• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.27-38
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• 2017

This Paper Presents a Method for Stitching a Large Number of Images Recorded by a Large Number of Individual Users Through a Cellular Phone Camera at a Venue. In Contrast to 360 Camera Solutions that Use Existing Fixed Rigs, these Conditions must Address New Challenges Such as Time Synchronization, Repeated Transformation Matrix Calculations, and Camera Sensor Mismatch Correction. In this Paper, we Solve this Problem by Updating the Transformation Matrix Using Time Synchronization Method Using Audio, Sensor Mismatch Removal by Color Transfer Method, and Global Operation Stabilization Algorithm. Experimental Results Show that the Proposed Algorithm Shows better Performance in Terms of Computation Speed and Subjective Image Quality than that of Screen Stitching.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.35-43
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• 1997

In monitor-based AR(Augmented Reality) systems, it is required to know the position and direction of a camera in order to combine real images from a camera with virtual images exactly_ Because a tracker is parted from a camera, however, there is a registration error caused by the inconsistency of a tracker with a camera. In this paper, we describe the error correction method using genetic algorithm. This method looks for the position and direction of a camera using genetic algorithm and solves the error correction matrix of it. And then it is registered of the real images and the revised virtual image. It has an effect on the error correction caused by the misalignment of a tracker with a camera in complex AR systems.

• Journal of Korean Ophthalmic Optics Society
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• v.3 no.1
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• pp.201-207
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• 1998

It was theoretically calculated the image position and size using matrix to obtain the reflection pattern for eye's cornea and crystalline, and made system to measure the reflection pattern by three light sources and a reflex camera. Hyperopia and myopia were measured by reflect pattern using single light source at retina, and cornea and curvature of crystalline were measured by the reflection pattern using double light sources.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.983-988
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• 2011

This paper presents a robust method for ground plane detection in vision-based applications based on a monocular sequence of images with a non-stationary camera. The proposed method, which is based on the reliable estimation of the homography between two frames taken from the sequence, aims at designing a practical system to detect road surface from traffic scenes. The homography is computed using a feature matching approach, which often gives rise to inaccurate matches or undesirable matches from out of the ground plane. Hence, the proposed homography estimation minimizes the effects from erroneous feature matching by the evaluation of the difference between the predicted and the observed matrices. The method is successfully demonstrated for the detection of road surface performed on experiments to fill an information void area taken place from geometric transformation applied to captured images by an in-vehicle camera system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1785-1791
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• 2003

This paper presents the mosaic method that the video sequence with shift and rotation information after Mellin Transform. The results are used to compute the projection matrix for each image registration. So before registration, we process camera calibration in order to reduce the image warp by camera and then compute the global projection matrix for image registration for reducing errors from rut image to last image. This paper describes the mosaic method that compute duplication and movement information quickly and robust noise using projection matrix on Mellin Transform.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.314-323
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• 1999

This paper introduces a methodology of active calibration of a camera pose (orientation and position) using the images of cylindrical objects that are going to be manipulated. This active calibration method is different from the passive calibration where a specific pattern needs to be located at a certain position. In the active calibration, a camera attached on the robot captures images of objects that are going to be manipulated. That is, the prespecified position and orientation data of the cylindrical object are transformed into the camera pose through the two consecutive image frames. An ellipse can be extracted from each image frame, which is defined as a circular-feature matrix. Therefore, two circular-feature matrices and motion parameters between the two ellipses are enough for the active calibration process. This active calibration scheme is very effective for the precise control of a mobile/task robot that needs to be calibrated dynamically. To verify the effectiveness of active calibration, fundamental experiments are peformed.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.508-518
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• 2016

In this paper, we propose a method combining an accelerometer with a cross structured light system to estimate the golf green slope. The cross-line laser provides two laser planes whose functions are computed with respect to the camera coordinate frame using a least square optimization. By capturing the projections of the cross-line laser on the golf slope in a static pose using a camera, two 3D curves’ functions are approximated as high order polynomials corresponding to the camera coordinate frame. Curves’ functions are then expressed in the world coordinate frame utilizing a rotation matrix that is estimated based on the accelerometer’s output. The curves provide some important information of the green such as the height and the slope’s angle. The curves estimation accuracy is verified via some experiments which use OptiTrack camera system as a ground-truth reference.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.30-35
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• 2017

Moving object segmentation from a nonstationary camera is a difficult problem due to the motion of both camera and the object. In this paper, we propose a new confidence-based background subtraction technique from moving camera. The method is based on clustering of motion vectors and generating adaptive multi-homography from a pair of adjacent video frames. The main innovation concerns the use of confidence images for each foreground and background motion groups. Experimental results revealed that our confidence-based approach robustly detect moving targets in sequences taken by a freely moving camera.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.785-796
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• 2019

Due to the view point, illumination, personal gait and other background situation, person re-identification across cameras has been a challenging task in video surveillance area. In order to address the problem, a novel method called Joint Bayesian across different cameras for person re-identification (JBR) is proposed. Motivated by the superior measurement ability of Joint Bayesian, a set of Joint Bayesian matrices is obtained by learning with different camera pairs. With the global Joint Bayesian matrix, the proposed method combines the characteristics of multi-camera shooting and person re-identification. Then this method can improve the calculation precision of the similarity between two individuals by learning the transition between two cameras. For investigating the proposed method, it is implemented on two compare large-scale re-ID datasets, the Market-1501 and DukeMTMC-reID. The RANK-1 accuracy significantly increases about 3% and 4%, and the maximum a posterior (MAP) improves about 1% and 4%, respectively.