• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.1
• /
• pp.70-77
• /
• 2014

This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

• Journal of Broadcast Engineering
• /
• v.27 no.4
• /
• pp.487-498
• /
• 2022

Depth map is an image that contains distance information in 3D space on a 2D plane and is used in various 3D vision tasks. Many existing depth estimation studies mainly use narrow FoV images, in which a significant portion of the entire scene is lost. In this paper, we propose a technique for generating 360° omnidirectional RGBD images from a sparse set of narrow FoV images. The proposed generative adversarial network based image generation model estimates the relative FoV for the entire panoramic image from a small number of non-overlapping images and produces a 360° RGB and depth image simultaneously. In addition, it shows improved performance by configuring a network reflecting the spherical characteristics of the 360° image.

• KIEAE Journal
• /
• v.9 no.2
• /
• pp.81-90
• /
• 2009

Relating to grasping sequential landscape characteristics in consideration of the behavioral characteristics of the subject experiencing visual perception, this study was made on the subject of main walking line section for visitors of three treasures of Buddhist temples. Especially, as a method of obtaining data for grasping sequential visual perception landscape, the researcher employed [momentum sequential viewpoint setup] according to [the interval of pointers arbitrarily] and fisheye-lens-camera photography using the obtained omni-directional angle visual perception information. As a result, in terms of viewpoint selection, factors like approach road form, change in circulation axis, change in the ground surface level, appearance of objects, etc. were verified to make effect, and among these, approach road form and circulation axis change turned out to be the greatest influences. In addition, as a result of reviewing the effectiveness via the subjects, for the sake of qualitative evaluation of landscape components using the VR picture image obtained in the process of acquiring omni-directional angle visual perception information, a positive result over certain values was earned in terms of panoramic vision, scene reproduction, three-dimensional perspective, etc. This convinces us of the possibility to activate the qualitative evaluation of omni-directional angle picture information and the study of landscape through it henceforth.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.4
• /
• pp.517-524
• /
• 2007

This paper presents a global localization method using circular correlation of an omni-directional image. The localization of a mobile robot, especially in indoor conditions, is a key component in the development of useful service robots. Though stereo vision is widely used for localization, its performance is limited due to computational complexity and its narrow view angle. To compensate for these shortcomings, we utilize a single omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Nodes around a robot are extracted by the correlation coefficients of CHL (Circular Horizontal Line) between the landmark and the current captured image. After finding possible near nodes, the robot moves to the nearest node based on the correlation values and the positions of these nodes. To accelerate computation, correlation values are calculated based on Fast Fourier Transforms. Experimental results and performance in a real home environment have shown the feasibility of the method.

• Journal of Satellite, Information and Communications
• /
• v.9 no.4
• /
• pp.32-37
• /
• 2014

The panorama is a good alternative to overcome narrow FOV under study in robot vision, stereo camera and panorama image registration and modeling. The panorama can materialize view with angles wider than human view and provide realistic space which make feeling of being on the scene based on realism. If we use all correspondence, it is too difficult to find strong features and correspondences and assume accurate homography matrix in geographic changes in images as load of calculation increases. Accordingly, we used SURF algorithm to estimate overlapping areas with high similarity by comparing and analyzing the input images' histograms and to detect features. And we solved the problem of input order so we can make panorama by input images without order.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.55-63
• /
• 2008

This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

• Journal of Broadcast Engineering
• /
• v.22 no.6
• /
• pp.850-853
• /
• 2017

In this paper, we propose an image analysis system based on omnidirectional image and object tracking image display using super wide angle camera. In order to generate spherical images, the projection process of converting from two wide-angle images to the equirectangular panoramic image was performed and the spherical image was expressed by converting rectangular to spherical coordinate system. Object tracking was performed by selecting the desired object initially, and KCF(Kernelized Correlation Filter) algorithm was used so that robust object tracking can be performed even when the object's shape is changed. In the initial dialog, the file and mode are selected, and then the result is displayed in the new dialog. If the object tracking mode is selected, the ROI is set by dragging the desired area in the new window.

• Journal of IKEEE
• /
• v.11 no.4
• /
• pp.187-192
• /
• 2007

Since wireless sensor networks (WSN) have relatively narrow bandwidth and have limited memory space. Mosaic by inlaying images transmitted by adjacent sensors can provide wider field of view and smaller storage memory. Most WSN are used for surveillance purpose, image acquisition period should be sufficiently short, so that mosaic algorithm has to be run in real time. Proposed algorithm is derived by using the fact that position of sensor nodes are fixed and known. Transformation matrix can be calculated by using distance between sensor nodes and distance between sensor nodes and predefined object. Simulation result shows that proposed algorithm provides very short processing time whereas it preserves image quality.

• Journal of Broadcast Engineering
• /
• v.19 no.3
• /
• pp.316-328
• /
• 2014

In this paper, we parallelize the popular feature detection algorithms, i.e. SIFT and SURF, and its application to fast panoramic image generation on the latest embedded GPU. Parallelized algorithms are implemented using recently developed OpenCL as the embedded GPGPU software platform. We compare the implementation efficiency and speed performance of conventional OpenGL Shading Language and OpenCL. Experimental result shows that implementation on OpenCL has comparable performance with GLSL. Compared with the performance on the embedded CPU in the same application processor, the embedded GPU runs 3~4 times faster. As an example of using feature extraction, panorama image synthesis is performed on embedded GPU by applying image matching using detected features.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
• /
• v.24 no.2
• /
• pp.361-368
• /
• 1994

Radiographic planning is needed for implant placement in order to determine implant length, jaw bone volume, anatomical stucture and so on. Radiographic examination includes conventional radiography, conventional tomography and CT scan. The most accurate mesurement can be obtained from CT scan. For the cross-sectional view of mandible, CT scan reconstruction is generally needed. But the cross-sectional view of mandible can be reformed by personal computer. This study was performed to examine the clinical usefulness of reformed image using personal computer in comparison with CT scan reconstructed image. CT axial slices of 4 mandibles of 4 volunteers were used. Digital imaging system was composed of Macintosh Ⅱ ci computer, high resolution Sony XC-77 CCD camera, Quick Capture frame grabber board and 'NIH Image' program. Seven reconstructed cross-sectional images within CT machine(CT group) were obtained. And seven reformed cross-sectional images(PC group) after digitization of CT axial slices into the personal computer were obtained. PC group was compared with CT group in the objective and subjective aspects. The results were as follow: 1. Measurement of mandibular height & width in both group showed insignificant difference(P>0.05). 2. Subjective assessment of the mandibular canal in both group showed insignificant difference(P>0.05). 3. Image reformation using personal computer could provide panoramic view, which could not be obtained in CT scan reconstruction.