• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.41-47
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• 2021

Detection of protein-protein interactions (PPIs) remains essential for the development of therapies against diseases. Experimental studies to detect PPI are longer and more expensive. Today, with the availability of PPI data, several computer models for predicting PPIs have been proposed. One of the big challenges in this task is feature extraction. The relevance of the information extracted by some extraction techniques remains limited. In this work, we first propose an extraction method based on correlation relationships between the physicochemical properties of amino acids. The proposed method uses a correlation matrix obtained from the hydrophobicity and hydrophilicity properties that it then integrates in the calculation of the bigram. Then, we use the SVM algorithm to detect the presence of an interaction between 2 given proteins. Experimental results show that the proposed method obtains better performances compared to the approaches in the literature. It obtains performances of 94.75% in accuracy, 95.12% in precision and 96% in sensitivity on human HPRD protein data.

• 한국지리정보학회지
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• 제20권1호
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• pp.152-161
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• 2017

모바일 매핑 시스템(Mobile Mapping System: MMS) 센서를 이용한 3차원 정밀지도의 구축은 자율주행 자동차 개발에 필요한 기술이다. 본 논문은 MMS LiDAR(Light Detection And Ranging) 센서를 이용하여 획득한 점군자료를 이용하여 도로주변의 3차원 객체 추출에 관한 연구를 수행하였다. 우선, MMS LiDAR 점군자료 이용하여 수치표면모형(DSM: Digital Surface Model)을 제작하고, 생성된 DSM을 기반으로 경사도 지도를 제작하였다. 추출된 경사도 정보를 이용하여 도로주변의 3차원 객체를 식별하였고, 모폴로지 필터링 기법을 이용하여 도로주변의 3차원 객체 중 총 97%의 객체를 추출하였다. 본 연구는 MMS 센서를 이용하여 획득한 공간정보자료를 기반으로 도로 주변의 3차원 객체를 추출함으로써 최근 주목받고 있는 자율주행기술의 활용성에 관한 방안을 제시하였다는데 의의가 있다.

• 한국군사과학기술학회지
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• 제5권2호
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• pp.50-61
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• 2002

In this study, 3-dimensional virtual visualization was performed for a rapid and accurate analysis of sea bottom topography, The visualization was done through the extracted data using the developed program and the generated data using the gridding method. The data extraction program was developed with AutoLISP programming language and this program was able to extract the needed sample bathymetry data from the electronic sea chart systematically as well as effectively. The gridded bathymetry data were generated by the interpolation or extrapolation method from the spatially-irregular sample data. As the result of realization for the 3-dimensional virtual visualization, it was shown a proper feasibility in the analysis of the sea bottom topography to determine the route of submarine cable burial.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.645-646
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• 2008

Silhouette extraction is widely used in many computer graphics applications. In this paper, we proposed a method for extracting 3D silhouette and internal pattern from 3D vector data. To do this, we first make an edge-list, secondly define the silhouette, and finally remove hidden lines. After getting the silhouette, we extract internal pattern using adjacent edge's dihedral. The proposed method not only effectively improves the performance of extracting 3D silhouette and internal pattern from 3D vector data but also reduces the computational complexity.

• 한국컴퓨터정보학회논문지
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• 제21권12호
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• pp.43-49
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• 2016

This paper presents the design and implementation of virtual aquarium by generating 3D models of fishes that are colored by viewers in an aim to create interaction among viewers and aquarium. The virtual aquarium system is composed of multiple texture extraction modules, a single interface module and a single display module. The texture extraction module recognize the QR code on the canvas to get information of the predefined mapping table and then extract the texture data for the corresponding 3D model. The scanned image is segmented and warp transformed onto the texture image by using the mapping information. The extracted texture is transferred to the interface module to save on the server computer and the interface module sends the fish code and texture information to the display module. The display module generates a fish on the virtual aquarium by using predefined 3D model with the transmitted texture. The fishes on the virtual aquarium have three different swimming methods: self-swimming, autonomous swimming, and leader-following swimming. The three different swimming methods are discussed in this paper. The future study will be the implementation of virtual aquarium based on storytelling to further increase interactions with the viewer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권4호
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• pp.263-269
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• 2012

The ability to characterize feature objects from radar readings is often limited by simply looking at their still frame reflectivity, differential reflectivity and differential phase data. In many cases, time-series study of these objects' reflectivity profile is required to properly characterize features objects of interest. This paper introduces a novel technique to automatically track multiple 3D radar structures in C,S-band in real-time using Doppler radar and profile their characteristic reflectivity distribution in time series. The extraction of reflectivity profile from different radar cluster structures is done in three stages: 1. static frame (zone-linkage) clustering, 2. dynamic frame (evolution-linkage) clustering and 3. characterization of clusters through time series profile of reflectivity distribution. The two clustering schemes proposed here are applied on composite multi-layers CAPPI (Constant Altitude Plan Position Indicator) radar data which covers altitude range of 0.25 to 10 km and an area spanning over hundreds of thousands $km^2$. Discrete numerical simulations show the validity of the proposed technique and that fast and accurate profiling of time series reflectivity distribution for deformable 3D radar structures is achievable.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권10호
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• pp.836-850
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• 2009

포즈인식은 최근에 유비쿼터스 환경, 행위 예술, 로봇 제어 등에서 그 필요성이 증가되고 있는 분야로써, 컴퓨터비전, 패턴인식 등에서 활발히 연구되고 있다. 하지만 기존의 포즈인식 연구들은 사람의 회전이나 이동에 따라서 불안정한 인식률을 보인다는 단점을 갖고 있다. 이는 포즈 인식을 위해 추출한 특징이 사람의 회전, 이동 등의 다양한 변수에 영향을 크게 받기 때문이다. 이를 극복하기 위하여 본 논문에서는, 다 시점(multi-view) 환경에서의 3D Star Skeleton과 주성분 분석(principal component analysis: PCA)에 기반한 사람의 회전에 강건한 특징 추출을 제안한다. 제안된 시스템은 포즈의 특징 추출을 위해 다 시점 환경 기반의 visual hull을 생성하는 과정에서 획득 가능한 깊이 정보를 표현하는 8개의 projection map을 입력데이터로 사용한다. 이를 통해 포즈의 3D 정보를 반영하는 3D Star Skeleton을 구성하고 주성분 분석 기반의 회전에 강건한 특징을 추출한다. 실험결과에서는 다양하게 회전된 사람으로부터 생성된 3D Star Skeleton에서 특징을 추출하고 다양한 인식기를 통해 포즈인식을 해보았으며, 제안된 특징 추출 방법이 사람의 회전에 강건함을 알 수 있었다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1998년도 학술대회
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• pp.3-8
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• 1998

The conversion of monoscopic video to 3D stereoscopic video has been studied by some pioneering researchers. In spite of the commercial of potential of the technology, two problems have bothered the progress of this research area: vertical motion parallax and high computational complexity. The former causes the low 3D perception, while the hardware complexity is required by the latter. The previous research has dealt with NTSC video, thur requiring complex processing steps, one of which is motion estimation. This paper proposes 3D stereoscopic conversion method of MPGE encoded data. Our proposed method has the advantage that motion estimation can be avoided by processing MPEG compressed data for the extraction of motion data as well as that camera and object motion in random in random directions can be handled.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.