• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.297-301
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• 2005

In this paper, we propose a method to estimate camera motion parameter based on invariant point features. Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time. The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum. In order to complement these shortfalls, we, first propose constructing feature models using invariant vector of geometry. Secondly, we propose a two-stage calculation method to improve accuracy and convergence by using homography and LM method. In the experiment, we compare and analyze the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.85-90
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• 2022

In this study, to reduce the time and cost disadvantages of the traditional motion graphic production method in order to realize the movement of a virtual camera identical to that of the real camera, motion graphics virtualization using AR Core-based mobile device real-time tracking data A method for creating a camera is proposed. The proposed method is a method that simplifies the tracking operation in the video file stored after shooting, and simultaneously proceeds with shooting on an AR Core-based mobile device to determine whether or not tracking is successful in the shooting stage. As a result of the experiment, there was no difference in the motion graphic result image compared to the conventional method, but the time of 6 minutes and 10 seconds was consumed based on the 300frame image, whereas the proposed method has very high time efficiency because this step can be omitted. At a time when interest in image production using virtual augmented reality and various studies are underway, this study will be utilized in virtual camera creation and match moving.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.141-144
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• 2002

This paper describes a new feature based tracking system that can track moving objects with a pan-tilt camera. We extract corner features of the scene and tracks the features using filtering, The global motion energy caused by camera movement is eliminated by finding the maximal matching position between consecutive frames using Pyramidal template matching. The region of moving object is segmented by clustering the motion trajectories and command the pan-tilt controller to follow the object such that the object will always lie at the center of the camera. The proposed system has demonstrated good performance for several video sequences.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.131-137
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• 2013

Zoom motion estimation of video sequence is very complicated for implementation. In this paper, we propose a method to implement the zoom motion estimation using together the depth camera and color camera. Depth camera obtains the distance information between current block and reference block, then zoom ratio between both blocks is calculated from this distance information. As the reference block is appropriately zoomed by the zoom ratio, the motion estimated difference signal can be reduced. Therefore, the proposed method is possible to increase the accuracy of motion estimation with keeping zoom motion estimation complexity not greater. Simulation was to measure the motion estimation accuracy of the proposed method, we can see the motion estimation error was decreased significantly compared to conventional block matching method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.741-744
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• 2003

in this paper, we propose a dynamic-based compression system by creating mosaic background and transmitting the change information. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion information. For the camera motion estimation, we calculate perspective projection parameters for each frame sequentially with respect to its previous frame. The camera motion is robustly estimated on the background by discriminating between background and foreground regions. The modified block-based motion estimation is used to separate the background region.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.1000-1009
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• 1999

본 논문에서는 비디오 데이타를 분석하여 다양한 카메라의 동작을 정량적으로 추출하는 방법을 제안한다. 본 논문에서 제안하는 카메라의 동작 추출 방법은 어파인 모델을 이용한 방법으로 인접 영상으로부터 추출한 동작 벡터를 어파인 모델에 적용하고 회귀분석법을 통해 어파인 모델을 구성하는 파라미터를 구한다. 그런 다음, 파라미터들의 크기를 분석하고 상호 관계를 해석하여 카메라의 동작을 추출한다. 본 논문에서는 잡음이 포함된 동작 벡터를 필터링하여 사용하므로 잡음에 강건한 결과를 얻을 수 있다. 그리고 어파인 모델을 구성하는 파라미터만을 분석함으로써 카메라의 다양한 동작을 간단하면서도 비교적 정확하게 추출한다. 실험 결과는 카메라의 동작을 정확하게 추출하고 있음을 보여준다.Abstract This paper presents an elegant method, an affine-model based approach, that can qualitatively estimate the information of camera motion. We define various types of camera motion by means of parameters of an affine-model. To get those parameters from images, we fit an affine-model to the field of instantaneous velocities, rather than raw images. We correlate consecutive images to get instantaneous velocities. The size filtering of the velocities are applied to remove noisy components, and the regression approach is employed for the fitting procedure. The fitted values of the parameters are examined to get the estimates of camera motion. The experimental results show that the suggested approach can yield the qualitative information of camera motion successfully.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.65-80
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• 1999

This paper presents an elegant method, an affine-model based approach, that can qualitatively estimate the information of camera motion. We define various types of camera motion by means of parameters of an affine-model. To get those parameters form images, we fit an affine-model to the field of instantaneous velocities, rather than raw images. We correlate consecutive images to get instantaneous velocities. The size filtering of the velocities are applied to remove noisy components, and the regression approach is employed for the fitting procedure. The fitted values of the parameters are examined to get the estimates of camera motion. The experimental results show that the suggested approach can yield the qualitative information of camera motion successfully.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.716-725
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• 2007

In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.672-676
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• 2009

Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.