• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.804-809
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• 2004

It is essential to calibrate a camera in order to recover 3-dimensional reconstruction from uncalibrated images. This paper proposes a new technique of the camera calibration using a homography between the planar patterns image taken by the camera, which is located at the three planar patterns image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented more easily and simply to recover 3D object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate the examples of 3D reconstruction using the proposed algorithm from image sequence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.381-390
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• 2006

This paper proposes a new technque of the camera calibration to be computed a homography between the planar patterns taken by a single image to be located at the three planar patterns from uncalibrated images. It is essential to calibrate a camera for 3-dimensional reconstruction from uncalibrated image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented to more easily and simply to recover 3D reconstruction of an object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate examples of recovering 3D reconstruction using the proposed algorithm from uncalibrated images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.499-508
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• 2023

In this paper, we propose a technique to estimate the coordinates of feature points existing on a 2D planar object in the three dimensional space. The proposed method detects multiple 3D features from the image, and excludes those which are not located on the plane. The proposed technique estimates the planar homography between the planar object in the 3D space and the camera image plane, and computes back-projection error of each feature point on the planar object. Then any feature points which have large error is considered as off-plane points and are excluded from the feature estimation phase. The proposed method is archived on the basis of the planar homography without any additional sensors or optimization algorithms. In the expretiments, it was confirmed that the speed of the proposed method is more than 40 frames per second. In addition, compared to the RGB-D camera, there was no significant difference in processing speed, and it was verified that the frame rate was unaffected even in the situation that the number of detected feature points continuously increased.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.681-686
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• 2003

In this paper, we propose an algorithm to extract valid planar regions from stereo images for visual navigation of mobile robots. The algorithm is based on the difference image between the stereo images obtained by applying Homography matrix between stereo cameras. Illegal planar regions are filtered out by the use of labeling of the difference images and filtering of invalid blobs using the size of each blob. Also, illegal large planar regions such as walls are removed by adopting a weighted low-pass filtering of the difference image using the past difference images. The algorithms are experimented successfully by the use of stereo camera system built in a mobile robot and a PC-based real-time vision system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2299-2311
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• 2013

As portable multimedia devices become more popular and smaller, the use of portable projectors is also rapidly increasing. However, when portable projectors are used in mobile environments in which a dedicated planar screen is not available, the problem of geometric distortion of the projected image often arises. In this paper, we present a geometric image compensation method for portable projectors to compensate for geometric distortions of images projected on various types of planar or nonplanar projection surfaces. The proposed method is based on extraction of the two-dimensional (2D) geometric information of a projection area, setting of the compensation area, and prewarping using 2D homography. The experimental results show that the proposed method allows effective compensation for waved and arbitrarily shaped projection areas, as well as tilted and bent surfaces that are often found in the mobile environment. Furthermore, the proposed method is more computationally efficient than conventional image compensation methods that use 3D geometric information.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.31-40
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• 2006

In this paper, we propose a gait recognition method based on gait silhouette sequences. Features of gait are affected by the variation of gait direction. Therefore, we synthesize silhouettes to canonical form by using planar homography in order to reduce the effect of the variation of gait direction. The planar homography is estimated with only the information which exist within the gait sequences without complicate operations such as camera calibration. Even though gait silhouettes are generated from an individual person, fragments beyond common characteristics exist because of errors caused by inaccuracy of background subtraction algorithm. In this paper, we use the Principal Component Analysis to analyze the deviated characteristics of each individual person. PCA used in this paper, however, is not same as the traditional strategy used in pattern classification. We use PCA as a criterion to analyze the amount of deviation from common characteristic. Experimental results show that the proposed method is robust to the variation of gait direction and improves separability of test-data groups.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.27-33
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• 2012

Tele-presence and tele-operation techniques are used to build up an immersive scene and control environment for the distant user. This paper presents a novel tele-presence system using the camera tracking based on planar homography. In the first step, the user wears the HMD(head mounted display) with the camera and his/her head motion is estimated. From the panoramic image by the omni-directional camera mounted on the mobile robot, a viewing image by the user is generated and displayed through HMD. The homography of 3D plane with markers is used to obtain the head motion of the user. For the performance evaluation, the camera tracking results by ARToolkit and the homography based method are compared with the really measured positions of the camera.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.21-27
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• 2015

A conventional fire detection has been developed based on images captured from a fixed camera. However, It is difficult to apply current algorithms to a flying Quad-rotor to detect fire. To solve this problem, we propose that the fire detection algorithm can be modified for Quad-rotor using Ego-motion compensation. The proposed fire detection algorithm consists of color detection, motion detection, and fire determination using a randomness test. Color detection and randomness test are adapted similarly from an existing algorithm. However, Ego-motion compensation is adapted on motion detection for compensating the degree of Quad-rotor's motion using Planar Projective Transformation based on Optical Flow, RANSAC Algorithm, and Homography. By adapting Ego-motion compensation on the motion detection step, it has been proven that the proposed algorithm has been able to detect fires 83% of the time in hovering mode.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.155-170
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• 2020

Passive ranging is a critical part of machine vision measurement. Most of passive ranging methods based on machine vision use binocular technology which need strict hardware conditions and lack of universality. To measure the distance of an object placed on horizontal plane, we present a passive ranging method based on monocular vision system by smartphone. Experimental results show that given the same abscissas, the ordinatesis of the image points linearly related to their actual imaging angles. According to this principle, we first establish a depth extraction model by assuming a linear function and substituting the actual imaging angles and ordinates of the special conjugate points into the linear function. The vertical distance of the target object to the optical axis is then calculated according to imaging principle of camera, and the passive ranging can be derived by depth and vertical distance to the optical axis of target object. Experimental results show that ranging by this method has a higher accuracy compare with others based on binocular vision system. The mean relative error of the depth measurement is 0.937% when the distance is within 3 m. When it is 3-10 m, the mean relative error is 1.71%. Compared with other methods based on monocular vision system, the method does not need to calibrate before ranging and avoids the error caused by data fitting.