• 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.

• International Journal of Aeronautical and Space Sciences
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• 제2권2호
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• pp.73-81
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• 2001

This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.468-473
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• 1998

An intelligent multimode target tracking algorithm using fuzzy logic is presented. Multimode tracking represents a synergistic approach that utilizes a variety of tracking techniques(centroid, correlation, etc.) to overcome the limitations inherent in any single-mode tracker. The design challenge for this type of multimode tracker is the data fusion algorithm. designs for this algorithm are based on heuristic rather than analytical approaches. A correlation-tracking algorithm seeks to align the incoming target image with a reference in age of the target, but has a critical problem, so called drift phenomenon. In this paper we will suggest a robust correlation tracker with gradient preprocessor combined by centroid algorithm to overcome the drift problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.335-337
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• 1994

The correlation tracker developed by John M. Fitts in 1979 is the most complex to mechanize but provides the best tracking performance in a low SNR condition. Correlation tracker would rewove the requirements for optimizing threshold and has no need to know information about the target. But if the displacement of the target is large, the tracking error of the correlation tracker tends to diverge. In this paper, we suggest a precision image tracking algorithm which improves the tracking performance via iterative application of the matched filter estimation algorithm.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.947-952
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• 2021

In this paper, the simplified kinematic error model for Delta parallel robot is presented, which can enable the analytical forward kinematics essentially for kinematic calibration calculations instead of the numerical one. The simplified kinematic error model is proposed and the forward kinematics including the error parameters is analytically derived. The kinematic calibration algorithm of the Delta parallel robot with 90 degree arrangement using laser tracker and the experiment result are presented.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (D)
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• pp.444-448
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• 2008

유비쿼터스 스마트 홈 (ubiquitous smart home) 은 인간과 홈의 컨텍스트(context) 정보를 이용하여 인간에게 자동적인 홈 서비스 (Home service)를 제공해줄 수 있는 미래의 환경이다. 인간의 위치와 모션은 유비쿼터스 스마트 홀에서 굉장히 중요한 컨텍스트이다. 본 논문은 유비쿼터스 스마트 홀에서 인간의 위치와 모션을 예측할 수 있는 실시간 휴먼 트랙커 (tracker)를 연구하였다. 실시간 휴먼 트랙커를 위해 우리는 4개의 네트워크 카메라를 사용하였다. 본 논문에서는 실시간 휴먼 트랙커의 구조를 설명하고, 인간의 위치와 모션을 자동적으로 예측 및 판단하는 알고리즘을 제안하였다. 인간 위치를 위해서 3개의 배경이미지를 이용하였다 (이미지1 : 빈 방, 이미지2: 가구 및 가전, 이미지3: 이미지 2 와 거주자를 포함). 실시간 휴먼 트랙커는 3개의 이미지를 비교하여 각 이미지로부터 추출되는 특징 값을 결정하고, 이들 특징 값을 SVM (Support Vector Machine)을 이용하여 각각의 모션을 예측하였다. 3 개의 배경 이미지를 이용한 인간 위치 인식실험은 평균 0.037 초가 소요되었다. SVM을 이용한 모션 인식 요소에서, 우리는 각 동작에 대하여 1000번씩 측정했고, 모든 모션의 정확도 평균은 86.5% 의 정확도를 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.395-396
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1095-1098
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• 1996

In this work, attitude determination with Inertial Reference Unit as attitude sensor is considered. Usually, the attitude error from IRU increases because of gyro rate bias and noise. Therefore, other attitude sensors(sun sensor, horizon sensor, star tracker) are needed to compensate for error from IRU. In this paper, we use the extended Kalman filter for attitude estimation of spacecraft with IRU and star tracker.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1986년도 추계학술발표회 논문집
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• pp.186-190
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• 1986

This paper describes a way of implementing the segmentation of 128*128 pixel images to be used as the inputs. to a real-time automatic video tracker. The suggested method uses the lowest valley-value of the computed intensity historgram with 16 levels. This method improves smoothing effects and also significantly reduces hardware requirements. Entire segmentation process is caried out in 10msec thus making a real time application possible.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.485-488
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• 2003

A conventional correlation target tracker is analysed with a simple mathematical approach. And, we will propose a correlation measure with selective attentional property in order to overcome the false-peak problem of the conventional methods. Various experimental results show that the proposed correlation measure is able to reduce considerably the probability of false-peaks degraded by the correlation between background images of a reference block and a distorted and noisy sensor input image.