• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.1
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• pp.53-59
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• 2014

In multiple object tracking, accurate detection for each of objects that appear sequentially and effective tracking in complicated cases that they are overlapped with each other are very important. In this paper, we propose a multiple object tracking system that has a concrete detection and tracking characteristics by using multi-lateral histogram and SIFT feature extraction algorithm. Especially, by limiting the matching area to object's inside and by utilizing the location informations in the keypoint matching process of SIFT algorithm, we advanced the tracking performance for multiple objects. Based on the experimental results, we found that the proposed tracking system has a robust tracking operation in the complicated environments that multiple objects are frequently overlapped in various of directions.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.86-94
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• 2009

This paper deals with the creation of a new, low-cost point/position tracking system that can measure deformations in engineering structures with simple commercially widespread cameras. Though point tracking systems do exist today, such as Stereo Pattern Recognition (SPR) and Projection Moir$\acute{e}$ Interferometry (PMI) systems, they are far too costly to use to analyze small, simple structures because complex optical components such as large flashes, high-resolution cameras and data acquisition systems with several computers are required. We developed a point tracking system using commercial cameras. This system used IR LEDs and commercial IR CCD cameras to minimize the interference posed by other extraneous light sources. The main algorithm used for this system is an optical point tracking algorithm, which is composed of the point extraction algorithm and the point matching algorithm for 3-D motion estimation. a series of verification tests were performed. Then, the developed point tracking system was applied to measure deformations of an acrylic plate under a mechanical load. The measured deformations of the acrylic plate matched well with the numerical analysis results. The results indicate that the developed point tracking system is reliable enough to measure continuous deformed shapes of various engineering structures.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.68-75
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• 2017

This study deals with a color-based tracking method of a moving object effectively in case that the color of the moving object is same as or similar to that of background. The CamShift algorithm, which is the representative color-based tracking method, shows unstable tracking when the color of moving objects exists in the background. In order to overcome the drawback, this paper proposes the CamShift algorithm merged with depth information of the object. Depth information can be obtained from Kinect device which measures the distance information of all pixels in an image. Experimental result shows that the proposed tracking method, the Camshift merged with depth information of the tracking object, makes up for the unstable tracking of the existing CamShift algorithm and also shows improved tracking performance in comparison with only CamShift algorithm.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.24-32
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• 2010

In this study, we have proposed a pre-processing algorithm newly developed for improving the tracking efficiency of the optical flow method. The developed pre-processing algorithm consists of a median filter, binarization, morphology, canny edge, contour detecting and an approximation method. In order to evaluate whether the optical flow tracking capacity increases, this study applied the pre-processing algorithm to the Lucas-Kanade(LK) optical flow algorithm, and comparatively analyzed its images and tracking results with those of optical flow without the pre-processing algorithm and with the existing pre-processing algorithm(composed of median filter and histogram equalization). As a result, it was observed that the tracking performance derived from the LK optical flow algorithm with the pre-processing algorithm, shows better tracking accuracy, compared to the one without the pre-processing algorithm and the one with the existing pre-processing algorithm. It seems to have resulted by successful segmentation for characteristic areas and subdivision into inner and outer contour lines.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.218-220
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• 2008

This paper proposes a the high efficiency tracking system regarding power loss when operating a tracking system for environment variable such as a rapidly changing insolation to improve the power of PV tracking system. In case of tracking an azimuth and altitude of the sun in realtime, therefore, the actual PV power is less increasing than the power of tracking system fixed a specific position. To reduce the power loss, this paper proposes a nonel control algorithm of the tracking system. The paper is analyzed efficiency about conventional PV tracking method, comparing proposed algorithm with high Performance method. We show propriety of proposed algorithm by means of the demonstrable study.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2520-2528
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• 2009

In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.13-20
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• 2004

In this paper, we developed a method for predicting the tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algerithm is known to be a measurement-oriented optimal Bayesian approach and is superior to any other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms as well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1121-1141
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• 2020

We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.05a
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• pp.411-414
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• 2008

In this paper a novel tracking system is described, regarding the influence of shadow between array, aimed at improving the efficiency of PV tracking system. The loss by influence of those shadow can be compensated for by means of control algorithm of the tracking device. The paper suggests a method controlling an altitude for length which is received the shadow influence of PV array. By using an azimuth of current solar position and the length between arrays, the controller of tracking device is able to calculate the length between actual arrays and make a comparison of the shadow length at a specific time with the length between arrays. In the paper, we develop the control algorithm able to minimize the loss caused by the influence of shadow on the PV tracking system, and compared this with conventional output system. The controller has been tested in the laboratory with proposed algorithm and shows excellent performance