• Title/Summary/Keyword: Visual feature

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Animal Fur Recognition Algorithm Based on Feature Fusion Network

  • Liu, Peng;Lei, Tao;Xiang, Qian;Wang, Zexuan;Wang, Jiwei
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.1-10
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    • 2022
  • China is a big country in animal fur industry. The total production and consumption of fur are increasing year by year. However, the recognition of fur in the fur production process still mainly relies on the visual identification of skilled workers, and the stability and consistency of products cannot be guaranteed. In response to this problem, this paper proposes a feature fusion-based animal fur recognition network on the basis of typical convolutional neural network structure, relying on rapidly developing deep learning techniques. This network superimposes texture feature - the most prominent feature of fur image - into the channel dimension of input image. The output feature map of the first layer convolution is inverted to obtain the inverted feature map and concat it into the original output feature map, then Leaky ReLU is used for activation, which makes full use of the texture information of fur image and the inverted feature information. Experimental results show that the algorithm improves the recognition accuracy by 9.08% on Fur_Recognition dataset and 6.41% on CIFAR-10 dataset. The algorithm in this paper can change the current situation that fur recognition relies on manual visual method to classify, and can lay foundation for improving the efficiency of fur production technology.

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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Pose Tracking of Moving Sensor using Monocular Camera and IMU Sensor

  • Jung, Sukwoo;Park, Seho;Lee, KyungTaek
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.8
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    • pp.3011-3024
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    • 2021
  • Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

A Study for Visual Style for Feature Animation - A Case of Feature Animation - (극장 판 장편 애니메이션의 시각적 스타일에 관한 연구 -장편애니메이션 'Life is Cool'의 제작사례를 중심으로-)

  • Choi, Seung-Won
    • Journal of Broadcast Engineering
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    • v.12 no.5
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    • pp.391-400
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    • 2007
  • The ways of expression are infinite to make animated film. When we compare to live action film, that fact is the actual power that animation only has and is one of the big weapons to appeal to the audience. Nonetheless, techniques to be chosen are monolithic like drawing, 3D computer, and clay when animation maker makes feature animation to screen in movie theatre. It's probably because feature animation must have popularity of visual style and they need to standardize technique about side of making. But popularity in expression does not mean monolithic visual style and making technique. It should be understood about side of artistic value to fascinate public audience. Audience is always eager for new subject, new directing style and new visual style. Monotonous and boring animation cannot but turn away from the audience. So if production does not have artistic value, we cannot expect commercial value and success also even it plans and makes for the feature animation. To create new visual style fnr animation is not only limited to artwork itself but also creation, which is included story and tone of the film and acting style about character. Also making process must be calculated and experimented to actualize that visual style about side of making.

Content-Based Retrieval using MPEG-7 Visual Descriptor and Hippocampal Neural Network (MPEG-7 시각 기술자와 해마 신경망을 이용한 내용기반 검색)

  • Kim Young Ho;Kang Dae-Seong
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.12
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    • pp.1083-1087
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    • 2005
  • As development of digital technology, many kinds of multimedia data are used variously and requirements for effective use by user are increasing. In order to transfer information fast and precisely what user wants, effective retrieval method is required. As existing multimedia data are impossible to apply the MPEG-1, MPEG-2 and MPEG-4 technologies which are aimed at compression, store and transmission. So MPEG-7 is introduced as a new technology for effective management and retrieval of multimedia data. In this paper, we extract content-based features using color descriptor among the MPEG-7 standardization visual descriptor, and reduce feature data applying PCA(Principal Components Analysis) technique. We model the cerebral cortex and hippocampal neural network in engineering domain, and team content-based feature vectors fast and apply the hippocampal neural network algorithm to compose of optimized feature. And then we present fast and precise retrieval effect when indexing and retrieving.

Visual servoing of robot manipulator by fuzzy membership function based neural network (퍼지 신경망에 의한 로보트의 시각구동)

  • 김태원;서일홍;조영조
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.874-879
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    • 1992
  • It is shown that there exists a nonlinear mappping which transforms features and their changes to the desired camera motion without measurement of the relative distance between the camera and the part, and the nonlinear mapping can eliminate several difficulties encountered when using the inverse of the feature Jacobian as in the usual feature-based visual feedback controls. And instead of analytically deriving the closed form of such a nonlinear mapping, a fuzzy membership function (FMF) based neural network is then proposed to approximate the nonlinear mapping, where the structure of proposed networks is similar to that of radial basis function neural network which is known to be very useful in function approximations. The proposed FMF network is trained to be capable of tracking moving parts in the whole work space along the line of sight. For the effective implementation of proposed IMF networks, an image feature selection processing is investigated, and required fuzzy membership functions are designed. Finally, several numerical examples are illustrated to show the validities of our proposed visual servoing method.

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Visual object tracking using inter-frame correlation of convolutional feature maps (컨볼루션 특징 맵의 상관관계를 이용한 영상물체추적)

  • Kim, Min-Ji;Kim, Sungchan
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.4
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    • pp.219-225
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    • 2016
  • Visual object tracking is one of the key tasks in computer vision. Robust trackers should address challenging issues such as fast motion, deformation, occlusion and so on. In this paper, we therefore propose a visual object tracking method that exploits inter-frame correlations of convolutional feature maps in Convolutional Neural Net (ConvNet). The proposed method predicts the location of a target by considering inter-frame spatial correlation between target location proposals in the present frame and its location in the previous frame. The experimental results show that the proposed algorithm outperforms the state-of-the-art work especially in hard-to-track sequences.

Uncalibrated Visual Servoing through the Efficient Estimation of the Image Jacobian for Large Residual

  • Kim, Gon-Woo
    • Journal of Electrical Engineering and Technology
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    • v.8 no.2
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    • pp.385-392
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    • 2013
  • An uncalibrated visual servo control method for tracking a target is presented. We define the robot-positioning problem as an unconstrained optimization problem to minimize the image error between the target feature and the robot end-effector feature. We propose a method to find the residual term for more precise modeling using the secant approximation method. The composite image Jacobian is estimated by the proper method for eye-to-hand configuration without knowledge of the kinematic structure, imaging geometry and intrinsic parameter of camera. This method is independent of the motion of a target feature. The algorithm for regulation of the joint velocity for safety and stability is presented using the cost function. Adaptive regulation for visibility constraints is proposed using the adaptive parameter.

A Novel Visual Servoing Method Using QR Decomposition and Disturbance Observer (QR분해와 외란관측기를 이용한 시각구동 방법)

  • 이준수;서일홍;유범재;오상록
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.6
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    • pp.462-470
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    • 2000
  • This paper proposes a visual servoing method based on QR decomposition and disturbance observer. The QR decomposition factors the image feature Jacobian into a unitary matrix and an upper triangular matrix. And it is shown that several performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability can be improved for any general image feature Jacobian by QR decomposition and disturbance observer. To show the validity of the proposed approach, visual servoing with stereo vision is carried out for a Samsung FARAMAN 6-axis industrial robot manipulator.

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Visual Touch Recognition for NUI Using Voronoi-Tessellation Algorithm (보로노이-테셀레이션 알고리즘을 이용한 NUI를 위한 비주얼 터치 인식)

  • Kim, Sung Kwan;Joo, Young Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.3
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    • pp.465-472
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    • 2015
  • This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.