• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.49-57
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• 2016

In this paper, we propose the novel tracking method which uses the weighted discriminative correlation filter (DCF). We also propose the PSPR instead of conventional PSR as tracker performance evaluation method. The proposed tracking method uses multiple DCF to estimates the target position. In addition, our proposed method reflects more weights on the correlation response of the tracker which is expected to have more performance using PSPR. While existing multi-DCF-based tracker calculates the final correlation response by directly summing correlation responses from each tracker, the proposed method acquires the final correlation response by weighted combining of correlation responses from the selected trackers robust to given environment. Accordingly, the proposed method can provide high performance tracking in various and complex background compared to multi-DCF based tracker. Through a series of tracking experiments for various video data, the presented method showed better performance than a single feature-based tracker and also than a multi-DCF based tracker.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Journal of Web Engineering
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• v.21 no.4
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• pp.1283-1294
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• 2022

Traffic volume is gradually increasing due to the development of technology and the concentration of people in cities. As the results, traffic congestion and traffic accidents are becoming social problems. Detecting and tracking a vehicle based on computer vision is a great helpful in providing important information such as identifying road traffic conditions and crime situations. However, vehicle detection and tracking using a camera is affected by environmental factors in which the camera is installed. In this paper, we thus propose a deep learning based on vehicle classification and tracking scheme to classify and track vehicles in a complex and diverse environment. Using YOLO model as deep learning model, it is possible to quickly and accurately perform robust vehicle tracking in various environments, compared to the traditional method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1823-1831
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• 2010

This paper proposes an automatic tracking control algorithm for efficiency improvement of photovoltaic generation. Increasing the power of PV systems should improve the efficiency of solar cells or the power condition system. The normal alignment of the PV module always have to run perpendicular to the sun's rays. The solar tracking system, able to improve the efficiency of the PV system, was initiated by applying that to the PV power plant. The tracking system of conventional PV power plant has been studied with regard to the tracking accuracy of the solar cells. Power generation efficiency were increased by aligning the cells for maximum exposure to the sun's rays. Using a perpendicular position facilitated optimum condition. However, there is a problem about the reliability of tracking systems unable to not track the sun correctly during environmental variations. Therefore, a novel control algorithm needs to improve the generation efficiency of the PV systems and reduce the loss of generation. This control algorithm is the proposed automatic tracking algorithm in this paper. Automatic tracking control is combined the sensor and program method for robust control in environment changing condition. This tracking system includes the insolation, rain sensor and anemometer for climate environment changing. Proposed algorithm in this paper, is compared to performance of conventional tracking control algorithm in variative insolation condition. And prove the validity of proposed algorithm through the experimental data.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.47-60
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• 2018

In this paper, we proposed a method for eliminating aiming error of unguided anti-tank rocket using improved target tracking. Since predicted fire is necessary to hit moving targets with unguided rockets, a method was proposed to estimate the position and velocity of target using fire control system. However, such a method has a problem that the hit rate may be lowered due to the aiming error of the shooter. In order to solve this problem, we used an image-based target tracking method to correct error caused by the shooter. We also proposed a robust tracking method based on TLD(Tracking Learning Detection) considering characteristics of the FCS(Fire Control System) devices. To verify the performance of our proposed algorithm, we measured the target velocity using GPS and compared it with our estimation. It is proved that our method is robust to shooter's aiming error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1217-1224
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• 2008

The carrier tracking has to be basically completed for accurate positioning of Galileo satellite system. The FLL for tracking frequency errors is robust to dynamic stress causing changes of propagation time but hardly tracks accurate carrier tracking. The PLL for tracking phase errors provides accurate carrier tracking but is sensitive to dynamic stress and its tracking performance is decreased when high dynamics exist. In this paper, we design the carrier tracking loop with the FLL-assisted PLL loop filter and co-operations of FLL and PLL to achieve accurate carrier tracking in high dynamic stress. we prove the performance of designed carrier tracking loop via simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.836-839
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• 1997

In recent years, much progress has been made in the automation of welding coped with a variety of highly flexible sensors. Among these sensors, only the eddy current sensor can detect the center location of the butt joint whose gap distance is zero. Thus, in this study the eddy current sensor is used to develop a robust and useful joint tracking system. The developed system is tested to qualify the performance of the system and seam tracking algorithm is proposed and two simulation are executed to show the performance of the proposed tracking algorithm.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.83-92
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• 2003

The outdoor antenna servo system is subject to has significant torque disturbances from wind pressures and gusts on the antenna structures, as well as bearing and aerodynamic frictions. This control system should provide a sharp directivity in spite of the environmental disturbances and internal uncertainties. Therefore, the implementation of a real-time controller is necessary for the precise generation of the reference signal and robust tracking performance. In this paper, the discrete-time controller for the quick tracking of a target communication satellite is designed by applying the sampled-data $H_{\infty}$ control theory along with the reference signal generated by an improved conventional step-tracking algorithm. The sampled-data $H_{\infty}$controller demonstrates superior robustness for the longer sampling period when compared with a simple PID controller.