• Journal of the Optical Society of Korea
• /
• v.14 no.3
• /
• pp.245-259
• /
• 2010

We have developed mathematically precise image-processing algorithms for extracting panoramic images from fisheye images. Furthermore, we have successfully built a DSP-based panoramic camera employing single fisheye lens.

• Journal of Korea Multimedia Society
• /
• v.24 no.4
• /
• pp.538-549
• /
• 2021

In this paper, we introduce a technique for 360-degree panoramic video streaming with multiple virtual cameras in real-time. The proposed technique consists of generating 360-degree panoramic video data by ORB feature point detection, texture transformation, panoramic video data compression, and RTSP-based video streaming transmission. Especially, the generating process of 360-degree panoramic video data and texture transformation are accelerated by CUDA for complex processing such as camera calibration, stitching, blending, encoding. Our experiment evaluated the frames per second (fps) of the transmitted 360-degree panoramic video. Experimental results verified that our technique takes at least 30fps at 4K output resolution, which indicates that it can both generates and transmits 360-degree panoramic video data in real time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.155-156
• /
• 2010

`Panoramic image' is called generally 'mosaic image', to create a new image by matching the number of relevant images. In this paper, we are entering data through the camera. Therefore, perspective model was used for recognition of camera parameters, minimizing the discrepancies by proposing measure of discrepancy between the frames. In addition, how to create panoramic images is proposed by fixed reference and time-varying reference in order to create panoramic images.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.3
• /
• pp.67-73
• /
• 2007

This paper presents a panoramic reference image generation based automatic algorithm for moving objects detection robust to illumination variations under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally. aligning and reorganizing this images. In generation of the cylindrical panoramic image, most of previous works assume the static environment. We propose the method to generating the panoramic reference image from dynamic environments in this paper. We develop an efficient approach for panoramic reference image generation by using accumulated edge map as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The experimental results show that panoramic reference image generation robust to illumination variations can be possible using the proposed method.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.2
• /
• pp.137-148
• /
• 2004

In this paper, we propose a new camera calibration method for rotating multi-view cameras to generate image-based panoramic 3D Virtual Environment. Since calibration accuracy worsens with an increase in distance between camera and calibration pattern, conventional camera calibration algorithms are not proper for panoramic 3D VE generation. To remedy the problem, a geometric relationship among all lenses of a multi-view camera is used for intra-camera calibration. Another geometric relationship among multiple cameras is used for inter-camera calibration. First camera parameters for all lenses of each multi-view camera we obtained by applying Tsai's algorithm. In intra-camera calibration, the extrinsic parameters are compensated by iteratively reducing discrepancy between estimated and actual distances. Estimated distances are calculated using extrinsic parameters for every lens. Inter-camera calibration arranges multiple cameras in a geometric relationship. It exploits Iterative Closet Point (ICP) algorithm using back-projected 3D point clouds. Finally, by repeatedly applying intra/inter-camera calibration to all lenses of rotating multi-view cameras, we can obtain improved extrinsic parameters at every rotated position for a middle-range distance. Consequently, the proposed method can be applied to stitching of 3D point cloud for panoramic 3D VE generation. Moreover, it may be adopted in various 3D AR applications.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.6
• /
• pp.663-673
• /
• 2007

This paper presents a new moving obstacle detection method using an optical flow in mobile robot with an omnidirectional camera. Because an omnidirectional camera consists of a nonlinear mirror and CCD camera, the optical flow pattern in omnidirectional image is different from the pattern in perspective camera. The geometry characteristic of an omnidirectional camera has influence on the optical flow in omnidirectional image. When a mobile robot with an omnidirectional camera moves, the optical flow is not only theoretically calculated in omnidirectional image, but also investigated in omnidirectional and panoramic images. In this paper, the panoramic image is generalized from an omnidirectional image using the geometry of an omnidirectional camera. In particular, Focus of expansion (FOE) and focus of contraction (FOC) vectors are defined from the estimated optical flow in omnidirectional and panoramic images. FOE and FOC vectors are used as reference vectors for the relative evaluation of optical flow. The moving obstacle is turned out through the relative evaluation of optical flows. The proposed algorithm is tested in four motions of a mobile robot including straight forward, left turn, right turn and rotation. The effectiveness of the proposed method is shown by the experimental results.

• Korean Journal of Remote Sensing
• /
• v.24 no.3
• /
• pp.223-233
• /
• 2008

In the mid 90's, the U.S. government released images acquired by the first generation of photo reconnaissance satellite missions between 1960 and 1972. The Declassified Intelligent Satellite Photographs (DISP) from the Corona mission are of high quality with an astounding ground resolution of about 2 m. The KH-4A panoramic camera system employed a scan angle of $70^{\circ}$ that produces film strips with a dimension of $55\;mm\;{\times}\;757\;mm$. Since GPS/INS did not exist at the time of data acquisition, the exterior orientation must be established in the traditional way by using control information and the interior orientation of the camera. Detailed information about the camera is not available, however. For reconstructing points in object space from DISP imagery to an accuracy that is comparable to high resolution (a few meters), a precise camera model is essential. This paper is concerned with the derivation of a rigorous mathematical model for the KH-4A/B panoramic camera. The proposed model is compared with generic sensor models, such as affine transformation and rational functions. The paper concludes with experimental results concerning the precision of reconstructed points in object space. The rigorous mathematical panoramic camera model for the KH-4A camera system is based on extended collinearity equations assuming that the satellite trajectory during one scan is smooth and the attitude remains unchanged. As a result, the collinearity equations express the perspective center as a function of the scan time. With the known satellite velocity this will translate into a shift along-track. Therefore, the exterior orientation contains seven parameters to be estimated. The reconstruction of object points can now be performed with the exterior orientation parameters, either by intersecting bundle rays with a known surface or by using the stereoscopic KH-4A arrangement with fore and aft cameras mounted an angle of $30^{\circ}$.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.3
• /
• pp.206-210
• /
• 2011

Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation coefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effective in global localization of mobile robots and robust to lighting variations.

• Journal of Broadcast Engineering
• /
• v.23 no.2
• /
• pp.197-205
• /
• 2018

Panoramic image is one of the technologies that are commonly used today. However, technical difficulties still exist in panoramic video production. Without a special camera such as a 360-degree camera, making panoramic video becomes more difficult. In order to make a panoramic video, it is necessary to synchronize the timeline of multiple videos shot at multiple locations. However, the timeline synchronization method using the internal clock of the camera may cause an error due to the difference of the internal hardware. In order to solve this problem, timeline synchronization between multiple videos using visual information or auditory information has been studied. However, there is a problem in accuracy and processing time when using video information, and there is a problem in that, when using audio information, there is no synchronization when there is sensitivity to noise or there is no melody. Therefore, in this paper, we propose a timeline synchronization method between multiple video using audio waveform. It shows higher synchronization accuracy and temporal efficiency than the video information based time synchronization method.

• Journal of information and communication convergence engineering
• /
• v.10 no.4
• /
• pp.411-419
• /
• 2012

This paper proposes a semi-automatic image-based approach for 3-dimensional (3D) modeling of buildings along streets. Image-based urban 3D modeling techniques are typically based on the use of aerial and ground-level images. The aerial image of the relevant area is extracted from publically available sources in Google Maps by stitching together different patches of the map. Panoramic images are common for ground-level recording because they have advantages for 3D modeling. A panoramic video recorder is used in the proposed approach for recording sequences of ground-level spherical panoramic images. The proposed approach has two advantages. First, detected camera trajectories are more accurate and stable (compared to methods using multi-view planar images only) due to the use of spherical panoramic images. Second, we extract the texture of a facade of a building from a single panoramic image. Thus, there is no need to deal with color blending problems that typically occur when using overlapping textures.