• 전기학회논문지
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• 제62권12호
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• pp.1737-1743
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• 2013

This paper proposes the range and velocity of the object estimation method using a moving camera. Structure and motion (SaM) estimation is to estimate the Euclidean geometry of the object as well as the relative motion between the camera and object. Unlike the previous works, the proposed estimation method can relax the camera and object motion constraints. To this end, we arrange the dynamics of moving camera-moving object relative motion model in an appropriate form such that the nonlinear observer can be employed for the SaM estimation. Through both simulations and experiments we have confirmed the validity of the proposed estimation algorithm.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2001년도 춘계학술대회논문집:21세기 신지식정보의 창출
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• pp.280-287
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• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evacuate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth ColorChecker. As a result, the proposed method showed a lower mean square ems between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2359-2364
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• 2017

This paper proposes a scale factor based range estimation method using a sum of squares (SOS) method. Many previous studies measured distance by using a camera, which usually required two cameras and a long computation time for image processing. To overcome these disadvantages, we propose a range estimation method for an object using a single moving camera. A SOS-based Luenberger observer is proposed to estimate the range on the basis of the Euclidean geometry of the object. By using a scale factor, the proposed method can realize a faster operation speed compared with the previous methods. The validity of the proposed method is verified through simulation results.

• 정보처리학회논문지B
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• 제13B권5호
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• pp.499-506
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• 2006

본 논문에서는 실시간 증강현실 시스템에서의 가상 객체 삽입을 위한 빠르고 안정된 카메라 자세 추정 방법을 제안한다. 단일 프레임에서 마커의 특징점 추출을 통해 카메라의 회전행렬과 이동벡터를 추정한다. 카메라 자세 추정을 위해 정사영 투영모델에서의 분해기법을 사용한다. 정사영 투영모델에서의 분해기법은 객체의 모든 특징점의 깊이좌표가 동일하다고 가정하기 때문에 깊이좌표의 기준이 되는 참조점의 설정과 점의 분포에 따라 카메라 자세 계산의 정확도가 달라진다. 본 논문에서는 실제 환경에서 일반적으로 잘 동작하고 융통성 있는 참조점 설정 방법과 이상점 제거 방법을 제안한다. 제안된 카메라 자세추정 방법에 기반하여 탐색된 마커 위치에 가상객체를 삽입하기 위한 비디오 증강 시스템을 구현하였다. 실 환경에서의 다양한 비디오에 대한 실험 결과, 제안된 카메라 자세 추정 기법은 기존의 자세추정 기법만큼 빠르고 기존의 방법보다 안정적이고 다양한 증강현실 시스템 응용에 적용될 수 있음을 보여주었다.

• ETRI Journal
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• 제37권4호
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• pp.766-771
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• 2015

Robust motion estimation for human-computer interactions played an important role in a novel method of interaction with electronic devices. Existing pose estimation using a monocular camera employs either ego-motion or exo-motion, both of which are not sufficiently accurate for estimating fine motion due to the motion ambiguity of rotation and translation. This paper presents a hybrid vision-based pose estimation method for fine-motion estimation that is specifically capable of extracting human body motion accurately. The method uses an ego-camera attached to a point of interest and exo-cameras located in the immediate surroundings of the point of interest. The exo-cameras can easily track the exact position of the point of interest by triangulation. Once the position is given, the ego-camera can accurately obtain the point of interest's orientation. In this way, any ambiguity between rotation and translation is eliminated and the exact motion of a target point (that is, ego-camera) can then be obtained. The proposed method is expected to provide a practical solution for robustly estimating fine motion in a non-contact manner, such as in interactive games that are designed for special purposes (for example, remote rehabilitation care systems).

• 전기학회논문지
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• 제65권12호
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• pp.2057-2060
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• 2016

Range-based motion estimation of a moving object by using a camera is proposed. Whereas the existing results constrain the motion of an object for the motion estimation of an object, the constraints on the motion is relieved in the proposed method in that a more generally moving object motion can be handled. To this end, a nonlinear observer is designed based on the relative dynamics between the object and camera so that the object velocity and the unknown camera velocity can be estimated. Stability analysis and simulation results for the moving object are provided to show the effectiveness of the proposed method.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.768-772
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• 2009

This paper proposes a method for measurement three-dimensional trajectories of bubbles generated around a swimmer's arms from stereo high-speed camera videos. This method is based on two techniques: two-dimensional trajectory estimation in single-camera images and trajectory pair matching in stereo-camera images. The two-dimensional trajectory is estimated by block matching using similarity of bubble shape and probability of bubble displacement. The trajectory matching is achieved by a consistensy test using epipolar constraint in multiple frames. The experimental results in two-dimensional trajectory estimation showed the estimation accuracy of 47% solely by the general optical flow estimation, whereas 71% taking the bubble displacement into consideration. This concludes bubble displacement is an efficient aspect in this estimation. In three-dimensional trajectory estimation, bubbles were visually captured moving along the flow generated by an arm; which means an efficient material for swimmers to swim faster.

• Advances in robotics research
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• 제2권2호
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• pp.129-140
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• 2018

With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• 한국멀티미디어학회논문지
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• 제16권2호
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• pp.131-137
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• 2013

동영상의 줌 움직임 추정은 구현이 아주 복잡하다. 본 논문에서는 줌 움직임 추정을 구현하기 위하여 깊이 카메라와 색상 카메라를 동시에 이용하는 방법을 제안한다. 깊이 카메라로부터 현재블록과 참조블록 사이의 거리 정보를 얻고, 이 거리 정보로부터 두 블록사이의 줌 비율을 계산한다. 줌 비율에 맞게 참조블록을 확대 또는 축소시켜 줌으로서 움직임 추정 차신호를 줄일 수 있다. 따라서, 제안된 방법은 줌 움직임 추정을 위한 복잡도가 크지 않으면서 움직임 추정 정확도를 높이는 것이 가능하다. 모의실험을 바탕으로 제안된 방법의 움직임 추정 정확도를 측정하였으며, 기존 블록정합 방법에 비하여 움직임 추정 오차값이 크게 감소함을 확인하였다.