• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.351-357
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• 2008

An aerial multi-looking camera system equips itself with five separate cameras which enables acquiring one vertical image and four oblique images at the same time. This provides diverse information about the site compared to aerial photographs vertically. The geometric relationship of oblique cameras and a vertical camera can be modelled by 6 exterior orientation parameters. Once the relationship between the vertical camera and each oblique camera is determined, the exterior orientation parameters of the oblique images can be calculated by the exterior orientation parameters of the vertical image. In order to examine the exterior orientation of both a vertical camera and each oblique cameras in the multi-looking camera relatively, calibration targets were installed in a lab and 14 images were taken from three image stations by tilting and rotating a non-metric digital camera. The interior orientation parameters of the camera and the exterior orientation parameters of the images were estimated. The exterior orientation parameters of the oblique image with respect to the vertical image were calculated relatively by the exterior orientation parameters of the images and error propagation of the orientation angles and the position of the projection center was examined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.141-152
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• 2011

Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.38-44
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• 2023

This study aims to determine how agricultural drones are operated for flight tests using a 5G communication in order to carry out a mission such as sensing agricultural crop healthy status with special cameras. Drones were installed with a multi-spectral and IR camera to capture images of crop status in separate altitudes with different speeds. A multi-spectral camera can capture crop image data using five different particular wavelengths with a built-in GPS so that captured images with synchronized time could provide better accuracy of position and altitude during the flight time. Captured thermal videos are then sent to a ground server to be analyzed via 5G communication. Thus, combining two cameras can result in better visualization of vegetation areas. The flight test verified how agricultural drones equipped with special cameras could collect image data in vegetation areas.

• Current Optics and Photonics
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• v.7 no.5
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• pp.545-556
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• 2023

This paper introduces volume-sharing multi-aperture imaging (VMAI), a potential approach proposed for volume reduction in space-borne imagers, with the aim of achieving high-resolution ground spatial imagery using deep learning methods, with reduced volume compared to conventional approaches. As an intermediate step in the VMAI payload development, we present a phase-1 design targeting a 1-meter ground sampling distance (GSD) at 500 km altitude. Although its optical imaging capability does not surpass conventional approaches, it remains attractive for specific applications on small satellite platforms, particularly surveillance missions. The design integrates one wide-field and three narrow-field cameras with volume sharing and no optical interference. Capturing independent images from the four cameras, the payload emulates a large circular aperture to address diffraction and synthesizes high-resolution images using deep learning. Computational simulations validated the VMAI approach, while addressing challenges like lower signal-to-noise (SNR) values resulting from aperture segmentation. Future work will focus on further reducing the volume and refining SNR management.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.1-8
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• 2008

In this paper, an algorithm to compensate the inter-view mismatch in the multi-view video according to the different characteristics of cameras is presented. Interview mismatches make it difficult to merge the multi-view images and decrease the coding performance. So, a preprocessing operation to compensate the mismatches is requisite in the multi-view video coding. It is shown that the mismatch in the outputs of multi-view cameras with different electro-optical transfer functions can be approximated with a linear model of a gain and an offset. In addition, a new algorithm for estimating and compensating the inter-view mismatch based on the detection of the overlapped region is presented. Experimental results using various rectified stereo images show that the proposed method compensates inter-view mismatches more accurately compared to the conventional approach.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1093-1101
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• 2012

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding exploits inter-view correlations among pictures of neighboring views and temporal correlations among pictures of the same view. Multi-view video coding which uses many cameras requires a method to reduce the computational complexity. In this paper, we proposed an efficient prediction structure to improve performance of multi-view video coding. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several small groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experimental results show that the proposed prediction structure shows good performance in image quality and bit-rates. When compared to the performance of hierarchical B pictures of Fraunhofer-HHI, the proposed prediction structure achieved 0.07~0.13 (dB) of PSNR gain and was down by 6.5(Kbps) in bitrate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.205-216
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• 2014

Multi-camera systems have been widely used as cost-effective tools for the collection of geospatial data for various applications. In order to fully achieve the potential accuracy of these systems for object space reconstruction, careful system calibration should be carried out prior to data collection. Since the structural integrity of the involved cameras' components and system mounting parameters cannot be guaranteed over time, multi-camera system should be frequently calibrated to confirm the stability of the estimated parameters. Therefore, automated techniques are needed to facilitate and speed up the system calibration procedure. The automation of the multi-camera system calibration approach, which was proposed in the first part of this paper, is contingent on the automated detection, localization, and identification of the object space signalized targets in the images. In this paper, the automation of the proposed camera calibration procedure through automatic target extraction and labelling approaches will be presented. The introduced automated system calibration procedure is then implemented for a newly-developed multi-camera system while considering the optimum configuration for the data collection. Experimental results from the implemented system calibration procedure are finally presented to verify the feasibility the proposed automated procedure. Qualitative and quantitative evaluation of the estimated system calibration parameters from two-calibration sessions is also presented to confirm the stability of the cameras' interior orientation and system mounting parameters.

• Journal of KIISE
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• v.41 no.11
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• pp.900-910
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• 2014

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. The computational complexity of multi view video coding increases in proportion to the number of cameras. To reduce computational complexity and maintain the image quality, improved prediction structure and motion estimation method is proposed in this paper. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. And the proposed motion estimation method uses a hierarchical search strategy. This strategy method consists of modified diamond search pattern, progressive diamond search pattern and modified raster search pattern. Experiment results show that the complexity reduction of the proposed prediction structure and motion estimation method over JMVC (Joint Multiview Video Coding) reference model using hierarchical B pictures of Fraunhofer-HHI and TZ search method can be up to 40~70% while maintaining similar video quality and bit rates.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.329-336
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• 2017

In video compression, Motion Estimation(ME) limits the performance of image quality and generated bit rates. However, it requires much complexity in the encoder part. Multi-view video uses many cameras at different positions. Multi-view video coding needs huge computational complexity in proportion to the number of the cameras. To reduce computational complexity and maintain the image quality, an effective motion estimation method is proposed in this paper. The proposed method exploiting the characteristics of motion vector distribution and the motion of video. The proposed is a kind of a hierarchical search strategy. This strategy consists of multi-grid rhombus pattern, diagonal pattern, rectangle pattern, and refinement pattern. Experiment results show that the complexity reduction of the proposed method over TZ search method and PBS (Pel Block Search) on JMVC (Joint Multiview Video Coding) can be up to 40~75% and 98% respectively while maintaining similar video image quality and generated bit rates.