• Title/Summary/Keyword: Marker Detection

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A Method of Lane Marker Detection Robust to Environmental Variation Using Lane Tracking (차선 추적을 이용한 환경변화에 강인한 차선 검출 방법)

  • Lee, Jihye;Yi, Kang
    • Journal of Korea Multimedia Society
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    • v.21 no.12
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    • pp.1396-1406
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    • 2018
  • Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

Enhancement of the Correctness of Marker Detection and Marker Recognition based on Artificial Neural Network (인공신경망을 이용한 마커 검출 및 인식의 정확도 개선)

  • Kang, Sun-Kyung;Kim, Young-Un;So, In-Mi;Jung, Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.1
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    • pp.89-97
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    • 2008
  • In this paper, we present a method for the enhancement of marker detection correctness and marker recognition speed by using artificial neural network. Contours of objects are extracted from the input image. They are approximated to a list of line segments. Quadrangles are found with the geometrical features of the approximated line segments. They are normalized into exact squares by using the warping technique and scale transformation. Feature vectors are extracted from the square image by using principal component analysis. Artincial neural network is used to checks if the square image is a marker image or a non-marker image. After that, the type of marker is recognized by using an artificial neural network. Experimental results show that the proposed method enhances the correctness of the marker detection and recognition.

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Audio Marker Detection of the implementation for Effective Augmented Reality (효과적인 증강현실 구현을 위한 오디오 마커 검출)

  • Jeon, Soo-Jin;Kim, Young-Seop
    • Journal of the Semiconductor & Display Technology
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    • v.10 no.2
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    • pp.121-124
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    • 2011
  • Augmented Reality integrates virtual objects onto a real world so that it extends the human's sensibility of real-world. an Augmented Reality technology combines real and virtual object in a real environment, and runs interactive in real time, and is regarded as an emerging technology in a large part of the future of information technology. So the benefits for the various businesses are estimated to be very high. In this paper, combine ARToolkit with OpenAL we can provide audio to users. These proposed methodologies will contribute to a better immersive realization of the conventional Augmented Reality system.

A Robust Marker Detection Algorithm Using Hybrid Features in Augmented Reality (증강현실 환경에서 복합특징 기반의 강인한 마커 검출 알고리즘)

  • Park, Gyu-Ho;Lee, Heng-Suk;Han, Kyu-Phil
    • The KIPS Transactions:PartA
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    • v.17A no.4
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    • pp.189-196
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    • 2010
  • This paper presents an improved marker detection algorithm using hybrid features such as corner, line segment, region, and adaptive threshold values, etc. In usual augmented reality environments, there are often marker occlusion and poor illumination. However, existing ARToolkit fails to recognize the marker in these situations, especially, partial concealment of marker by user, large change of illumination and dim circumstances. In order to solve these problems, the adaptive threshold technique is adopted to extract a marker region and a corner extraction method based on line segments is presented against marker occlusions. In addition, a compensating method, corresponding the marker size and center between registered and extracted one, is proposed to increase the template matching efficiency, because the inside marker size of warped images is slightly distorted due to the movement of corner and warping. Therefore, experimental results showed that the proposed algorithm can robustly detect the marker in severe illumination change and occlusion environment and use similar markers because the matching efficiency was increased almost 30%.

Performance Enhancement of Marker Detection and Recognition using SVM and LDA (SVM과 LDA를 이용한 마커 검출 및 인식의 성능 향상)

  • Kang, Sun-Kyoung;So, In-Mi;Kim, Young-Un;Lee, Sang-Seol;Jung, Sung-Tae
    • Journal of Korea Multimedia Society
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    • v.10 no.7
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    • pp.923-933
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    • 2007
  • In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

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Mobile-AR Inspection System Based on RF-Marker to Improve Marker Detection (마커 검출 개선을 위한 RF-Marker기반 Mobile AR검사 시스템)

  • Lee, Jung-Min;Lee, Kyung-Ho;Kim, Dae-Seok
    • Korean Journal of Computational Design and Engineering
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    • v.17 no.3
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    • pp.208-215
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    • 2012
  • Augmented reality can help to improve user's engineering abilities such as perception and decision making in industry field. Therefore we have studied on the maintenance-supporting applications for inspectors previously. The advantage of pre-existing marker system is that the making and using are easier than any other feature tracking and detection methods. However it must to be exposed to the sufficient light to be detected by computer image processing. The most of industry field is not in clean environment and there are not sufficient light as well. So, the normal marker system is not appropriated for industrial fields. This paper suggests RFID-based marker system to improve marker-detection ability in our AR maintenance system. RFID is not implemented by image processing but it is implemented by electromagnetic induction. Therefore we could more precisely detect markers even if the environment is low-light intensity condition.

Improved LiDAR-Camera Calibration Using Marker Detection Based on 3D Plane Extraction

  • Yoo, Joong-Sun;Kim, Do-Hyeong;Kim, Gon-Woo
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2530-2544
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    • 2018
  • In this paper, we propose an enhanced LiDAR-camera calibration method that extracts the marker plane from 3D point cloud information. In previous work, we estimated the straight line of each board to obtain the vertex. However, the errors in the point information in relation to the z axis were not considered. These errors are caused by the effects of user selection on the board border. Because of the nature of LiDAR, the point information is separated in the horizontal direction, causing the approximated model of the straight line to be erroneous. In the proposed work, we obtain each vertex by estimating a rectangle from a plane rather than obtaining a point from each straight line in order to obtain a vertex more precisely than the previous study. The advantage of using planes is that it is easier to select the area, and the most point information on the board is available. We demonstrated through experiments that the proposed method could be used to obtain more accurate results compared to the performance of the previous method.

Marker Detection by Using Affine-SIFT Matching Points for Marker Occlusion of Augmented Reality (증강현실에서 가려진 마커를 위한 Affine-SIFT 정합 점들을 이용한 마커 검출 기법)

  • Kim, Yong-Min;Park, Chan-Woo;Park, Ki-Tae;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.2
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    • pp.55-65
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    • 2011
  • In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.

Marker Recognition System for the User Interface of a Serious Case (중증환자 인터페이스를 위한 마커 인식 시스템)

  • So, In-Mi;Kang, Sun-Kyung;Kim, Young-Un;Jung, Sung-Tae
    • The KIPS Transactions:PartB
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    • v.14B no.3 s.113
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    • pp.191-198
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    • 2007
  • In this paper, we present a marker detection and recognition method from camera image for a disabled person to interact with a server system which can control appliance of surrounding environment. It converts the camera image to a binary image by using multi-threshold and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds rectangular markers by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted markers into exact squares by using the warping technique. It extracts feature vectors from marker image by using principal component analysis and then recognizes the marker. The proposed marker recognition system is robust for light change by using multi-threshold. Also, it is robust for angular variation of camera by using warping technique and principal component analysis. Experimental results show that the proposed method achieves 100% recognition rate at maximum for 21 markers and execution speed of 12 frames/sec.

Simple Camera-based Evaluation System for Lower Limb Alignment during Pedalling (자전거 페달링 시 하지 정렬 평가를 위한 영상 시스템 개발)

  • Oh, Ho-Sang;Choi, Jin-Seung;Kang, Dong-Won;Seo, Jeong-Woo;Bae, Jae-Hyuk;Tack, Gye-Rae
    • Korean Journal of Sport Biomechanics
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    • v.22 no.1
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    • pp.123-129
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    • 2012
  • Simple camera-based system for evaluation of lower limb alignment as a part of an automated cycling fitting system was developed and verified in this study. Developed imaging system can evaluate lower limb alignment quantitatively during pedaling using a general camcorder and single marker attached on the knee. Threshold-based marker detection algorithm was proposed in this study. Experiment was carried out to compare the trajectory data from marker detection algorithm of the developed imaging system with the trajectory data from 3-D motion capture system. Results showed that average error between trajectories was 2.33 mm (0.92 %) in the vertical direction and 0.62 mm (1.86 %) in the medio-lateral direction. There existed significant correlation between two measured values (r=0.9996 in the vertical direction and r=0.9975 in the medio-lateral direction). It can be concluded that developed imaging system be applied to evaluate lower limb alignment which is an important factor for dynamic bicycle fitting.