• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.55-61
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• 2017

In this paper, we propose a novel tracking method using target separation and detection that are based on discriminative correlation filter (DCF), which is studied a lot recently. 'Retainability' is one of the most important factor of tracking. There are some factors making retainability of tracking worse. Especially, fast movement and occlusion of a target frequently occur in image data, and when it happens, it would make target lost. As a result, the tracking cannot be retained. For maintaining a robust tracking, in this paper, separation of a target is used so that normal tracking is maintained even though some part of a target is occluded. The detection algorithm is executed and find new location of the target when the target gets out of tracking range due to occlusion of whole part of a target or fast movement speed of a target. A variety of experiments with various image data sets are conducted. The algorithm proposed in this paper showed better performance than other conventional algorithms when fast movement and occlusion of a target occur.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.10
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• pp.50-57
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• 1997

A fast tool servo (FTS) for diamond turning improves machining accuracy by quickly compensating relative position errors between the cutter and the workpiece. Therefore, the FTS needs to have large band-width with good tracking performance. Serious hysteresis nonlinearity of PZT actuators used in the FTS, however, deteriorates fast tracking performance. Several types of feedforward hysteresis compensators and feedback controllers are tested to improve tracking performance. Through simulations and experiments, control structure which yields the smallest tracking error is selected. The maximum peak to peak error in tracking a sinusoidal waveform is reduced by one fifth compared to that of a regular PID controller.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.291-294
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• 2004

Semantic video object extraction is important for tracking meaningful objects in video and object-based video coding. We propose a fast semiautomatic video object extraction algorithm which combines a watershed segmentation schemes and chamfer distance transform. Initial object boundaries in the first frame are defined by a human before the tracking, and fast video object tracking can be achieved by tracking only motion-detected regions in a video frame. Experimental results shows that the boundaries of tracking video object arc close to real video object boundaries and the proposed algorithm is promising in terms of speed.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.5-99
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• 2002

$\textbullet$ 3-D object tracking framework $\textbullet$ Using fast stereo vision system for range image $\textbullet$ Using CONDENSATION algorithm to tracking object $\textbullet$ For recognizing object, superquardrics model is used $\textbullet$ Our target object is like coils in steel works

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.185-186
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• 2016

Maximum power point tracking (MPPT) techniques play a big role in improving the efficiency of photovoltaic (PV) system. Among various schemes, the incremental conductance (INC) method is mostly discussed in literature because of its fast response to the rapid irradiation changes and high tracking accuracy. However, the existing INC algorithm has trade-offs between fast dynamic response and steady state stability. This study proposes a novel INC method to meet high efficiency and fast tracking performance at the same time.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.673-679
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• 2012

This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.454-461
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• 2016

A maximum power point tracking (MPPT) system with fast-tracked time and high power efficiency is presented in this paper. The proposed MPPT system uses an unbounded binary search (UBS) algorithm that continuously tracks the maximum power point (MPP) with a binary system to follow the MPP under rapid-weather-change conditions. The proposed algorithm can decide the correct direction of the MPPT system while comparing the previous power point with the present power point. And then, by fixing the MPP until finding the next MPP, there is no oscillation of voltage MPP, which maximizes the overall power efficiency of the photovoltaic module. With these advantages, this proposed UBS is able to detect the MPP more effectively. This MPPT system is based on a boost converter with a micro-control unit to control analog-to-digital converters and pulse width modulation. Analysis of this work and experimental results show that the proposed UBS MPPT provides fast, accurate tracking with no oscillation in situations where weather rapidly changes and shadow is caused by all sorts of things. The tracking time is reduced by 87.3% and 66.1% under dynamic-state and steady-state operation, respectively, as compared with the conventional 7-bit perturb and observe technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.124-127
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• 2000

This paper describes the algorithm for more fast tracking by compensation of the staring angle of antenna to receive the satellite signal changed by the mobile vehicle direction. The staring angle is compensated by signal processing from the electronic compass which is called VECTOR2X, and a left-right tracking method. Especially, when mobile vehicle is turning with high speed, it is observed a result which has more fast tracking time by using angle tracking technique compensated by electronic compass than one by only left right tracking method.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.977-985
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• 2009

This paper proposes a real-time algorithm for tracking the fast moving human body. Although Iterative closest point (ICP) algorithm is suitable for real-time tracking due to its efficiency and low computational complexity, ICP often fails to converge when the human body moves fast because the closest point may be mistakenly selected and trapped in a local minimum. To overcome such limitation, we combine a particle filter based on a motion history information with the ICP. The proposed human body motion tracking algorithm reduces the search space for each limb by employing a hierarchical tree structure, and enables tracking of the fast moving human bodies by using the motion prediction based on the motion history. Experimental results show that the proposed human body motion tracking provides accurate tracking performance and fast convergence rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.15-22
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• 2005

This paper proposed a object tracking algorithm which can track contour of fast moving object through motion estimation. Since the proposed tracking algorithm is based on the radial representation, the motion estimation of object can be accomplished at the center of object with the low computation complexity. The motion estimation of object makes it possible to track object which move fast more than distance from center point to contour point for each frame. In addition, by introducing both gradient image and difference image into energy functions in the process of energy convergence, object tracking is more robust to the complex background. The results of experiment show that the proposed algorithm can track fast moving object in real-time and is robust under the complex background.