• Title/Summary/Keyword: object matching

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Multi-camera Matching for Mixed Reality Object Tracking (다중카메라 매칭을 이용한 혼합현실 객체 추적)

  • Yang, Dong-ho;Kim, Jang-hyong;Kim, Hyung-soo;Lee, Sang-boo
    • Annual Conference of KIPS
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    • 2013.11a
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    • pp.1567-1570
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    • 2013
  • 최근 혼합현실 기반의 다양한 콘텐츠의 생산이 활성화 되고 있다. 이러한 콘텐츠는 실세계의 촬영 영상과 가상의 영상을 합성하는 기법으로 이를 위해서는 실세계의 촬영 영상과 마커 또는 생체 정보등의 객체를 이용하여 영상 합성을 통하여 구현되는 것이 일반적이다. 본 논문에서는 이러한 혼합영상에서의 가상영상 합성을 위해 스테레오 카메라를 이용, 영상의 객체 깊이를 측정하는 시스템을 구현한다.

Character Recognition Based on Adaptive Statistical Learning Algorithm

  • K.C. Koh;Park, H.J.;Kim, J.S.;K. Koh;H.S. Cho
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.109.2-109
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    • 2001
  • In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...

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Development of Hand-drawn Clothing Matching System (손그림을 통한 의류검색 시스템)

  • Lim, Ho-Kyun;Moon, Mikyeong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.553-554
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    • 2021
  • 온라인 쇼핑 시장의 규모나 나날이 증가하고 있는 추세이다. 이러한 시장 경제 속에서 사용자들을 유지하기 위해 저마다 다른 독자적이 서비스를 제공하고 있으며 서비스 경쟁의 노력 중 하나로 이미지 검색을 사용하는 사이트가 늘어나고 있다. 하지만 기존의 이미지 검색을 의류 쇼핑몰에 그대로 적용할 경우 사용자가 검색하고자 하는 의류가 해당 사이트에 존재하지 않거나 검색을 위한 이미지를 소유하고 있지 않은 경우 기존 텍스트 형식의 검색 시스템을 그대로 이용해야 하는 등의 문제들이 존재한다. 이에 본 논문에서는 사용자가 직접 그린 그림을 이용한 '손그림 의류 검색 시스템'을 제안하였다. 본 시스템을 기존의 텍스트와 이미지에 국한되어 있던 검색 경험과 별개로 그림으로 검색을 시도함으로써 사용자에게 폭넓은 검색 경험을 제공할 수 있을 것으로 기대한다.

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Cylinder-based Angular Interpolation to Efficiently Feature Point Matching in AR Environment (AR환경에서 특징 포인트를 효율적으로 매칭하기 위한 실린더 기반의 각도 보간)

  • Moon, YeRin;Kim, Jong-Hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.365-368
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    • 2022
  • 본 논문에서는 가상 물체를 현실과 오차 없이 정확하게 증강 시켜야 하는 상황에서 특징 포인트를 이용하여 효율적으로 매칭하기 위한 실린더 기반의 각도 보간 기법을 제안한다. 증강현실에서 활용되는 대표적인 객체를 증강하는 방법은 특징 포인트들을 트래킹하여 찾아낸 후, RANSAC 알고리즘을 기반으로 포인트 셋에서 바닥, 벽과 같이 하나의 평면을 구성하고 그 위에 객체를 증강한다. 이 방법은 평면을 이용하기 때문에 계산량이 적지만, 증강 위치에 대한 오차가 존재하기 때문에 때때로 잘못된 위치에 객체가 배치되는 경우가 발생한다. 특히, 의료시설, 도로 공사에서 증강 현실을 사용했을 때에 증강된 가상물체의 위치, 크기 등이 현실에서 작은 오차라도 어긋날 경우 크게 사고가 발생할 수 있다. 본 논문에서는 평면 생성 없이 특징 포인트만을 이용하여 효율적으로 매칭 할 수 있는 실린더 기반의 각도 보간을 이용하여 정확하게 객체를 증강할 수 있는 결과를 보여준다.

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The effect of orientation on recognizing object representation (규범적 표상의 방향성 효과)

  • Jung, Hyo-Sun;Lee, Seung-Bok;Jung, Woo-Hyun
    • Science of Emotion and Sensibility
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    • v.11 no.4
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    • pp.501-510
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    • 2008
  • The purpose of this study was to investigate whether the orientation of the head position across different categories affect reaction time and accuracy of object recognition. Fifty four right handed undergraduate students were participated in the experiment. Participants performed the word-picture matching tasks, which were different in terms of head direction of object (i.e., Left-headed or Right-headed) and object category (i.e., natural : animal or artificial : tool). Participants were asked to decide whether each picture matched the word which was followed by the picture. For accuracy, no statistically significant difference was found for both animal and tool pictures due to the ceiling effect. Interaction effect of category and orientation were statistically significant, whereas only the main effect of category was significant. In the animal condition, faster reaction times were observed for left to right than right to left presentation, while no statistical significant difference was found in the tool condition. The orientation of the object's canonical representation was different across different categories. The faster RT for the animal condition implies that the canonical representation for animal is left-headed. This could be due to the orientation of the face.

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A Study on Abalone Young Shells Counting System using Machine Vision (머신비전을 이용한 전복 치패 계수에 관한 연구)

  • Park, Kyung-min;Ahn, Byeong-Won;Park, Young-San;Bae, Cherl-O
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.4
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    • pp.415-420
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    • 2017
  • In this paper, an algorithm for object counting via a conveyor system using machine vision is suggested. Object counting systems using image processing have been applied in a variety of industries for such purposes as measuring floating populations and traffic volume, etc. The methods of object counting mainly used involve template matching and machine learning for detecting and tracking. However, operational time for these methods should be short for detecting objects on quickly moving conveyor belts. To provide this characteristic, this algorithm for image processing is a region-based method. In this experiment, we counted young abalone shells that are similar in shape, size and color. We applied a characteristic conveyor system that operated in one direction. It obtained information on objects in the region of interest by comparing a second frame that continuously changed according to the information obtained with reference to objects in the first region. Objects were counted if the information between the first and second images matched. This count was exact when young shells were evenly spaced without overlap and missed objects were calculated using size information when objects moved without extra space. The proposed algorithm can be applied for various object counting controls on conveyor systems.

Advanced Design of Birdcage RF Coil for Various Absorption Regions at 3T MRI System

  • Lee, Jung-Woo;Choe, Bo-Young;Choi, Chi-Bong;Huh, Soon-Nyoung
    • Journal of the Korean Magnetic Resonance Society
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    • v.9 no.1
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    • pp.48-60
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    • 2005
  • Purpose: The purpose of this study was to design and build an optimized birdcage resonator configuration with a low pass filter, which would facilitate the acquisition of high-resolution 3D-image of small animals at 3T MRI system. Methods and Materials: The birdcage resonator with 12-element structures was built, in order to ensure B1 homogeneity over the image volume and maximum filling factor, and hence to maximize the signal to noise ratio (SNR) and resolution of the 3-dimensional images. The diameter and length of each element of a birdcage resonator were as follows: (1) diameter 13 cm, length 22 cm, (2) diameter 15 cm, length 22 cm, (3) diameter 17 cm, length 25 cm. Spin echo pulse sequence and fast spin echo pulse sequence were employed in obtaining MR images. The quality of the manufactured birdcage resonators wes evaluated on the basis of the return loss following matching and tuning process. Results: The experimental MR image of phantoms by the various manufactured birdcage resonators were obtained to compare the SNR in accordance with the size of objects. The size of an object to that of coil was identified by parameters that were estimated from the image of a phantom. First, the diameter of the birdcage resonator was 15cm, and the ratio of the tangerine to the birdcage resonator accounted for approximately 27%. The Q factor was 53.2 and the SNR was 150.7. Second, at the same birdcage resonator, the ratio of the orange was approximately 53%. The SNR and the Q parameter was 212.8 and 91.2, respectively. Conclusion: The present study demonstrated that if birdcage resonators have the same forms, SNR could be different depending on the size of an object, especially when the size of an object to that of coil is approximately 40~80%, the former is bigger than the latter. Therefore, when the size of an object to be observed is smaller than that of coil, the coil should be manufactured in accordance with the size of an object in order to obtain much more excellent images.

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Tracking Moving Object using Hierarchical Search Method (계층적 탐색기법을 이용한 이동물체 추적)

  • 방만식;김태식;김영일
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.3
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    • pp.568-576
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    • 2003
  • This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

Stereo-based Robust Human Detection on Pose Variation Using Multiple Oriented 2D Elliptical Filters (방향성 2차원 타원형 필터를 이용한 스테레오 기반 포즈에 강인한 사람 검출)

  • Cho, Sang-Ho;Kim, Tae-Wan;Kim, Dae-Jin
    • Journal of KIISE:Software and Applications
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    • v.35 no.10
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    • pp.600-607
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    • 2008
  • This paper proposes a robust human detection method irrespective of their pose variation using the multiple oriented 2D elliptical filters (MO2DEFs). The MO2DEFs can detect the humans regardless of their poses unlike existing object oriented scale adaptive filter (OOSAF). To overcome OOSAF's limitation, we introduce the MO2DEFs whose shapes look like the oriented ellipses. We perform human detection by applying four different 2D elliptical filters with specific orientations to the 2D spatial-depth histogram and then by taking the thresholds over the filtered histograms. In addition, we determine the human pose by using convolution results which are computed by using the MO2DEFs. We verify the human candidates by either detecting the face or matching head-shoulder shapes over the estimated rotation. The experimental results showed that the accuracy of pose angle estimation was about 88%, the human detection using the MO2DEFs outperformed that of using the OOSAF by $15{\sim}20%$ especially in case of the posed human.

A Combined Hough Transform based Edge Detection and Region Growing Method for Region Extraction (영역 추출을 위한 Hough 변환 기반 에지 검출과 영역 확장을 통합한 방법)

  • N.T.B., Nguyen;Kim, Yong-Kwon;Chung, Chin-Wan;Lee, Seok-Lyong;Kim, Deok-Hwan
    • Journal of KIISE:Databases
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    • v.36 no.4
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    • pp.263-279
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    • 2009
  • Shape features in a content-based image retrieval (CBIR) system are divided into two classes: contour-based and region-based. Contour-based shape features are simple but they are not as efficient as region-based shape features. Most systems using the region-based shape feature have to extract the region firs t. The prior works on region-based systems still have shortcomings. They are complex to implement, particularly with respect to region extraction, and do not sufficiently use the spatial relationship between regions in the distance model In this paper, a region extraction method that is the combination of an edge-based method and a region growing method is proposed to accurately extract regions inside an object. Edges inside an object are accurately detected based on the Canny edge detector and the Hough transform. And the modified Integrated Region Matching (IRM) scheme which includes the adjacency relationship of regions is also proposed. It is used to compute the distance between images for the similarity search using shape features. The experimental results show the effectiveness of our region extraction method as well as the modified IRM. In comparison with other works, it is shown that the new region extraction method outperforms others.