• Title/Summary/Keyword: Detect3D

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Boundary Line Extract for Moving Object Tracking (이동 물체 추적을 위한 경계선 추출)

  • Kim, Tea-Sik;Lee, Ju-Shin
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.2
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    • pp.28-34
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    • 1998
  • In this paper, I'd like to make a suggestion for boundary line detect algorithm which is used 3-D image processing system in order to track moving object. Through this study, more than anything else, difference image method was adopted to detect moving object in input image. To detect moving object, I made use of detect windows constructed by 4's predictive areas and object area for the purpose of reducing processing time and its size was determined by the size of moving object and prediction parameter directed center position. And also, tracking camera was movable toward the direction of X, Y by DC motor. As a conclusion of the study proposed algorithm, I found out the following results that tracking error was less than 6% of total moving object size and maximum tracking time 2 seconds by toy-car simulation.

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Robust 3D Facial Landmark Detection Using Angular Partitioned Spin Images (각 분할 스핀 영상을 사용한 3차원 얼굴 특징점 검출 방법)

  • Kim, Dong-Hyun;Choi, Kang-Sun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.199-207
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    • 2013
  • Spin images representing efficiently surface features of 3D mesh models have been used to detect facial landmark points. However, at a certain point, different normal direction can lead to quite different spin images. Moreover, since 3D points are projected to the 2D (${\alpha}-{\beta}$) space during spin image generation, surface features cannot be described clearly. In this paper, we present a method to detect 3D facial landmark using improved spin images by partitioning the search area with respect to angle. By generating sub-spin images for angular partitioned 3D spaces, more unique features describing corresponding surfaces can be obtained, and improve the performance of landmark detection. In order to generate spin images robust to inaccurate surface normal direction, we utilize on averaging surface normal with its neighboring normal vectors. The experimental results show that the proposed method increases the accuracy in landmark detection by about 34% over a conventional method.

Multi-dimensional analyses of plant chromosomes and genomes.

  • Fukui, Kiichi;Ohmido, Nobuko;Wako, Toshiyuki
    • Proceedings of the Botanical Society of Korea Conference
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    • 1998.07a
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    • pp.61-70
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    • 1998
  • Genome and chromosome analyses in plants using fluorescence in situ hybridization (FISH) and immuno-staining (IMS) methods are reviewed by presenting the recent results obtained by the Chromosome Link, a group of chromosome and genome researchers. FISH is now effective to detect unique nucleotide sequences with 153 bp on the extended DNA fibers. Genomic in situ hybridization (GISH) also allows painting plant chromosomes of different genomes. GISH is quite effective to detect the genomic differentiation in the individual chromosomes within a nucleus. Three dimensional (3D) analyses are now available by confocal microscopy and a deconvolution system. These techniques are invaluable to visualize both the structural and functional dynamics within a nucleus. 3D-FISH revealed the spatial differentiation of different genomees within a nucleus. 3D-FISH also proved structural partition of centromeric and telomeric domains within a barely nucleus. The dynamic acetylation of histone H4 at the specific regions of a genome during a cell cycle is also analyzed using 3D-IMS. It is anticipated that these methods will provide us powerful tools to understand the structural and functional significance of plant chromosomes and genomes.

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RNA polymerase I subunit D activated by Yin Yang 1 transcription promote cell proliferation and angiogenesis of colorectal cancer cells

  • Jianfeng Shan;Yuanxiao Liang;Zhili Yang;Wenshan Chen;Yun Chen;Ke Sun
    • The Korean Journal of Physiology and Pharmacology
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    • v.28 no.3
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    • pp.265-273
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    • 2024
  • This study aims to explore possible effect of RNA polymerase I subunit D (POLR1D) on proliferation and angiogenesis ability of colorectal cancer (CRC) cells and mechanism herein. The correlation of POLR1D and Yin Yang 1 (YY1) expressions with prognosis of CRC patients in TCGA database was analyzed. Quantitative realtime polymerase chain reaction (qRT-PCR) and Western blot were applied to detect expression levels of POLR1D and YY1 in CRC cell lines and CRC tissues. SW480 and HT-29 cells were transfected with si-POLR1D or pcDNA3.1-POLR1D to achieve POLR1D suppression or overexpression before cell migration, angiogenesis of human umbilical vein endothelial cells were assessed. Western blot was used to detect expressions of p38 MAPK signal pathway related proteins and interaction of YY1 with POLR1D was confirmed by dual luciferase reporter gene assay and chromatin immunoprecipitation (ChIP). TCGA data showed that both POLR1D and YY1 expressions were up-regulated in CRC patients. High expression of POLR1D was associated with poor prognosis of CRC patients. The results showed that POLR1D and YY1 were highly expressed in CRC cell lines. Inhibition or overexpression of POLR1D can respectively suppress or enhance proliferation and angiogenesis of CRC cells. YY1 inhibition can suppress CRC progression and deactivate p38 MAPK signal pathway, which can be counteracted by POLR1D overexpression. JASPAR predicted YY1 can bind with POLR1D promoter, which was confirmed by dual luciferase reporter gene assay and ChIP. YY1 transcription can up-regulate POLR1D expression to activate p38 MAPK signal pathway, thus promoting proliferation and angiogenesis ability of CRC cells.

Aerial Object Detection and Tracking based on Fusion of Vision and Lidar Sensors using Kalman Filter for UAV

  • Park, Cheonman;Lee, Seongbong;Kim, Hyeji;Lee, Dongjin
    • International journal of advanced smart convergence
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    • v.9 no.3
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    • pp.232-238
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    • 2020
  • In this paper, we study on aerial objects detection and position estimation algorithm for the safety of UAV that flight in BVLOS. We use the vision sensor and LiDAR to detect objects. We use YOLOv2 architecture based on CNN to detect objects on a 2D image. Additionally we use a clustering method to detect objects on point cloud data acquired from LiDAR. When a single sensor used, detection rate can be degraded in a specific situation depending on the characteristics of sensor. If the result of the detection algorithm using a single sensor is absent or false, we need to complement the detection accuracy. In order to complement the accuracy of detection algorithm based on a single sensor, we use the Kalman filter. And we fused the results of a single sensor to improve detection accuracy. We estimate the 3D position of the object using the pixel position of the object and distance measured to LiDAR. We verified the performance of proposed fusion algorithm by performing the simulation using the Gazebo simulator.

A study of using the magnifying lens to detect the detail 3D data (정밀한 3차원 데이터를 얻기 위한 확대경 사용에 관한 연구)

  • Cha, Kuk-Chan
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.41-47
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    • 2006
  • The range-based method is easy to get the 3D data in detail, but the image-based is not. In this paper. employing the magnifying lens. the new approach to get the 3D data in detail is suggested. The magnifying lens amplifies the disparity in stereo vision system and the amplification of disparity is to increase the resolution of the depth. We mathematically and experimentally verifies the fact to amplify the disparity and suggests the method to improve the original 3D data with the detail 3D data.

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Magnet Location Estimation Technology in 3D Using MI Sensors (MI센서를 이용한 3차원상 자석 위치 추정 기술)

  • Ju Hyeok Jo;Hwa Young Kim
    • Journal of Sensor Science and Technology
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    • v.32 no.4
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    • pp.232-237
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    • 2023
  • This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.

Label Restoration Using Biquadratic Transformation

  • Le, Huy Phat;Nguyen, Toan Dinh;Lee, Guee-Sang
    • International Journal of Contents
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    • v.6 no.1
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    • pp.6-11
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    • 2010
  • Recently, there has been research to use portable digital camera to recognize objects in natural scene images, including labels or marks on a cylindrical surface. In many cases, text or logo in a label can be distorted by a structural movement of the object on which the label resides. Since the distortion in the label can degrade the performance of object recognition, the label should be rectified or restored from deformations. In this paper, a new method for label detection and restoration in digital images is presented. In the detection phase, the Hough transform is employed to detect two vertical boundaries of the label, and a horizontal edge profile is analyzed to detect upper-side and lower-side boundaries of the label. Then, the biquadratic transformation is used to restore the rectangular shape of the label. The proposed algorithm performs restoration of 3D objects in a 2D space, and it requires neither an auxiliary hardware such as 3D camera to construct 3D models nor a multi-camera to capture objects in different views. Experimental results demonstrate the effectiveness of the proposed method.

Detection of Moving Objects using Depth Frame Data of 3D Sensor (3D센서의 Depth frame 데이터를 이용한 이동물체 감지)

  • Lee, Seong-Ho;Han, Kyong-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.5
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    • pp.243-248
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    • 2014
  • This study presents an investigation into the ways to detect the areas of object movement with Kinect's Depth Frame, which is capable of receiving 3D information regardless of external light sources. Applied to remove noises along the boundaries of objects among the depth information received from sensors were the blurring technique for the x and y coordinates of pixels and the frequency filter for the z coordinate. In addition, a clustering filter was applied according to the changing amounts of adjacent pixels to extract the areas of moving objects. It was also designed to detect fast movements above the standard according to filter settings, being applicable to mobile robots. Detected movements can be applied to security systems when being delivered to distant places via a network and can also be expanded to large-scale data through concerned information.

A Study of Using the Magnifying Lens to Detect the Detailed 3D Data in the Stereo Vision (양안입체시에서 3차원 정밀 데이터를 얻기 위한 확대경 사용에 관한 연구)

  • Cha, Kuk-Chan
    • Journal of Korea Multimedia Society
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    • v.9 no.10
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    • pp.1296-1303
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    • 2006
  • The range-based method is easy to get the 3D data in detail, but the image-based is not. In this paper, I suggests the new approach to get the 3D data in detail from the magnified stereo image. Main idea is using the magnifying lens. The magnifying lens not only magnifies the object but also increases the depth resolution. The relation between the amplification of the disparity and the increase of the depth resolution is verified mathematically and the method to improve the original 3D data is suggested.

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