• 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 the korean academy of Pediatric Dentistry
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• v.23 no.2
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• pp.537-548
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• 1996

To investigate the relationship between the calcification stages of mandibular canines and the skeletal maturity stage of the hand-wrist in subjects with normal occlusion and Class III malocclusion, hand-wrist radiographs and panoramic radiographs were taken from subjects of normal occlusions(94 males, 88 females) and Class III malocclusions(75 males, 76 females) who had no systemic diseases and no history of orthodontic or prosthodontic treatment. Fishman's method for the skeletal maturity stages of the hand-wrist and Demirijian's method for the calcification stages of mandibular canines were used and analyzed. The results were as follows : 1. In subjects with normal occlusion and Class III malocclusion, skeletal maturity of the hand-wrist and calcification of mandibular canines at various ages occured earlier in females than in males(p<0.05). 2. Comparing the skeletal maturity stages of the hand-wrist and the calcification stages of mandibular canines between subjects with normal occlusion and Class III malocclusion, there were no significant differences between the groups. 3. The correlation coefficient between the calcification stages of mandibular canines and the skeletal maturity stages of the hand-wrist. in subjects with normal occlusion and Class III malocclusion showed a high association(p<0.01). 4. In stage 4 of the skeletal maturity of the hand-wrist, the frequency distribution of calcification G stage among the various calcification stages was highest both in normal occlusion and in subjects with Class III malocclusion. However, there was no significant difference in the frequency distribution of calcification stages between the groups.

• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.111-118
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• 2014

In tangible augmented reality (AR) environments, the user interacts with virtual objects by manipulating their physical counterparts, but he or she often encounters awkward situations in which his or her hands are occluded by the augmented virtual objects, which causes great difficulty in figuring out hand positions, and reduces both immersion and ease of interaction. To solve the problem of such hand occlusion, skin color information has been usefully exploited. In this paper, we propose an approach to simple and effective construction of a skin color map which is suitable for hand segmentation and tangible AR interaction. The basic idea used herein is to obtain hand images used in a target AR environment by simple image subtraction and to represent their color information by a convex polygonal map in the YCbCr color space. We experimentally found that the convex polygonal map is more accurate in representing skin color than a conventional rectangular map. After implementing a solution for resolving hand occlusion using the proposed skin color map construction, we showed its usefulness by applying it to virtual design evaluation of digital handheld products in a tangible AR environment.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.11-18
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• 2018

To interact with a virtual object in immersive virtual environment, the target object should be selected quickly and accurately. Conventional 3D ray casting method using a direction of user's hand or head allows the user to select an object quickly. However, accuracy problem occurs when selecting an object using conventional methods among occlusion of objects. In this paper, we propose a region of interest based selection method that enables to select an object among occlusion of objects using a combination of gaze tracking and hand gesture recognition. When a user looks at a group of occlusion of objects, the proposed method recognizes user's gaze input, and then region of interest is set by gaze input. If the user wants to select an object among them, the user gives an activation hand gesture. Then, the proposed system relocates and visualizes all objects on a virtual active window. The user can select an object by a selecting hand gesture. Our experiment verified that the user can select an object correctly and accurately.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.131-136
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• 1997

We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.39-49
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• 2006

This paper proposes a hand-posture recognition method using reinforcement learning for the performance improvement of vision-based hand-posture recognition. The difficulties in vision-based hand-posture recognition lie in viewing direction dependency and self-occlusion problem due to the high degree-of-freedom of human hand. General approaches to deal with these problems include multiple camera approach and methods of limiting the relative angle between cameras and the user's hand. In the case of using multiple cameras, however, fusion techniques to induce the final decision should be considered. Limiting the angle of user's hand restricts the user's freedom. The proposed method combines angular features and appearance features to describe hand-postures by a two-layered data structure and reinforcement learning. The validity of the proposed method is evaluated by appling it to the hand-posture recognition system using three cameras.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3924-3940
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• 2020

Dynamic hand gesture recognition(d-HGR) plays an important role in human-computer interaction(HCI) system. With the growth of hand-pose estimation as well as 3D depth sensors, depth, and the hand-skeleton dataset is proposed to bring much research in depth and 3D hand skeleton approaches. However, it is still a challenging problem due to the low resolution, higher complexity, and self-occlusion. In this paper, we propose a hand-shape feature extraction(HSFE) network to produce robust hand-shapes. We build a hand-shape model, and hand-skeleton based on LSTM to exploit the temporal information from hand-shape and motion changes. Fusion between two models brings the best accuracy in dynamic hand gesture (DHG) dataset.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1040-1047
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• 2012

In this paper, we propose a ball tracking algorithm robust against occlusion in broadcasting soccer video sequences. Soccer ball tracking is a challenging task due to occlusion, fast motion and fast direction changes. Many works have been proposed based on ball trajectory. However, this approach requires heavy computational complexity. We propose a ball tracking algorithm with occlusion handling capability. Initial ball location is calculated using the circular hough transform. Then, the ball is tracked using template matching. Occlusion is handled by matching score. In occlusion cases, we generate a set of ball candidates. The ball candidates which exist in the previous frame were removed. On the other hand, the new appearing candidate is determined as the ball. Experiments with several broadcasting soccer video sequences show that the proposed method efficiently handles the occlusion cases.

• The korean journal of orthodontics
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• v.20 no.1
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• pp.111-122
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• 1990

To investigate the relationship of skeletal maturity among the normal occlusion group and each malocclusion groups, the author used hand and wrist X-ray of 133 Korean 13 year old boys (normal occlusion 30, Class I malocclusion 35, Class II malocclusion 35 and Class III malocclusion 33) and assessed their skeletal maturity. In this study, fourteen skeletal maturity stages were selected from; Radius, Hamate, Pisiform, Ulnar sesamoid of the metacarpophalangeal joint of the first thumb, proximal phalanges of the first, second and third finger, middle and distal phalanx of the third finger. The difference of skeletal maturity of each malocclusion groups in relative to normal occlusion group and that of each malocclusion groups were analyzed. The findings of this study can be summerized as follows: 1. Average skeletal maturity stage of each groups were MP3cap stage in normal occlusion group, H-2 stage in Class I malocclusion group, midstage between S and H-2 stage in Class II malocclusion group, MP3cap stage in Class III malocclusion group. 2. There was no significant difference in skeletal maturity of Class I malocclusion and Class III malocclusion groups in relative to normal occlusion group. 3. There was significant retardation of skeletal maturity in Class II malocclusion group in relative to normal occlusion group. 4. There was no significant difference in skeletal maturity between Class I and Class II malocclusion groups. 5. There was no significant difference in skeletal maturity between Class I and Class III malocclusion groups. 6. There was significant retardation of skeletal maturity in Class II malocclusion group in relative to Class III malocclusion group.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.553-556
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• 2005

We present a vision-based hand gesture recognition system for object manipulation in virtual space. Most conventional hand gesture recognition systems utilize a simpler method for hand detection such as background subtractions with assumed static observation conditions and those methods are not robust against camera motions, illumination changes, and so on. Therefore, we propose a statistical method to recognize and detect hand regions in images using geometrical structures. Also, Our hand tracking system employs multiple cameras to reduce occlusion problems and non-synchronous multiple observations enhance system scalability. Experimental results show the effectiveness of our method.