• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.169-189
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• 2015

Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

• ETRI Journal
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• v.37 no.1
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• pp.138-146
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• 2015

This paper presents a new non-constraining online optical handwritten signature reconstruction system that, in the main, makes use of a transparent glass pad placed in front of a color camera. The reconstruction approach allows efficient exploitation of hand activity during a signing process; thus, the system as a whole can be seen as a viable alternative to other similar acquisition tools. This proposed system allows people with physical or emotional problems to carry out their own signatures without having to use a pen or sophisticated acquisition system. Moreover, the developed reconstruction signature algorithms have low computational complexity and are therefore well suited for a hardware implementation on a dedicated smart system.

• Korea-Australia Rheology Journal
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• v.21 no.4
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• pp.289-297
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• 2009

We numerically analyzed flow characteristics of the polymer melt in the screw equipment using a proper modeling and investigated design parameters which have influence on the mixing performance as the capability of the screw equipment. We considered the non-Newtonian and non-isothermal flow in a single rotor equipment to investigate the mixing performance with respect to screw dimensions as shape parameter of the single rotor equipment and screw speed as process parameter. We used Bird-Carreau-Yasuda model as a viscous model of the polymer melt and the particle tracking method to investigate the mixing performance in the screw equipment and considered four mixing performance indexes: residence time distribution, deformation rate, total strain and particle standard deviation as a new mixing performance index. We compared these indexes to determine design parameters and object function. On basis of the analysis results, we carried out the optimal design by using the response surface method and design of experiments. In conclusion, the differences of results between the optimal value and numerical analysis are about 5.0%.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.103-110
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• 2003

With significant development of power electronics technology, the proliferation of nonlinear loads such as static power converters has deteriorated power quality in power transmission and distribution systems. Notably, voltage harmonics resulting from current harmonics produced by the nonlinear loads have become a serious problem in many countries. Many photovoltaic power generation systems installed in building systems have harmonics that are the worst object for distribution systems as a utility interactive system, and it tends to spread out continuously. Proposed and implemented in this paper is a multi-function inverter control strategy that allows a shunt active filter function to the power inverter of the photovoltaic power generation system established on a building system. The effectiveness of the proposed system is demonstrated through the simulation of a hypothetical power system using PSCAD/EMTDC.

• Textile Coloration and Finishing
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• v.25 no.4
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• pp.287-291
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• 2013

Nowadays, terms such as 'Smart Textile', 'Intelligent Textile' and 'Wearable Computing' are commonly used in everyday contexts. And radio-frequency identification (RFID) is the use of a wireless non-contact system that uses radio-frequency electromagnetic fields to transfer data from a tag attached to an object, for the purposes of automatic identification and tracking. These products are required technologies which are textile treatments, printing, ink, etc. Durability of textile substrates is an essential marker for conductive ink printing process. Especially, heat stability is important, since conductive ink should be processable (annealing, curing) at temperatures below $150^{\circ}C$. This study was application of RFID on textiles. The textile pre-treatment processes should be carried out to use RFID antenna on textiles.

• Proceedings of the KIEE Conference
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• summer
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• pp.1471-1473
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• 2004

Maximum power point tracking(MPPT) is used in photovoltaic(PV) systems to maximize the photovoltaic array output power, irrespective of the temperature and irradiation conditions. The object of this paper is to compare and analyze MPPT efficiency for different MPPT techniques by changing irradiance. Also, this paper introduces transformerless grid-connected inverter. Simple flow charts and characteristics of each MPPT algorithm are shown. The implementation of transformerless grid-connected inveter system was based on a digital signal processor(DSP). Simulation was carried out for each MPPT method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.73-82
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• 2011

The location-based service is emerging again to the public attention. The location recognition environment up-to-now has been studied with its focus only on a person, an object or a moving object. However, this study proposes a location recognition model that serves to recognize and track, in real time, multiple passengers in a moving vehicle. Identifying the locations of passengers can be classified into two classes: one is to use the high price terminal with GPS function, and the other is to use the economic price compact terminal without GPS function. Our model enables the simple compact terminal to provide effective location recognition under the on-boarding situation by transmitting messages through an interface device and sensor networks for a vehicle equipped with GPS. This technology reduces transmission traffic after detecting the condition of a vehicle (being parked or running), because it does not require transmission/receiving of information on the locations of passengers who are confined in a vehicle when the vehicle is running. Also it extends battery life by saving power consumption of the compact terminal. Hence, we carried out experiments to verify its serviceability by materializing the efficient tracking system for passengers with the detection algorithm of a stopping vehicle proposed in this study. Moreover, about 200 experiments using the system designed with this technology proved successful recognition on on-boarding and alighting of passengers with the maximum transmission distance of 12 km. In addition to this, the running recognition tests showed the test with the detection algorithm of a stopping vehicle has reduced transmission traffic by 41.6% compared to the algorithm without our model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of the Korea Computer Graphics Society
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• v.25 no.5
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• pp.11-20
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• 2019

With the development of deep learning technology, research is being actively carried out on user-friendly interfaces that are suitable for use in virtual reality or augmented reality applications. To support the interface using the user's hands, this paper proposes a deep learning-based fingertip detection method to enable the tracking of fingertip coordinates to select virtual objects, or to write or draw in the air. After cutting the approximate part of the corresponding fingertip object from the input image with the Grad-CAM, and perform the convolution neural network with Atrous Convolution for the cut image to detect fingertip location. This method is simpler and easier to implement than existing object detection algorithms without requiring a pre-processing for annotating objects. To verify this method we implemented an air writing application and showed that the recognition rate of 81% and the speed of 76 ms were able to write smoothly without delay in the air, making it possible to utilize the application in real time.