• Title/Summary/Keyword: Marker Detection

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Dynamic Manipulation of a Virtual Object in Marker-less AR system Based on Both Human Hands

  • Chun, Jun-Chul;Lee, Byung-Sung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.4
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    • pp.618-632
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    • 2010
  • This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human's body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.

IR LED Marker Detection Method for Production of Multiple Marker based on Augmented Reality (다수 마커의 제작을 위한 증강현실 기반의 IR LED 마커 검출 기법)

  • Lee, Hye-Mi;Ryu, Nam-Hoon;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.3
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    • pp.457-463
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    • 2011
  • As computer related technologies are developed, interests in augmented reality technologies are greatly increasing. Augmented reality is a technology that composes digital contents from the real input images through camera and it enables interaction with users. This study designed a directional marker using LED light that emits infrared ray, then, provided a detection algorithm and a marker information extraction method that can realize various virtual objects as augmented reality from one marker. The newly designed method provides a solution to settle the problems in existing marker technologies such as decrease of immersiveness and read rate and single information expression, and at the same time it can minimize the cost or time consumption in marker information storage.

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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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.

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.

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%.

A Study on Marker-based Detection Method of Object Position using Perspective Projection

  • Park, Minjoo;Jang, Kyung-Sik
    • Journal of information and communication convergence engineering
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    • v.20 no.1
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    • pp.65-72
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    • 2022
  • With the mark of the fourth industrial revolution, the smart factory is evolving into a new future manufacturing plant. As a human-machine-interactive tool, augmented reality (AR) helps workers acquire the proficiency needed in smart factories. The valuable data displayed on the AR device must be delivered intuitively to users. Current AR applications used in smart factories lack user movement calibration, and visual fiducial markers for position correction are detected only nearby. This paper demonstrates a marker-based object detection using perspective projection to adjust augmented content while maintaining the user's original perspective with displacement. A new angle, location, and scaling values for the AR content can be calculated by comparing equivalent marker positions in two images. Two experiments were conducted to verify the implementation of the algorithm and its practicality in the smart factory. The markers were well-detected in both experiments, and the applicability in smart factories was verified by presenting appropriate displacement values for AR contents according to various movements.

Development of a Detection and Recognition System for Rectangular Marker (사각형 마커 검출 및 인식 시스템 개발)

  • Kang Sun-Kyung;Lee Sang-Seol;Jung Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4 s.42
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    • pp.97-107
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    • 2006
  • In this paper, we present a method for the detection and recognition of rectangular markers from a camera image. It converts the camera 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 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. It then 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 98% recognition rate at maximum for 50 markers and execution speed of 11.1 frames/sec for images which contains eleven markers.

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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.