• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2042-2059
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• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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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.

• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.519-524
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• 2009

This paper describes a new sensor system for 3D environment perception using stereo structured infrared light sources and a camera. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and two projected infrared light sources are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Two successive captures of the image with left and right infrared light projection provide several benefits, which include wider area of depth measurement, higher spatial resolution and the visibility perception.

• 정보처리학회논문지B
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• 제18B권1호
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• pp.21-28
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• 2011

얼굴의 3차원 정보는 얼굴 인식이나 얼굴 합성, Human Computer Interaction (HCI) 등 다양한 분야에서 유용하게 이용될 수 있다. 그러나 일반적으로 3차원 정보는 3D 스캐너와 같은 고가의 장비를 이용하여 획득되기 때문에 얼굴의 3차원 정보를 얻기 위해서는 많은 비용이 요구된다. 본 논문에서는 일반적으로 손쉽게 얻을 수 있는 2차원의 얼굴 영상 시퀀스로부터 효과적으로 3차월 얼굴 형태를 추적하고 재구성하기 위한 3차원 Active Appearance Model (3D-AAM) 방법을 제안한다. 얼굴의 3차원 변화 정보를 추정하기 위해 학습 영상은 정면 얼굴 포즈로 다양한 얼굴 표정 변화를 포함한 영상과 표정 변화를 갖지 않으면서 서로 크게 다른 얼굴 포즈를 갖는 영상으로 구성한다. 입력 영상의 3차원 얼굴 변화를 추정하기 위해 먼저 서로 다른 포즈를 갖는 학습 영상으로부터 얼굴의 각 특징점(Land-mark)의 기하학적 변화를 이용하여 깊이 정보를 추정하고 추정된 특징점의 깊이 정보를 입력 영상의 2차원 얼굴 변화에 추가하여 최종적으로 입력 얼굴의 3차원 변화를 추정한다. 본 논문에서 제안된 방법은 얼굴의 다양한 표정 변화와 함께 3차원의 얼굴 포즈 변화를 포함한 실험 영상을 이용하여 기존의 AAM에 비해 효과적이면서 빠르게 입력 얼굴을 추적(Fitting)할 수 있으며 입력 영상의 정확한 3차원 얼굴 형태를 생성할 수 있음을 보였다.

• 방송공학회논문지
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• 제25권7호
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• pp.1095-1106
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• 2020

In this paper, we propose an algorithm that extracts a high-precision 3D skeleton using a model generated using a distributed RGB-D camera. When information about a 3D model is extracted through a distributed RGB-D camera, if the information of the 3D model is used, a skeleton with higher precision can be obtained. In this paper, in order to improve the precision of the 2D skeleton, we find the conditions to obtain the 2D skeleton well using the PCA. Through this, high-quality 2D skeletons are obtained, and high-precision 3D skeletons are extracted by combining the information of the 2D skeletons. Even though this process goes through, the generated skeleton may have errors, so we propose an algorithm that removes these errors by using the information of the 3D model. We were able to extract very high accuracy skeletons using the proposed method.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.193-198
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• 2017

In this study, we propose a three-dimensional (3D) visualization technique of occluded objects using integral imaging with a plenoptic camera. In previous studies, depth map estimation from elemental images was used to remove occlusion. However, the resolution of these depth maps is low. Thus, the occlusion removal accuracy is not efficient. Therefore, we use a plenoptic camera to obtain a high-resolution depth map. Hence, individual depth map for each elemental image can also be generated. Finally, we can regenerate a more accurate depth map for 3D objects with these separate depth maps, allowing us to remove the occlusion layers more efficiently. We perform optical experiments to prove our proposed technique. Moreover, we use MSE and PSNR as a performance metric to evaluate the quality of the reconstructed image. In conclusion, we enhance the visual quality of the reconstructed image after removing the occlusion layers using the plenoptic camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• 한국통신학회논문지
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• 제36권9C호
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• pp.555-563
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• 2011

본 논문에서는 움직임 추정 (motion estimation, ME), 컬러 라벨링(labeling) 그리고 Non-local mean 필터를 이용하여 2D 영상을 3D 업체 영상으로 변환하는 기법을 제안한다. 제안하는 기법에서는 먼저 프레임 간의 움직임을 추정하여 객체의 움직임 벡터를 추출하고 주어진 영상에 대해 컬러 라벨링 작업을 수행하여 영상을 분리한다. 움직임 추정 결과와 컬러 라벨링 결과를 비교 분석하여 영상내의 객체를 추출하고 추출된 객체를 이동하여 우 영상을 생성하게 되는데 이때 우 영상을 생성하는 과정에서 채워지지 않은 가려짐 영역이 발생하며 전체 화소간의 상관도를 고려하는 Non-local mean 필터를 사용하여 보상한다. 이후 원본 영상인 좌 영상과 생성된 우 영상으로 비윌 주사하여 최종 3D 업체 영상을 재현한다. 실험 결과를 통해 제안된 기법으로 생성된 3D 업체 영상에서 객체위주의 안정된 업체 변환이 수행되는 것을 확인할 수 있었다.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2002년도 추계학술대회 논문집
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• pp.267-272
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• 2002

Pitting corrosion is a very common occurrence in marine structures. Therefore, the 3-D finite element analysis is carried out to determine the stress intensity factors at the pit depth and also at the surface of the pit. The pits are modeled as a part of sphere, based on the pit depth and the pit diameter as specified by the Ship Structural Committee. The pit depth and pit diameter are function of the percentage of pitting that the plate is subjected to. A dog-bone shaped specimen is subjected to different intensities of pitting and the stress intensity factors are determined under axial tensile loads.

• 방송공학회논문지
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• 제24권5호
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• pp.765-774
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• 2019

본 논문에서는 다중 RGB-D 카메라의 포인트 클라우드 정합 알고리즘을 제안한다. 일반적으로 컴퓨터 비전 분야에서는 카메라의 위치를 정밀하게 추정하는 문제에 많은 관심을 두고 있다. 기존의 3D 모델 생성 방식들은 많은 카메라 대수나 고가의 3D Camera를 필요로 한다. 또한 2차원 이미지를 통해 카메라 외부 파라미터를 얻는 기존의 방식은 큰 오차를 가지고 있다. 본 논문에서는 저가의 RGB-D 카메라 8대를 사용하여 전방위 3차원 모델을 생성하기 위해 깊이 이미지와 함수 최적화 방식을 이용하여 유효한 범위 내의 오차를 갖는 좌표 변환 파라미터를 구하는 방식을 제안한다.