• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

In this paper, we analyze geometrical relations of 3D shape reconstruction from 2D images taken under anne projection. The purpose of this research is to contribute to more accurate 3-D reconstruction under noise distribution by analyzing geometrically the 2D to 3D relationship. In situation for no missing feature points (FPs) or no noise in 2D image plane, the accurate solution of 3D shape reconstruction is blown to be provided by Singular Yalue Decomposition (SVD) factorization. However, if several FPs not been observed because of object occlusion and image low resolution, and so on, there is no simple solution. Moreover, the 3D shape reconstructed from noise-distributed FPs is peturbed because of the influence of the noise. This paper focuses on analysis of geometrical properties which can interpret the missing FPs even though the noise is distributed on other FPs.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.150-157
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• 2015

Pedestrian detection has largely been researched as one of the important technologies for autonomous driving vehicle and preventing accidents. There are two categories for pedestrian detection, camera-based and LIDAR-based. LIDAR-based methods have the advantage of the wide angle of view and insensitivity of illuminance change while camera-based methods have not. However, there are several problems with 3D LIDAR, such as insufficient resolution to detect distant pedestrians and decrease in detection rate in a complex situation due to segmentation error and occlusion. In this paper, two methods using GM-PHD filter are proposed to improve the poor rates of pedestrian detection algorithms based on 3D LIDAR. First one improves detection performance and resolution of object by automatic accumulation of points in previous frames onto current objects. Second one additionally enhances the detection results by applying the GM-PHD filter which is modified in order to handle the poor situation to classified multi target. A quantitative evaluation with autonomously acquired road environment data shows the proposed methods highly increase the performance of existing pedestrian detection algorithms.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.449-460
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• 2005

This paper proposes a method to track persons robustly in illumination changes and partial occlusions in color video frames acquired from a fixed camera. To solve a problem of changing appearance by illumination change, a time-independent intrinsic image is used to remove noises in an frame and is adaptively updated frame-by-frame. We use a hierarchical human model including body color information in order to track persons in occlusion. The tracked human model is recorded into a persons' list for some duration after the corresponding person's exit and is recovered from the list after her reentering. The proposed method was experimented in several indoor and outdoor scenario. This demonstrated the potential effectiveness of an adaptive model-base method that corrected distorted person's color information by lighting changes, and succeeded tracking of persons which was overlapped in a frame.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8A
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• pp.679-688
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• 2012

In this paper, performance improved hole-filling algorithm including boundary noise removing pre-process which can be used for an arbitrary view synthesis with given two views is proposed. Boundary noise usually occurs because of the boundary mismatch between the reference image and depth map and common-hole is defined as the occluded region. These boundary noise and common-hole created while synthesizing a virtual view result in some defects and they are usually very difficult to be completely recovered by using only given two images as references. The spiral weighted average algorithm gives a clear boundary of each object by using depth information and the gradient searching algorithm is able to preserve details. In this paper, we combine these two algorithms by using a weighting factor ${\alpha}$ to reflect the strong point of each algorithm effectively in the virtual view synthesis process. The experimental results show that the proposed algorithm performs much better than conventional algorithms.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.236-247
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• 2010

Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5459-5473
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• 2017

Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

• The Korea Journal of Herbology
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• v.26 no.3
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• pp.7-14
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• 2011

Object : This study evaluated the effects of Daeseungkitang(DSK) on cerebral infarct of middle cerebral artery occlusion(MCAO). Method : Sprague-Dawley rats are used for observing to induce cerebral infraction closing its middle cerebral artery temporarily and take DSK by mouth the next 5 days, observe the amount of feces and urine. It is investigated the correlation between them after examining neurological score. Results : It is resulted the below. On the 2nd day of taking DSK, the total amount of feces of the cerebral infarct rats is increased significantly. After taking DSK, the urine volume of the cerebral infarct rats does not change at all. Taking DSK significantly improves neurological score of the cerebral infarct rats. There is a significant correlation between total amount of feces of the cerebral infarct rats and neurological score, otherwise there is no significant correlation between total amount of feces and neurological score which is taken DSK. By taking DSK, the volume of cerebral infarction does not decrease significantly. Taking DSK restrains the expression of iNOS in the cerebral cortex and striatum of the cerebral infarct rats. Taking DSK restrains the expression of MMP-9 in the cerebral cortex of the cerebral infarct rats. Taking DSK restrains the edema of astrocytes of the positive reaction of GFAP in the cerebral cortex of the cerebral infarct rats. Conclusion : According to above results, Daeseungkitang(DSK) is assumed that showing reaction of protecting neuron cell by restraint brain tissue edema thorough controlling water balance.

• Journal of Sasang Constitutional Medicine
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• v.21 no.2
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• pp.48-57
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• 2009

1. Objective : The object of this thesis is to find the basis of Constitution assignment of Nogeun(蘆根, Phragmites communis Trin.) used to the medication for Taeyangin. Also, it is to recognize what kind of Constitution of Mogeun(茅根, Imperata cylindrica var. koenigii) is needed to be assigned to. 2. Methods "Dongyi Soose Bowon", 'SinchukBon', 'ChobonKwun', other related Sasang Constitutional Medicine(SCM) books, herbal medicine books such as "Boncho Kangmok", and etc. were compared and researched. 3. Results & Conclusions : 1) Nogeun(蘆根) lowers Qi and harmonizes the body. Because of the effect of lowering soar-Qi(氣), it used to treat the symptoms of Taeyangin's vomiting(噎膈反胃, Stomach reflux due to dysphagia-occlusion). Also Yuksoo Nogeun(逆水蘆恨, Reed growing near the river in low scream) is the basis of considering inhale-gathering Qi effect as a major indication of Nogeun. 2) The theory of classifying White Mogeun as a Tae-eumin Medicinal is based on the effect of Radiating while classifying White Mogeun as a Taeyangin Medicinal is based on the effect of treating stomach reflux(反胃). But both basis are not conclusive and thus requires further study. 3) In "Sasang Geumge Bibang", the first text ever to write only about separate medicinals and Classified Foods (食物類) of each constitution, there were examples of Nogeun and Mogeun's usage based on other pre-existing medical texts. 4) Because White Mogeun is classified as Tae-yangin medication in "Dongmu Yugo", but classified as a Taeeumin's medication in "Dongyi Soose Bowon" 'ChobonKwun' and "Sasang Geumge Bibang", there remains a controversy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.63-71
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• 2008

In this paper, we propose a color based hierarchically propagated particle filter that extends the color based particle filter into the articulated upper body tracking. Since color feature is robust to partial occlusion and rotation, the color based particle filter is widely used for object tracking. However, in articulated body tacking, it is not desirable to use the traditional particle filter because the dimension of the state vector usually is high and thus, many samples are required for robust hacking. To overcome this problem, we use a hierarchical tracking method for each body part based on the blown body part. By using a hierarchical tracking method, we can reduce the number of samples for robust tracking in the cluttered environment. Also for human pose recognition, we classify the human pose into eight categories using Support Vector Machine(SVM) according to the angle between upper- arm and fore-arm. Experimental results show that our proposed method is more efficient than the traditional particle filter.