• 한국컴퓨터정보학회논문지
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• 제21권11호
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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.

• 제어로봇시스템학회논문지
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• 제11권7호
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• pp.587-594
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• 2005

In this paper, a robust correlation-based video tracking is proposed to track a moving object in correlated image sequences. A correlation-based video tracking algorithm seeks to align the incoming target image with the reference target block image, but has critical problems, so called a false-peak problem and a drift phenomenon (correlator walk-off. The false-peak problem is generally caused by highly correlated background pixels with similar intensity of a moving target and the drift phenomenon occurs when tracking errors accumulate from frame to frame because of the nature of the correlation process. At first, the false-peaks problem for the ordinary correlation-based video tracking is investigated using a simple mathematical analysis. And, we will suggest a robust selective-attention correlation measure with a gradient preprocessor combined by a drift removal compensator to overcome the walk-off problem. The drift compensator adaptively controls the template block size according to the target size of interest. The robustness of the proposed method for practical application is demonstrated by simulating two real-image sequences.

• Journal of Positioning, Navigation, and Timing
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• 제4권3호
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• pp.107-114
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• 2015

Binary Offset Carrier (BOC) signal planned for future Global Navigation Satellite System (GNSS) provided better positioning accuracy and smaller multipath error than GPS C/A signal. However, due to the multiple side peaks in the auto-correlation function (ACF) of the BOC modulated signals, a receiver may false lock onto one of the side peaks in the tracking mode. This false lock would then result in a fatal tracking error. In this paper, we propose an unambiguous tracking method for composite BOC (CBOC) signals to mitigate this problem. It aims to reduce the side peaks of the ACF of CBOC modulated signals. It is based on the combination of traditional CBOC correlation function (CF) and reference CF of unmodulated pseudo- random noise code (PRN code). First, we present that cross-correlation function (CCF) with unmodulated PRN code is close to the secondary peaks of the traditional CBOC. Then, we obtain an unambiguous correlation function by subtracting traditional CBOC ACF from these CFs. Finally, the tracking performance for the CBOC signals is examined, and it is shown that the proposed method has better performance than the traditional unambiguous tracking method in additive white Gaussian noise (AWGN) channel.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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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.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.552-555
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• 2012

The main goal of this paper is to develop a robust visual tracking algorithm with particle filtering. Visual Tracking with particle filter technique is not easy task due to cluttered environment, illumination changes. To deal with these problems, we develop an efficient observation model for target tracking with particle filter. We develop a robust phase correlation combined with motion information based observation model for particle filter framework. Phase correlation provides straight-forward estimation of rigid translational motion between two images, which is based on the well-known Fourier shift property. Phase correlation has the advantage that it is not affected by any intensity or contrast differences between two images. On the other hand, motion cue is also very well known technique and widely used due to its simplicity. Therefore, we apply the phase correlation integrated with motion information in particle filter framework for robust tracking. In experimental results, we show that tracking with multiple cues based model provides more reliable performance than single cue.

• 한국통신학회논문지
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• 제40권7호
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• pp.1433-1440
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• 2015

본 논문에서는 이진 옵셋 반송파 (binary offset carrier: BOC) 신호의 추적 성능 향상을 위한 비모호 상관함수를 제안한다. 구체적으로는 BOC 신호의 부반송파를 여러 개의 펄스가 존재하는 형태로 해석하고, BOC 신호의 자기상관함수를 여러 개의 부분상관함수들의 합으로 해석한다. 이후 두 개의 부분상관함수를 조합하여 새로운 두개의 부상관함수를 생성하고, 부상관함수와 부분상관함수의 조합을 통하여 폭을 조절할 수 있으며 주변 첨두를 가지지 않는 비모호 상관함수를 제안한다. 모의실험을 통해 신호 추적에 제안한 상관함수를 이용한 경우 기존의 상관함수들을 이용한 경우에 비해 더욱 향상된 추적 오류 표준편차를 가지는 것을 확인한다.

• Journal of Electrical Engineering and information Science
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• 제3권2호
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• pp.230-238
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• 1998

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

• 한국통신학회논문지
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• 제38A권5호
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• pp.409-415
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• 2013

본 논문에서는 코사인 위상 이진 옵셋 반송파 (binary offset carrier: BOC) 신호 추적에 알맞은 새로운 비모호 상관함수를 제안한다. 구체적으로는 코사인 위상 BOC 신호를 의사잡음코드의 칩 하나 안에 다수의 부반송파 펄스가 존재하는 형태로 해석하고, 그에 따른 새로운 국소신호들을 설계한다. 이후 새로운 국소신호들과 수신된 코사인 위상 BOC 신호를 상관하여 재조합함으로써 주변 첨두가 없는 새로운 비모호 상관함수를 생성한다. 모의실험을 통해 제안한 상관함수를 이용한 경우 기존의 상관함수들을 이용한 경우들에 비해 더욱 향상된 추적 오차 표준편차를 가지는 것을 확인한다.

• 한국통신학회논문지
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• 제38A권6호
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• pp.512-519
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• 2013

본 논문에서는 합성 이진 옵셋 반송파를 (composite binary offset carrier: CBOC) 위한 새로운 비모호 상관함수를 제안한다. 먼저, CBOC 신호의 부반송파를 네 개의 부분 부반송파의 합으로 해석하고, 각 부분 부반송파들과 수신 신호의 부분 상관들을 생성한다. 이후 생성된 부분 상관을 재조합하여 날카로운 주 첨두를 갖는 새로운 비모호 상관함수를 생성한다. 모의실험의 결과로부터 신호 추적에 제안한 상관함수를 이용한 경우 기존 상관함수들을 이용한 경우보다 더욱 향상된 추적 오류 표준편차와 다중 경로 오류 포락선을 가짐을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2094-2112
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• 2019

Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has poor performance in handling scale change and obscured objects, this paper proposes an anti-occlusion and scale adaptive tracking algorithm in the basis of KCF. The average Peak-to Correlation Energy and the peak value of correlation filtering response are used as the confidence indexes to determine whether the target is obscured. In the case of non-occlusion, we modify the searching scheme of the KCF. Instead of searching for a target with a fixed sample size, we search for the target area with multiple scales and then resize it into the sample size to compare with the learnt model. The scale factor with the maximum filter response is the best target scaling and is updated as the optimal scale for the following tracking. Once occlusion is detected, the model updating and scale updating are stopped. Experiments have been conducted on the OTB benchmark video sequences for compassion with other state-of-the-art tracking methods. The results demonstrate the proposed method can effectively improve the tracking success rate and the accuracy in the cases of scale change and occlusion, and meanwhile ensure a real-time performance.