• Title/Summary/Keyword: Occlusion Problem

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A study on the Development and Evaluation of Sludge Occlusion Reduced Diffuser (폐색 저감형 산기관의 개발 및 적용성 평가)

  • Kim, Young-Hoon;Kim, Kwan-Yeop;Lee, Eui-Jong;Nam, Jong-Woo;Lee, Chang-Ha;Jeon, Min-Jung;Kim, Hyung-Soo
    • Journal of Korean Society of Water and Wastewater
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    • v.25 no.1
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    • pp.41-49
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    • 2011
  • The diffuser which is conventionally adapted to MBR, has problem that decreasing the cleaning effect of membrane module by inflexible air supply due to the occlusion of sludge from diffuser hole. To solve this problem, diffuser structure of submerged module should be improved to discharge sludge which is flow into the diffuser for prevent occlusion in the diffuser. In this study, the structure of the diffuser was reformed to open lower part for preclusion the blocking. And the outlet diameter of the diffuser was drawn through the condition for the depth of water and air rate, to prevent air-leak condition of improved diffuser. Moreover, application is evaluated by comparing test with occlusion effect of the conventional and improved diffuser. From the results, air-water boundary changes are steady with changes of water depth and it shows linear relation about air rate. By using this linear numerical formula, the height of diffuser's outlet can be decided. Also, it displays that it can prevent the occlusion effect during the comparing test. Hereafter, if this diffuser is applied to practical MBR process, the occlusion problem of diffuser will be disappeared.

Analysis on Occlusion Problem of Landmark-based Homing Navigation Methods (랜드마크 기반 귀소 내비게이션 알고리즘의 가림 현상 분석 및 비교)

  • Yu, Seung-Eun;Kim, Dae-Eun
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.596-601
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    • 2011
  • Autonomous navigating algorithms for mobile robots have been proved to be a difficult task. Based on the excellent homing performance shown by many insects, bio-inspired navigation algorithms for robotic experiments have been widely researched and applied to the design of navigational strategies for mobile robots. In this paper, among them, we analyze two simple landmark navigation methods their strengths and limits. We investigate the effect of the occlusion problem mainly, which is an important yet tough problem in many landmark navigation algorithms. In the point of view of the error of homing vector and the performance of the homing paths in the environment with artificial occlusions, we investigate the effect of occlusion problem in both methods in order to further study on solutions.

Weighted Parameter Analysis of L1 Minimization for Occlusion Problem in Visual Tracking (영상 추적의 Occlusion 문제 해결을 위한 L1 Minimization의 Weighted Parameter 분석)

  • Wibowo, Suryo Adhi;Jang, Eunseok;Lee, Hansoo;Kim, Sungshin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.101-103
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    • 2016
  • Recently, the target object can be represented as sparse coefficient vector in visual tracking. Due to this reason, exploitation of the compressibility in the transform domain by using L1 minimization is needed. Further, L1 minimization is proposed to handle the occlusion problem in visual tracking, since tracking failures mostly are caused by occlusion. Furthermore, there is a weighted parameter in L1 minimization that influences the result of this minimization. In this paper, this parameter is analyzed for occlusion problem in visual tracking. Several coefficients that derived from median value of the target object, mean value of the arget object, the standard deviation of the target object are, 0, 0.1, and 0.01 are used as weighted parameter of L1 minimization. Based on the experimental results, the value which is equal to 0.1 is suggested as weighted parameter of L1 minimization, due to achieved the best result of success rate and precision performance parameter. Both of these performance parameters are based on one pass evaluation (OPE).

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FD-StackGAN: Face De-occlusion Using Stacked Generative Adversarial Networks

  • Jabbar, Abdul;Li, Xi;Iqbal, M. Munawwar;Malik, Arif Jamal
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2547-2567
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    • 2021
  • It has been widely acknowledged that occlusion impairments adversely distress many face recognition algorithms' performance. Therefore, it is crucial to solving the problem of face image occlusion in face recognition. To solve the image occlusion problem in face recognition, this paper aims to automatically de-occlude the human face majority or discriminative regions to improve face recognition performance. To achieve this, we decompose the generative process into two key stages and employ a separate generative adversarial network (GAN)-based network in both stages. The first stage generates an initial coarse face image without an occlusion mask. The second stage refines the result from the first stage by forcing it closer to real face images or ground truth. To increase the performance and minimize the artifacts in the generated result, a new refine loss (e.g., reconstruction loss, perceptual loss, and adversarial loss) is used to determine all differences between the generated de-occluded face image and ground truth. Furthermore, we build occluded face images and corresponding occlusion-free face images dataset. We trained our model on this new dataset and later tested it on real-world face images. The experiment results (qualitative and quantitative) and the comparative study confirm the robustness and effectiveness of the proposed work in removing challenging occlusion masks with various structures, sizes, shapes, types, and positions.

Techniques for Background Updating under PTZ Camera Based Surveillance

  • Jung, Sung-Hoon;Kim, Min-Hwan
    • Journal of Korea Multimedia Society
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    • v.12 no.12
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    • pp.1745-1754
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    • 2009
  • PTZ (Pan-Tilt-Zoom) camera based surveillance systems are enlarging their field of application due to their wide observable area. We aimed to detect both static and moving objects in automated working space by using a PTZ camera. For object detection we used background difference method because of the high quality segmentation. However, the method has a problem called 'hole' that is caused by non-continuous surveillance of the PTZ camera and its own characteristics. Moreover, the occlusion which occurs when the moving object overlaps with the static object should be solved for robust object detection. In this paper, we suggest a region-based technique for updating background images thereby overcoming the hole and occlusion problem. Through experiments with real scenes, it was verified that meaningful static and/or moving objects were detected very well.

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Active Fusion Model with Robustness against Partial Occlusions (부분적 폐색에 강건한 활동적 퓨전 모델)

  • Lee Joong-Jae;Lee Geun-Soo;Kim Gye-Young
    • The KIPS Transactions:PartB
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    • v.13B no.1 s.104
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    • pp.35-46
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    • 2006
  • The dynamic change of background and moving objects is an important factor which causes the problem of occlusion in tracking moving objects. The tracking accuracy is also remarkably decreased in the presence of occlusion. We therefore propose an active fusion model which is robust against partial occlusions that are occurred by background and other objects. The active fusion model is consisted of contour-based md region-based snake. The former is a conventional snake model using contour features of a moving object and the latter is a regional snake model which considers region features inside its boundary. First, this model classifies total occlusion into contour and region occlusion. And then it adjusts the confidence of each model based on calculating the location and amount of occlusion, so it can overcome the problem of occlusion. Experimental results show that the proposed method can successfully track a moving object but the previous methods fail to track it under partial occlusion.

True Orthoimage Generation Using Multiple Aerial Images (다중 항공영상을 이용한 엄밀정사영상 생성)

  • Yoo, Eun-Jin;Lee, Dong-Cheon
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.225-226
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    • 2010
  • The problem in orthoimage generation is to recover occlusion areas. In this study, occlusion areas - double mapping regions of the building roofs - were mutually corrected by using multiple images. The proposed method could be efficient for generating true orthoimages in urban areas.

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Principles and considerations of orthodontics for Prosthodontic treatment (심미보철치료를 위한 교정치료의 원칙과 고려사항)

  • Chang, Won-Gun
    • The Journal of the Korean dental association
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    • v.56 no.9
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    • pp.503-511
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    • 2018
  • Outcome of esthetic ceramic restorations are affected by tooth size, gingival contour, occlusal relationship, etc. For this reason, demand of orthodontic treatment before esthetic ceramic restoration is increasing. If a Bolton ratio discrepancy, a problem of the maxillary incisor's vertical position, a problem of inclination of anterior teeth, a pathogenic occlusion is existed, a pre-prosthodontic orthodontics should be accomplished. These problems can be satisfactory only after the prosthetic treatment is performed after orthodontic treatment. When orthodontic treatment is given, it should be treated with the following principle. 1. Treat it in the direction of functioning occlusion. 2. Keep the patient's stable occlusal scheme. 3. Treat the teeth by considering the average tooth size and Bolton ratio. Ortho-Prostho combined treatment with optimal treatment plan can lead a patient's function, esthetics, and long-term stability.

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Application Research on Obstruction Area Detection of Building Wall using R-CNN Technique (R-CNN 기법을 이용한 건물 벽 폐색영역 추출 적용 연구)

  • Kim, Hye Jin;Lee, Jeong Min;Bae, Kyoung Ho;Eo, Yang Dam
    • Journal of Cadastre & Land InformatiX
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    • v.48 no.2
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    • pp.213-225
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    • 2018
  • For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

Comparative study of data augmentation methods for fake audio detection (음성위조 탐지에 있어서 데이터 증강 기법의 성능에 관한 비교 연구)

  • KwanYeol Park;Il-Youp Kwak
    • The Korean Journal of Applied Statistics
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    • v.36 no.2
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    • pp.101-114
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    • 2023
  • The data augmentation technique is effectively used to solve the problem of overfitting the model by allowing the training dataset to be viewed from various perspectives. In addition to image augmentation techniques such as rotation, cropping, horizontal flip, and vertical flip, occlusion-based data augmentation methods such as Cutmix and Cutout have been proposed. For models based on speech data, it is possible to use an occlusion-based data-based augmentation technique after converting a 1D speech signal into a 2D spectrogram. In particular, SpecAugment is an occlusion-based augmentation technique for speech spectrograms. In this study, we intend to compare and study data augmentation techniques that can be used in the problem of false-voice detection. Using data from the ASVspoof2017 and ASVspoof2019 competitions held to detect fake audio, a dataset applied with Cutout, Cutmix, and SpecAugment, an occlusion-based data augmentation method, was trained through an LCNN model. All three augmentation techniques, Cutout, Cutmix, and SpecAugment, generally improved the performance of the model. In ASVspoof2017, Cutmix, in ASVspoof2019 LA, Mixup, and in ASVspoof2019 PA, SpecAugment showed the best performance. In addition, increasing the number of masks for SpecAugment helps to improve performance. In conclusion, it is understood that the appropriate augmentation technique differs depending on the situation and data.