• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3172-3193
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• 2018

Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.881-888
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• 1997

The existing method s for curvature estimation have a common problem in determining a unique smoothong factor. we previously proposed two approaches to overcome that problem: a constrained regularization approach and a mean field annealing approach. We consistently detected corners from the perprocessed smooth boundary obtained by either the constrained eglarization approach or the mean field annealing approach. Moreover, we defined corner sharpness to increase the robustness of both approaches. We evaluate the performance of those methods proposed in this paper. In addition, we show some matching results using a two-dimensional Hopfield neural network in the presence of occlusion as a demonstration of the power of our proposed methods.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.57-63
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• 2016

In generally, the resolution of reconstructed three-dimensional images can be seriously degraded by undesired occlusions in the integral imaging system, because the undesired information of the occlusion overlap the three-dimensional images to be reconstructed. To solve the problem of the undesired occlusion, we present an exemplar-based image restoration method in integral imaging system. In the proposed method, a minimum spanning tree-based stereo matching method is used to remove the region of undesired occlusions in each elemental image. After that, the removed occlusion region of each elemental images are re-established by using the exemplar-based image restoration method. For further improve the performance of the image restoration, the structure tensor is used to solve the filling error cause by discontinuous structures. Finally, the resolution enhanced three-dimensional images are reconstructed by using the restored elemental images. The preliminary experiments are presented to demonstrate the feasibility of the proposed method.

• Journal of Chest Surgery
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• v.38 no.10 s.255
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• pp.710-713
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• 2005

Acute abdominal Aortic occlusion is rare but it is a vascular emergency with high mortality and morbidity. There­fore, delay in diagnosis can have severe impact on the prognosis. A 60-year-old women complained of paresthesia, paralysis, and severe pain in bilateral lower extremities on 13th day after open heart surgery for mitral stenosis, atrial fibrillation, coronary arterial stenosis, tricuspid regurgitation, and atrial septal defect. Her skin was mottled and cool from the umbilicus to the feet, and there were no palpable pulses in the lower exteremities. We diagnosed an acute abdominal aortic occlusion using the Multi-Detector Row Spiral Computed Tomography and successfully treated the problem with emergent thrombo-embolectomy and Aortobifemoral bypass.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Journal of Korea Game Society
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• v.20 no.2
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• pp.183-192
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• 2020

Due to the problem of matching between virtual world space and real-world space, the reality of augmented reality content is rather low. There are many reasons for this result, firstly virtual object is rendered without considering relation between real-world space and virtual world space. Secondly, virtual objects rely too much on the marker to reduce reality. We propose two schemes to improve the reality of augmented reality, one is people occlusion, the other is to reduce the dependence of virtual objects on the marker.

• Korean Journal of Geomatics
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• v.1 no.1
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• pp.7-13
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• 2001

Geospatial Information Systems (GIS) have been employed to systematically manage and design land use in urban areas. This has increased the need for more accurate vector and raster data. In Korea, l/l,000-scale digital maps are used as vector data for the facility management in urban areas. This has increased the need for large scale orthoimages. Orthoimages generated from aerial imagery can provide accurate information, making possible the more effective city management. However, there is a large problem in using the orthoimages, i.e., currently available conventional orthoimages have not been generated based on Digital Elevation Model (DEM) that takes into account the building heights. So this causes the displacements of building image in large scale orthoimages. The present study is an attempt to generate the large scale orthoimages based on building DEM. The semiautomatic building extraction method can detect building outlines by mouse clicking on either building roofs or corners. Building DEM, based on the outline and calculated building height, was used to produce the large scale orthoimages with the corrected building occlusion.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.17 no.1
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• pp.223-232
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• 1987

The author obtained the transcranial-oblique lateral radiograms from 78 patients(26 male, 52 female) with temporomandibular dysfunction problem. And then, the author analyzed the dimensional changes of the TMJ space on centric occlusion, horizontal condylar movement and antero-posterior positional relationship of condyle to the articular eminence on 2.54㎝ mouth opening with clicking, TMJ pain and mouth opening limitation repectively, which were the symptoms of the temporomandibular joint pain dysfunction problem, and compared these data with control group. The results were as follows: 1. In centric occlusion, anterior and posterior TMJ space of experimental group was slightly lesser than those of the control group, also superior TMJ space of experimental group was significantly lesser than that of the control group. (p<0.01) 2. In 2.54㎝ mouth opening, the condylar horizontal movement and the antero-posterior positional relationship to the articular eminence were significantly lesser than those of the control group. (p<0.01) 3. Examined experimental group, the degree of condylar horizontal movement of affected ide was lesser than that of the normal side in 2.54㎝ mouth opening.

• The korean journal of orthodontics
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• v.2 no.1
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• pp.35-40
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• 1971

Since malocclusion affects a large segment of the population, it is by definition a public health problem. The etiology ana treatment of malocclusions have been studied by clinicians; however epidemioloic aspect of tile problem have been neglected. This study was undertaken using Angle's classification to obtain and to evaluate epidemiologic data on the prevalence of malocclusion in a group of 2,378 Yonsei University students, 17 to 23 years of age. All freshmen were selected, except for those students receiving orthodontic treatment and those few with too many missing teeth which prohibits classification by Angle's method. The following results were obtained: 1) Almost $91\%$ of students had malocclusion of the teeth severe enough to require correction. 2) There was a statistically significant difference in malocclusion between males and females($93.66\%$ malocclusion in males, $79.13\%$ malocclusioa in females). 3) Crowding was most pravalent in class I malocclusion. 4) There appeared to be a specific association between the number of lost first molars and Angle's classification. 5) In this study, more class II, Div.2 malocclusion appeared than in Massier's and Frankel's study of Caucasians, which used similar criteria. Class III malocclusion was more prevalent than normal occlusion in the Korean students studied, but in Caucasians' normal occlusion was more prevalent.