• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.277-284
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• 2011

In tangible augmented reality (AR) environments for virtual prototyping, the user interacts with virtual products by manipulating tangible objects with his or her hands, but the user often encounter awkward situations in which his or her hands are occluded by augmented virtual objects, which reduces both immersion and ease of interaction. In this paper, we present how to resolve such hand region occlusion in order to enhance natural interaction and immersive visualization. In the AR environment considered, we use two types (product-type and pointer-type) of tangible objects for tangible user interaction with a virtual product of interest. Holding the tangible objects with his or her hands, the user can create input events by touching specified regions of the product-type tangible object with the pointer-type tangible object. We developed a method for resolving hand region occlusion frequently arising during such user interaction, It first detect hand region in a real image and refines the rendered image of the virtual object by subtracting the hand region from the rendered image, Then, it superimposes the refined image onto the real image to obtain an image in which the occlusion is resolved. Incorporated into tangible AR interaction for virtual prototyping of handheld products such as cellular phones and MP3 players, the method has been found by a preliminary user study that it is not only useful to improve natural interaction and immersive visualization of virtual products, but also helpful for making the users experience the products' shapes and functions better.

• Journal of Periodontal and Implant Science
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• v.46 no.6
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• pp.396-404
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• 2016

Purpose: The aim of this retrospective study was to determine the association between dental implants in the posterior region and traumatic occlusion in the adjacent premolars, using data collected during from 2002 to 2015. Methods: Traumatic occlusion in the adjacent premolars was assessed by examining clinical parameters (bleeding on probing, probing pocket depth, fremitus, and tooth mobility) and radiographic parameters (loss of supporting bone and widening of the periodontal ligament space) over a mean follow-up of 5 years. Clinical factors (gender, age, implant type, maxillary or mandibular position, opposing teeth, and duration of functional loading) were evaluated statistically in order to characterize the relationship between implants in the posterior region and traumatic occlusion in the adjacent premolars. Results: The study inclusion criteria were met by 283 patients, who had received 347 implants in the posterior region. The incidence of traumatic occlusion in the adjacent premolars was significantly higher for splinted implants (P=0.004), implants in the maxillary region (P<0.001), and when implants were present in the opposing teeth (P<0.001). The other clinical factors of gender, age, and duration of functional loading were not significantly associated with traumatic occlusion. Conclusions: This study found that the risk of traumatic occlusion in the adjacent premolars increased when splinted implants were placed in the maxillary molar region and when the teeth opposing an implant also contained implants.

• 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.

• 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.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.573-583
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• 2011

In this paper, we propose an occlusion compensation algorithm which is used for virtual view generation. In general, since occlusion region is recovered from neighboring pixels by taking the mean value or median value of neighbor pixels, the visual characteristics of a given image are not considered and consequently the accuracy of the compensated occlusion regions is not guaranteed. To solve these problem, we propose an algorithm that considers primary visual characteristics of a given image to compensate the occluded regions by using seam carving algorithm. In the proposed algorithm, we first use Sobel mask to obtain the edge map of a given image and then make it binary digit 0 or 1 and finally thinning process follows. Then, the energy patterns of original and thinned edge map obtained by the modified seam carving method are used to compensate the occlusion regions. Through experiments with many test images, we verify that the proposed algorithm performed better than conventional algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.228-230
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• 2016

In this paper, we introduce new FRUC method for Multi-View Video based on DIBR (Depth Image based Rendering, DIBR). In the proposed method, we divide each block to sub-regions using depth map. Then, we reconstruct occlusion region information at each sub-regions by using other views. With reconstructed occlusion region information, we estimate and compensate each sub-regions' motion. The proposed method estimates more accurate motion compared to the conventional methods in occlusion region.

• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.390-396
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• 2015

We propose a partial occlusion removal method for computational integral imaging reconstruction (CIIR) based on the usage of the exemplar based inpainting technique. The proposed method is an improved version of the original linear inpainting based CIIR (LI-CIIR), which uses the inpainting technique to fill in the data missing region. The LI-CIIR shows good results for images which contain objects with smooth surfaces. However, if the object has a textured surface, the result of the LI-CIIR deteriorates, since the linear inpainting cannot recover the textured data in the data missing region well. In this work, we utilize the exemplar based inpainting to fill in the textured data in the data missing region. We call the proposed method the neighboring elemental image exemplar based inpainting (NEI-exemplar inpainting) method, since it uses sources from neighboring elemental images to fill in the data missing region. Furthermore, we also propose an automatic occluding region extraction method based on the use of the mutual constraint using depth estimation (MC-DE) and the level set based bimodal segmentation. Experimental results show the validity of the proposed system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.99-105
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• 2017

Generally, stereo matching methods are used to estimate depth information based on color and spatial similarity. However, most depth estimation methods suffer from the occlusion region because occlusion regions cause inaccurate depth information. Moreover, they do not consider the temporal dimension when estimating the disparity. In this paper, we propose a temporal stereo matching method, considering occlusion and disregarding inaccurate temporal depth information. First, we apply a global stereo matching algorithm to estimate the depth information, we segment the image to occlusion and non-occlusion regions. After occlusion detection, we fill the occluded region with a reasonable disparity value that are obtained from neighboring pixels of the current pixel. Then, we apply a temporal disparity estimation method using the reliable information. Experimental results show that our method detects more accurate occlusion regions, compared to a conventional method. The proposed method increases the temporal consistency of estimated disparity maps and outperforms per-frame methods in noisy images.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.684-695
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• 1987

In this paper, an improved matching method using subtemplate of moving region and 3-step search algorithm is proposed. It reduces heavy computational load of the conventional method and also can continuously track the target even with occlusion. The proposed method is applied to an automatic target tracker using high speed 16bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has better performance over the conventional method in spite of greately reducing the computational load, even in case with complex background and/or with occlusion.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.1-8
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• 2015

In recent years, ear has emerged as a new biometric trait, because it has advantage of higher user acceptance than fingerprint and can be captured at remote distance in an indoor or outdoor environment. This paper proposes an individual identification method using ear region based on SIFT(shift invariant feature transform). Unlike most of the previous studies using rectangle shape for extracting a region of interest(ROI), this study sets an ROI as a flexible expanded region including ear. It also presents an effective extraction and matching method for SIFT keypoints. Experiments for evaluating the performance of the proposed method were performed on IITD public database. It showed correct identification rate of 98.89%, and it showed 98.44% with a deformed dataset of 20% occlusion. These results show that the proposed method is effective in ear recognition and robust to occlusion.