• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• 한국안광학회지
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• 제5권1호
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• pp.101-105
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• 2000

본 연구는 한국인을 대상으로 주시점의 위치에 따른 시 표적이 뇌파에 미치는 영향을 조사한 것이다. 시유발 전위 장치는 BIO-Pag를 이용하였으며, 검사 결과는 586 컴퓨터에 입력하여 분석하였다. 조도는 500lux이여 시표는 직경이 3 cm인 붉은 광점을 사용하였다. 수렴과 개산에 따른 결과는 다음과 같다. 1. 시자극에 관계하는 시피질의 뇌파의 출현 빈도는 델타파, 베타파, 세타파, 그리고 알파파의 순으로 나타났다. 2. 수렴 상태는 개산에 비해서 속파 성분이 많이 출현되었다. 3. 수렴은 개산에 비해서 베타파와 알파파가 많아 나타났다. 4. 수렴과 개산에서 진폭에 대한 히스토 그램은 비가우시안 모양이다. 5. 뇌파의 진폭에 대한 위상 분석은 거의 선상을 나타내었다.

• 대한기계학회논문집
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• 제19권5호
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• pp.1220-1228
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• 1995

In this paper, we consider the problems of tracking an object in a real image. In evaluating these problems, we explore a new technique based on an active contour model commonly called a snake model, and propose the active bar models to represent target. Using this model, we simplified the target welection problems, reduced the search space of energy surface, and obtained the better performances than those of snake model. This approach improves the numerical stability and the tendency for points to bunch up and speed up the computational efficiency. Representing the object by active bar, we can easily obtain the zeroth, the first, and the second moment and it facilitates the target tracking. Finally, we present the good result for the visual tracking problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.451-465
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• 2017

This paper presents a novel discriminative visual tracking algorithm with an adaptive incremental extreme learning machine. The parameters for an adaptive incremental extreme learning machine are initialized at the first frame with a target that is manually assigned. At each frame, the training samples are collected and random Haar-like features are extracted. The proposed tracker updates the overall output weights for each frame, and the updated tracker is used to estimate the new location of the target in the next frame. The adaptive learning rate for the update of the overall output weights is estimated by using the confidence of the predicted target location at the current frame. Our experimental results indicate that the proposed tracker can manage various difficulties and can achieve better performance than other state-of-the-art trackers.

• 대한의용생체공학회:의공학회지
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• 제2권1호
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• pp.21-30
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• 1981

In this study, measuring eye movements with E.O.G. to targets beyond 20$^{\circ}$ from fixation point, results are as follows. (1) When the eyes turn toward targets of more than 20$^{\circ}$ eccentricity, the first saccadic eye movement falls short of the target. The presence of image of the target off the fovea(visual error signal) subsequent to such an undershoot elicits, after short interval, corrective saccadic eye movements(usually one) which place the image of the target on the fovea. (2) There are different programming modes at retina for eye movement to targets within and beyond 20$^{\circ}$ from the fixation point. (3) Saccadic system, preparing the direction and amplitude of eye movement completes the corrective saccadic eye movements. (4) Distribution of latency and intersaccadic interval(I.S.I.)are frequently multi modal, with a seperation between modes of 25[msec]. (5) There are two types of saccadic eye movements for the double-step targets. This fact suggests that the visual information is sampled stochastically. (6) The new model of saccadic system including the dissociation of visual functions dependent on retinal eccentricity is required.

• 한국멀티미디어학회논문지
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• 제24권9호
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• pp.1279-1284
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• 2021

This paper addresses the task of transferring facial blendshape models to an arbitrary target face. Blendshape is a common method for the facial rig; however, production of blendshape rig is a time-consuming process in the current facial animation pipeline. We propose automatic blendshape facial rigging based on our blendshape transfer method. Our method computes the difference between source and target facial model and then transfers the source blendshape to the target face based on a deformation transfer algorithm. Our automatic method provides efficient production of a controllable digital human face; the results can be applied to various applications such as games, VR chating, and AI agent services.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.145-148
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• 1996

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

• 한국컴퓨터정보학회논문지
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• 제22권7호
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• ETRI Journal
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• 제41권4호
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• pp.483-493
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• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• 감성과학
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• 제21권2호
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• pp.73-88
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• 2018

본 연구는 손과 가까운 시각 정보의 처리적 특성이 과제전환에 미치는 영향을 살펴보기 위해 수행되었다. 최근 연구들은 손과 가깝게 제시된 정보에 대한 인지통제가 향상됨을 보고하고 있다. 이러한 인지통제 향상효과를 손 근접성과 주의의 관계를 통해 규명하고자 두 번의 실험을 실시하였다. 그 결과 과제전환 수행에서 단서와 목표자극의 감각양상에 따라 손 근접성의 효과가 달라짐을 관찰할 수 있었다. 첫 번째 실험에서 손에 근접한 자극에 대한 전환비용의 감소가 관찰되었다. 선행 연구들에서 전환비용의 감소원인으로 지목되었던 특징결합 문제를 제외시켰을 경우에도 동일한 결과가 관찰되었다. 즉, 손 근접성이 전환비용을 감소시켰음을 검증할 수 있었다. 두 번째 실험에서는 손 근접성과 감각양상의 상호작용이 전환비용에 미치는 영향을 살펴보기 위해 수행되었다. 과제전환에서 목표자극은 시각으로 단서는 시각 또는 청각으로 제시하였고, 단서의 준비성 효과를 관찰하기 위해 단서-목표자극 간격을 조변하였다. 연구 결과 손에 근접한 시각 단서는 과제 준비 시간을 단축시켜 전환비용을 감소시켰으나, 청각 단서의 경우 손에 근접할 때 오히려 과제 준비 시간이 더 오래 걸렸다. 시각 단서의 결과는 손에 근접한 시각 정보에 대한 신속한 주의정향으로 인한 이득으로 설명될 수 있다. 반면에 청각 단서에서 나타난 손실은 청각 단서와 시각 자극 간의 감각 간 전환이 손 근접성의 주의 범위 고정 효과로 인해 방해된 결과로 해석될 수 있다. 마지막으로 손 근접성의 주의효과로 인해 달라지는 전환비용에 대해 논의하였다.