• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.66-76
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• 2005

In this study, star visibility analysis of a star tracker is performed by using a statistical apprach. The probability of the Sun and the Earth proximity, the solar array masking probability, and the solar array blinding probability by the Sun light are obtained from the arbitrary chosen satellite positions as a function of a line of sight vector of the star tracker in several satellite attitude modes. This analysis demonstrates that the optimized star tracker accomodations can be determined to be an elevation angle -40o and two azimuth angles $-35^{circ}$ and $-150^{circ}$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.201-220
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• 2020

Trackers, especially long-term (LT) trackers, now have a more complex structure and more intensive computation for nowadays' endless pursuit of high accuracy and robustness. However, computing efficiency of LT trackers cannot meet the real-time requirement in various real application scenarios. Considering heterogeneous CPU-GPU platforms have been more popular than ever, it is a challenge to exploit the computing capacity of heterogeneous platform to improve the efficiency of LT trackers for real-time requirement. This paper focuses on TLD, which is the first LT tracking framework, and proposes an efficient parallel implementation based on OpenCL. In this paper, we firstly make an analysis of the TLD tracker and then optimize the computing intensive kernels, including Fern Feature Extraction, Fern Classification, NCC Calculation, Overlaps Calculation, Positive and Negative Samples Extraction. Experimental results demonstrate that our efficient parallel TLD tracker outperforms the original TLD, achieving the 3.92 speedup on CPU and GPU. Moreover, the parallel TLD tracker can run 52.9 frames per second and meet the real-time requirement.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.893-910
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• 2017

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.

• Journal of the Speleological Society of Korea
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• no.89
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• pp.27-33
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• 2008

Solar energy is most green and clean, unlimited and sustainable energy source on the earth. It is almost 97% of imported consumer energy in Korea. Because of resource poor nation, it is necessary to do their best to make alternative energy to allot their deficiency of the matter in hand of energy resources of petroleum. In a point of view of this problems, the natural solar energy should be improved by any methods as much, possible as we need. Photovoltaic generation with solar tracking system for obtaining optimal power is one of most benefit equipment to improve power of solar-cell panel producing clean electric power efficiently. Solar tracker is a device for orienting a solar photovoltaic panel toward the sun perpendicularly to sunlight, especially in widely separated place. For this reason, we are very interested in developing the equipment system of tracker, specially in solar cell applications, obtaining a high degree of accuracy to ensure that the optimal sunlight could be directed precisely against to the powered device. As a result, it was obtained of 12.46 volts at 90$^\circ$toward solar panel and 9.44 volts at 45$^\circ$, furthermore, improved efficiency more than 30% of average output voltage between tracker system (12.41V) and fixed system (8.55V), respectively. It is also very useful for optimum power system of widely separated cave.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.256-263
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• 2002

In this study, the tracking of the temporal variation of the frequency and the amplitude in the presence of additive white Gaussian noise is considered using the Extended Kalman filter (EKF. The EKF has many applications and it has been applied to the problem of tracking the time-variable frequency. However the existing EKF frequency trackers could was driven in the small time-variable amplitude or required the additional amplitude tracker in the large time-variable amplitude. In this study, the EKF frequency-amplitude tracker, which could track both frequency and amplitude simultaneously from the measured signal in the relatively large time-variable amplitude environment, is proposed for improving the performance of the time-variable frequency tracking and its performance is verified by the simulation and the experimental work.

• Journal of IKEEE
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• v.15 no.3
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• pp.211-217
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• 2011

The energy of CPV system is different as the altitude and azimuth of solar. In order to The maximum of solar energy density, the tracking system which does there to make be the module and the solar will be able to maintain a normal line is necessary. This paper proposed for GPS solar tracker of stand-alone 60[W] concentrating photovoltaic system. The position algorithm of solar tracker is through the coordinates transformation calculating the altitude and azimuth of the solar.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.703-710
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• 2014

An Image-Based Target Tracker maintains LOS(Line Of Sight) to a target by controlling azimuth and elevation gimbals of an ISS(Inertially Stabilized System). Its controller produces the gimbals commands of the ISS using tracking errors provided by an image tracker. The control performance of the target tracker with PI controller generally used for tracking controller is limited because of bandwidth limitation by time delay yielded by image capture and processing of the image tracker. In this paper, tracking controller using target states estimator is proposed which can enhance the tracking performance under the highly dynamic maneuvering conditions of the ISS and the target. Simulation results show that the proposed method can improve the tracking performance than that with only PI controller.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.45-55
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• 1998

In this paper, a robust path tracker and depth controller of Autonomous Underwater Vehicle based on sliding mode control is presented. We have also designed augmented equivalent control inputs by analyzing the sliding mode with the reaching mode. This can enhance the reaching rate, and improve chattering problems, that is, noise caused by the control plane actuator of the vehicle, which is one of the problems that occur when sliding mode control is used. Also to resolve the steady state error generated in the path tracker under current effect, a modified sliding plane is constructed. Also a redesigned sliding plane and control input using transformation matrix is proposed to do easy design of MIMO depth controller. For state variables that cannot be measured directly, reduced order sliding mode control is used to design an observer. The performance of designed path tracker and depth controller is investigated by computer simulation. The results show that the proposed control system has robust performance to parameter variation, modelling error and disturbance.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.8
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• pp.683-689
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• 2016

Servo mismatch, which affects positioning accuracy of multi-axis machine tools, is usually estimated via the circular test. However, due to mechanical restrictions in measuring instruments, the circular test using a double ball-bar is difficult to apply in miniaturized or super-large sized machine tools. Laser trackers are widely used to measure the form accuracy of parts and the positioning accuracy of driving systems. In this paper, a technique for the servo mismatch estimation of multi-axis machine tools is proposed via the circular test using a laser tracker. To verify the proposed technique, experiments using a double ball-bar and laser tracker are conducted in a 3-axis machine tool. The difference in the evaluation results is 0.05 msec. The servo mismatch for the miniaturized machine tool is also evaluated using the proposed technique.