely applied in various fields, including action recognition, sports analysis, and human-computer interaction. 3D human pose estimation has achieved significant progress with the introduction of convolutional neural network (CNN). Recently, several researches have proposed the use of multiview approaches to avoid occlusions in single-view approaches. However, as the number of cameras increases, a 3D pose estimation system relying on a CNN may lack in computational resources. In addition, when a single host system uses multiple cameras, the data transition speed becomes inadequate owing to bandwidth limitations. To address this problem, we propose a distributed real-time 3D pose estimation framework based on asynchronous multiple cameras. The proposed framework comprises a central server and multiple edge devices. Each multiple-edge device estimates a 2D human pose from its view and sendsit to the central server. Subsequently, the central server synchronizes the received 2D human pose data based on the timestamps. Finally, the central server reconstructs a 3D human pose using geometrical triangulation. We demonstrate that the proposed framework increases the percentage of detected joints and successfully estimates 3D human poses in real-time.

• Korean Journal of Remote Sensing
• /
• v.34 no.2_2
• /
• pp.313-326
• /
• 2018

This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.3 no.1 s.4
• /
• pp.67-74
• /
• 2004

Next generation telematics technology, offering new and diverse multimedia service by connecting car and wireless access network, has been presented with promising industry. Telematics technology was simply to monitor and control the in-vehicle devices and to navigate the road in the early days but nowadays, telematics technology has provided the mobile internet access service, LBS service, agent rescue service and multimedia service to us using connection of wireless access network. In this paper, telematics mobile platform architecture is proposed for service promotion and efficiency.

• Proceedings of the KIPE Conference
• /
• 2016.07a
• /
• pp.32-33
• /
• 2016

Due to the frequent occurrence of dangerous wild animals in rural or mountainous areas. it has been increasing damage of crops in every year. Fight bell or electric fence is typically installed to chase those wild animals. But there are problems that it is impossible to drive out birds and spends high installation and maintenance cost. In addition, it is inefficient to the risk of electric shock effect. In this study, the proposed system can drive out hazardous wildlife and birds regardless of installation location through realtime detection with the multi-sensing based IoT platform technology. This study showed a very large significance effect that can reduce crop damage by wildlife and birds.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.7
• /
• pp.2095-2107
• /
• 2000

In maned ship, crews may have risks as they manage damage control system in IPMS in damage situations such as fire in a ship. So the application of unmaned autonomous systms can reduce the number of boarding crews and attribute to safe marine transportation. The paper suggests an intelligent system of the fire fighting control using fuzzy logic in Integrated Platform Management System which can take measures against fire situation of a ship excluding unnecessary warnings with undamaged situations. The system here detected the fire more accurately and adopted more appropriate measures according to ship status compared with conventional systems. Of all, a reduction of false detection of fires was noted.