• Title/Summary/Keyword: Image feature points

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INTERACTIVE FEATURE EXTRACTION FOR IMAGE REGISTRATION

  • Kim Jun-chul;Lee Young-ran;Shin Sung-woong;Kim Kyung-ok
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.641-644
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    • 2005
  • This paper introduces an Interactive Feature Extraction (!FE) approach for the registration of satellite imagery by matching extracted point and line features. !FE method contains both point extraction by cross-correlation matching of singular points and line extraction by Hough transform. The purpose of this study is to minimize user's intervention in feature extraction and easily apply the extracted features for image registration. Experiments with these imagery dataset proved the feasibility and the efficiency of the suggested method.

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Ship Design Visualization System base on Augmented Reality (증강현실 기반의 선박설계 시각화 시스템)

  • Park, Mi-Jeong;Yoo, Seung-Hyeok;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.249-251
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    • 2012
  • Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

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3D View Synthesis with Feature-Based Warping

  • Hu, Ningning;Zhao, Yao;Bai, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5506-5521
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    • 2017
  • Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.

Vision System for NN-based Emotion Recognition (신경회로망 기반 감성 인식 비젼 시스템)

  • Lee, Sang-Yun;Kim, Sung-Nam;Joo, Young-Hoon;Park, Chang-Hyun;Sim, Kwee-Bo
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2036-2038
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    • 2001
  • In this paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using vision system. In the proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Also, we use R,G,B(red, green, blue) color image data and the gray image data to get the highly trust rate of feature point extraction. For this, we propose an algorithm to extract four feature points (eyebrow, eye, nose, mouth) from the face image acquired by the color CCD camera and find some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector(position and distance among the feature points). Finally, we show the practical application possibility of the proposed method.

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High-Speed Image Matching Method Using Geometry - Phase Information (기하 위상 정보를 이용한 고속 영상 정합 기법)

  • Chong Min-Yeong;Oh Jae-Yong;Lee Chil-Woo;Bae Ki-Tae
    • Journal of Korea Multimedia Society
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    • v.8 no.9
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    • pp.1195-1207
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    • 2005
  • In this paper, we describe image matching techniques which is automatically retrieving the exact matching area using geometry-phase information. We proposed a Matching Method which is rapidly estimating the correspondent points between adjacent images that included big-rotation and top-bottom movement element. It is a method that reduce computation quantity to be required to find an exact correspondent position using geometry-phase information of extracted points in images and DT map which set the distance value among feature points and other points on the basis of each feature point of a image. The proposed method shows good performance especially in the part to search a exact correspondent position between adjacent images that included big-rotation and top-bottom movement element.

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Laser Image SLAM based on Image Matching for Navigation of a Mobile Robot (이동 로봇 주행을 위한 이미지 매칭에 기반한 레이저 영상 SLAM)

  • Choi, Yun Won;Kim, Kyung Dong;Choi, Jung Won;Lee, Suk Gyu
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.2
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    • pp.177-184
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    • 2013
  • This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

Navigation Sign Recognition in Indoor enviroments Using Fuzzy Inference (퍼지추론을 이용한 실내환경에서의 주행신호인식)

  • 김전호;유범재;조영조;박민용;고범석
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.11a
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    • pp.141-144
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    • 1997
  • This paper presents a method of navigation sign recognition in indoor environments using a fuzzy inference for an autonomous mobile robot. In order to adapt to image deformation of a navigation sign resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The DASM is proposed to detect correct feature points among incorrect feature points. Finally sugeno-style fuzzy inference are adopted for recognizing the navigation sign.

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Parallel Injection Method for Improving Descriptive Performance of Bi-GRU Image Captions (Bi-GRU 이미지 캡션의 서술 성능 향상을 위한 Parallel Injection 기법 연구)

  • Lee, Jun Hee;Lee, Soo Hwan;Tae, Soo Ho;Seo, Dong Hoan
    • Journal of Korea Multimedia Society
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    • v.22 no.11
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    • pp.1223-1232
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    • 2019
  • The injection is the input method of the image feature vector from the encoder to the decoder. Since the image feature vector contains object details such as color and texture, it is essential to generate image captions. However, the bidirectional decoder model using the existing injection method only inputs the image feature vector in the first step, so image feature vectors of the backward sequence are vanishing. This problem makes it difficult to describe the context in detail. Therefore, in this paper, we propose the parallel injection method to improve the description performance of image captions. The proposed Injection method fuses all embeddings and image vectors to preserve the context. Also, We optimize our image caption model with Bidirectional Gated Recurrent Unit (Bi-GRU) to reduce the amount of computation of the decoder. To validate the proposed model, experiments were conducted with a certified image caption dataset, demonstrating excellence in comparison with the latest models using BLEU and METEOR scores. The proposed model improved the BLEU score up to 20.2 points and the METEOR score up to 3.65 points compared to the existing caption model.

Visual Servoing of manipulator using feature points (특징점을 이용한 매니퓰래이터 자세 시각 제어)

  • 박성태;이민철
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.1087-1090
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    • 2004
  • stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. In this paper we persent a visual approach to the problem of object grasping. First we propose object recognization method which can find the object position and pose using feature points. A robot recognizes the feature point to Object. So a number of feature point is the more, the better, but if it is overly many, the robot have to process many data, it makes real-time image processing ability weakly. In other to avoid this problem, the robot selects only two point and recognize the object by line made by two points. Second we propose trajectory planing of the robot manipulator. Using grometry of between object and gripper, robot can find a goal point to translate the robot manipulator, and then it can grip the object successfully.

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Correspondence Search Algorithm for Feature Tracking with Incomplete Trajectories

  • Jeong, Jong-Myeon;Moon, young-Shik
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.803-806
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    • 2000
  • The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

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