• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.389-393
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• 2008

Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.165-172
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• 2013

In this paper, high-quality mosaic image is generated by high-resolution hyperspectral strip images using scale-invariant feature transform (SIFT) algorithm, which is one of the representative image matching methods. The experiments are applied to AISA Eagle images geo-referenced by using GPS/INS information acquired when it was taken on flight. The matching points between three strips of hyperspectral images are extracted using SIFT method, and the transformation models between images are constructed from the points. Mosaic image is, then, generated using the transformation models constructed from corresponding images. Optimal band appropriate for the matching point extraction is determined by selecting representative bands of hyperspectral data and analyzing the matched results based on each band. Mosaic image generated by proposed method is visually compared with the mosaic image generated from initial geo-referenced AISA hyperspectral images. From the comparison, we could estimate geometrical accuracy of generated mosaic image and analyze the efficiency of our methodology.

• Journal of the Korea Computer Graphics Society
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• v.18 no.1
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• pp.1-9
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• 2012

Video-based modeling / rendering developed to produce photo-realistic video contents have been one of the important research topics in computer graphics and computer visions. To smoothly combine original input video clips and 3D graphic models, geometrical information of light sources and cameras used to capture a scene in the real world is essentially required. In this paper, we present a simple technique to estimate the position and orientation of an optimal light source from the topology of objects and the silhouettes of shadows appeared in the original video clips. The technique supports functions to generate well matched shadows as well as to render the inserted models by applying the estimated light sources. Shadows are known as an important visual cue that empirically indicates the relative location of objects in the 3D space. Thus our method can enhance realism in the final composed videos through the proposed shadow generation and rendering algorithms in real-time.

• Journal of the Korean earth science society
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• v.28 no.7
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• pp.847-856
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• 2007

The Planetary nebula NGC 6881 displays quadrupole morphology and it also has a jet feature in its image. We investigated the line profiles of the optical region spectral emission lines, using the Hamilton Echelle Spectrograph (HES) at the Lick observatory. The HES data obtained in this study was the radiation coming from the inner region within the diameter of 4 second of arc. Expansion velocity was obtained, based on the strong emission line profiles of e.g. H, Hel, Hell, [OIII], [NII], [ArIII], [SII], and [SIII}, using the IRAF and StarLink/Dipso reduction packages. The HI recombination lines showed one single peak profile, while the He and forbidden strong lines displayed double peaks. The results of this study show that the outflow velocity of gas increases radially outwards due to the central stellar radiation pressure. It was concluded that three central rings appeared in the HST image are the result of a combined structure of bipolar cones (seen in e.g. HI lines) and a ring (seen in He, [SIII] lines) in projection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1725-1731
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• 2004

The use of gestures provides an attractive alternate to cumbersome interface devices for human-computer interaction. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures. The most important issues in gesture recognition are the simplification of algorithm and the reduction of processing time. The mathematical morphology based on geometrical set theory is best used to perform the processing. A key idea of proposed algorithm in this paper is to apply morphological shape decomposition. The primitive elements extracted to a hand gesture include in very important information on the directivity of the hand gestures. Based on this characteristic, we proposed the morphological gesture recognition algorithm using feature vectors calculated to lines connecting the center points of a main-primitive element and sub-primitive elements. Through the experiment, we demonstrated the efficiency of proposed algorithm. Coupling natural interactions such as hand gesture with an appropriately designed interface is a valuable and powerful component in the building of TV switch navigating and video contents browsing system.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.773-779
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• 2003

Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

• Publications of The Korean Astronomical Society
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• v.15 no.spc1
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• pp.103-112
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• 2000

Symbiotic stars are known as binary systems of a giant with heavy mass loss and a white dwarf accompanied by an emission nebula. They often show bipolar nebulae, and are believed to form an accretion disk around the white dwarf component by attracting the slow but heavy stellar wind around the giant companion. However, the existence and physical properties of the accretion disk in these systems still remain controversial. Unique to the spectra of symbiotic stars is the existence of the symbiotic bands around $6830{\AA}$ and $7088{\AA}$, which have been identified by Schmid (1989) as the Raman scattered features of the O VI $1032{\AA}$ and $1038{\AA}$ doublet by atomic hydrogen. Due to the incoherency of the Raman scattering, these features have very broad profiles and they are also strongly polarized. In the accretion disk emission model, it is expected that the Raman features are polarized perpendicular to the binary axis and show multiple peak structures in the profile, because the neutral scatterers located near the giant component views the accretion disk in the edge-on direction. Assuming the presence of scattering regions outflowing in the polar directions, we may explain the additional red wing or red peak structure, which is polarized parallel to the binary axis. We argue that in the accretion disk emission model it is predicted that the profile of the Raman feature around $6830{\AA}$ is different from the profile of the $7088{\AA}$ because the O VI line optical depth varies locally around the white dwarf component. We conclude that the Raman scattered features are an important tool to investigate the physical conditions and geometrical configuration of the accretion disk in a symbiotic star.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.55-62
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching, using linear features, is presented. Scene or model images are described by a set of linear features approximating edge information, which can be obtained by the conventional edge detection, thinning, and piecewise linear approximation. A set of candidate parameters are hypothesized by mapping the angular difference and a new distance measure to the Hough space and by detecting maximally consistent points. These hypotheses are verified by a fast linear feature matching algorithm composed of a single-step relaxation and a Hough technique. The proposed method is shown to be much faster than the conventional one where the relaxation process is repeated until convergence, while providing matching performance robust to the random alteration of the linear features, without a priori information on the geometrical transformation parameters.