• Journal of Information Processing Systems
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• 제14권6호
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.375-378
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• 1997

This research deals with a problem of reconstructing 3D surface structures from their 2D projections, which is an important research topic in computer vision. In order to provide robust reconstruction algorithm, that is reliable even in the presence of uncertainty in the range images, we first present a detailed model and analysis of several error sources and their effects on measuring three-dimensional surface properties using the space encoded range imaging technique. Our approach has two key elements. The first is the error modeling for the space encoding range sensor and its propagation to the 3D surface reconstruction problem. The second key element in our approach is the algorithm for removing outliers in the range image. Such analyses, to our knowledge, have never attempted before. Experimental results show that our approach is significantly reliable.

• 지구물리와물리탐사
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• 제16권1호
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• pp.27-35
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• 2013

본 연구를 통하여 3차원 자력역산 소프트웨어 시작품(KMag3D, 가칭)을 개발하고 개발 시 역점사항을 사용자 매뉴얼 형식으로 소개하였다. KMag3D는 다음 두 가지 사항을 기본 뼈대로 구성되었다. 첫째, 지금까지 자력역산에 일반적으로 적용되는 최소제곱법에 의한 방법 대신 대수적 재구성법에 기반한 알고리즘을 도입하였다. 이는 계산시간과 기억용량을 획기적으로 줄여 3차원 자력역산을 매우 효율적으로 수행한다. 둘째, 대수적 재구성법에 의한 3차원 역산에 필요한 초기모형과 사전정보 모형을 결정하는 데 2차원 수치모델링 및 역산 집합과 주향방향 내삽을 이용하는 방법을 제시하였다. 이는 3차원 역산 알고리즘에 사전정보를 효율적으로 적용하며 특히 매우 실용적임을 보여주었다.

• 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.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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• pp.177-178
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• 2006

Digital holographic particle tracking velocimetry (HPTV) is developed by single high-speed camera and single continuous laser with long coherent length. This system can directly capture 4000 hologram fringe images for 1 second through a camera computer memory. The 3D particle location is made of the reconstruction by using a computer hologram algorithm. This system can successfully be applied to instantaneous 3D velocity measurement in the water flow inside a micro-tube. The average of 100 instantaneous velocity vectors is obtained by reconstruction and tracking with the time of evolution of recorded fringes images. In the near future, we will apply this technique to measure 3D flow information inside various micro structures.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 춘계학술대회
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• pp.155-157
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• 2012

본 논문에서는 집적 영상 기술에 기반한 컴퓨터 3D 영상 복원을 이용하여 비선형 3D 영상 상관기를 제안한다. 제안하는 방법에서는 먼저 기준 3D 물체와 목표 3D 물체의 요소 영상들을 렌즈 어레이를 통해 픽업한다. 이 픽업된 영상에 컴퓨터 집적 영상 복원 방법을 사용하여 목표 평면 영상과 기준 평면 영상들이 복원된다. 복원된 기준 평면 영상과 목표 평면 영상들 간의 비선형 상호상관을 통해 인식을 수행한다. 제안된 방법의 유용함을 보이기 위해 기존의 방법과 비교하여 기초적인 상관관계 실험을 수행하고 그 결과를 발표한다.

• 대한의용생체공학회:의공학회지
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• 제30권1호
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• pp.56-65
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• 2009

Compton imaging is often recognized as a potentially more valuable 3-D technique in nuclear medicine than conventional emission tomography. Due to inherent computational limitations, however, it has been of a difficult problem to reconstruct images with good accuracy. In this work we show that the row-action maximum likelihood algorithm (RAMLA), which have proven useful for conventional tomographic reconstruction, can also be applied to the problem of 3-D reconstruction of cone-beam projections from Compton scattered data. The major advantage of RAMLA is that it converges to a true maximum likelihood solution at an order of magnitude faster than the standard expectation maximiation (EM) algorithm. For our simulations, we first model a Compton camera system consisting of the three pairs of scatterer and absorber detectors placed at x-, y- and z-axes, and generate conical projection data using a software phantom. We then compare the quantitative performance of RAMLA and EM reconstructions in terms of the percentage error. The net conclusion based on our experimental results is that the RAMLA applied to Compton camera reconstruction significantly outperforms the EM algorithm in convergence rate; while computational costs of one iteration of RAMLA and EM are about the same, one iteration of RAMLA performs as well as 128 iterations of EM.

• 한국자동차공학회논문집
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• 제16권1호
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• pp.52-63
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• 2008

The side collision reconstruction algorithm is developed using three dimensional car crash analysis. Medium size passenger car is modeled for finite element analysis. Total 24 side collision configurations, four different speed and six different angle, are set up for making side collision database. Deformation index and degree index are built up for each collision case. Deformation index is a kind of deformation estimate averaging displacement of side door of crashed car from finite element analysis result. Angle index is constructed measuring deformed angle of crashing car. There are two kinds of angle index, one is measured at driver's side and the other is measured at passenger's side. Also a collision analysis information in side of cars is used for giving a basis for scientific and practical reason in a reconstruction of the car accident. The analysis program, LS-DYNA3D is utilized for finite element analysis program for a collision analysis. Those database are used for side collision reconstruction. Side collision reconstruction algorithm is developed, and applied to find the collision conditions before the accident occurs. Three example collision cases are tried to check the effectiveness of the algorithm. Deformation index and angle index is extracted for the case from the analysis result. Deformation index is compared to the established database, and estimated collision speed and angle are introduced by interpolation function. Angle index is used to select a specific collision condition from the several available conditions. The collision condition found by reconstruction algorithm shows good match with original condition within 10% error for speed and angle. As a result, the calculation from the reconstruction of the situation is reproducing the situation well. The performance in this study can be used in many ways for practical field using deformation index and degree index. Other different collision situations may be set up for extending the scope of this study in the future.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.451-452
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• 2006

In this paper, we present a 3D reconstruction method using multi-camera. This method is very compact algorithm so that can be implemented easily on small hardware architecture. By using multi-camera, it gives exacter result than existing method and we propose accurate index for each matching nodes to use multi-camera.