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Liczba wyników
2015 | 5 | 841--847
Tytuł artykułu

Augmented Reality Using Optical Flow

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper deals with the application of Lucas- Kanade optical flow algorithm to develop an augmented reality (AR) system. Merging of a live view of the physical real world with context-related computer-rendered images to create a mixed image is a challenging problem. A virtual object has to be located in the correct pose and position in real time and perspective. Besides the occlusion problem need to be taken into consideration. In the paper a computer-vision based method for AR systems based on the fiducial marker matching is proposed. For simplicity black square was used as the marker. This method consists of two main steps. The initial step uses Hough's transformation to detect the marker initial position and to select the marker tracked points. In the second step for each image frame these selected points are being tracked using Lucas-Kanade optical flow method. The positions of the selected points are used for calculating the pose and position of a virtual object. Unlike existing method proposed system using optical flow to increase speed performance. The examples of AR applications using the proposed algorithm are provided and discussed.(original abstract)
Rocznik
Tom
5
Strony
841--847
Opis fizyczny
Twórcy
  • Polish Academy of Science
Bibliografia
  • Chari V, Singh J M, Narayanan P J, (2008) Augmented Reality using Over-Segmentation, National Conference on Computer Vision Pattern Recognition Image Processing and Graphics.
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  • Bouguet J Y (2001) Pyramidal implementation of the affine Lucas Kanade feature tracker description of the algorithm, Intel Corporation, 5.
  • Sun D, Roth S, Lewis J P, (2008) Learning Optical Flow, Computer Vision - ECCV 2008, Springer, 83-97.
  • Computer Vision Library: OpenCV (2012) http://opencv.willowgarage. com version 2.4.
  • Beauchemin S S, Baron J L (1995) The computation of optical flow, ACM Computing Surveys (CSUR), 27(3), 433-466.
  • Baker S, Scharstein D, Lewis J L, Roth S, Black M, Szeliski M (2011) A database and Evaluation Metodology for Optical Flow, International Journal of Computer Vision, 92(1), 1-31.
  • Herakleous K, Poullis C H (2013) Improving augmented reality applications with optical flow, IEEE International Conference on Image Processing 2013, 3403-3406.
  • Li H, Qi M, Wu Y (2012) A Real-Time Registration Method of Augmented Reality based on SURF and Optical Flow, Journal of Theoretical and Applied Information Technology, 42(2), 281-286.
  • Ji J, Chen G, Sun L (2011) A novel Hough transform method for line detection by anhancing accumulator array, Pattern Recognition Letters, 32(11), 1503-1510.
  • Hirzer M (2008) Marker detection for augmented reality applications, Institut for Computer Graphics and Vision, Graz University, Technical Report, ICG-TR-08/05.
  • Fuhrt B (2011) Handbook of Augmented Reality, Springer Science+ Business Media, New York, New York.
  • Lee T, Hollerer T (2009) Multithreaded Hybrid Feature Tracking for Markerless Augmented Reality, IEEE Transactions on Visualization and Computer Graphics, 15(3), 355-368.
  • Gedik O S, Alatan A A (2013) 3-D Rigid Body Tracking Using Vision and Depth Sensors, IEEE Transactions on Cybernetics, 43(5), 1395- 1405.
  • Cheok A D, Qiu Y, Xu K, Kumar G K (2007) Combined Wireless Hardware and Real-Time Computer Vision Interface for Tangible Mixed Reality, IEEE Transactions on Industrial Electronics, 54(4), 2174-2189.
  • Chen Z, Li X (2010) Markless Tracking based on Natural Feature for Augmented Reality, IEEE International Conference on Educational and Information Technology (ICEIT 2010), 2, 126-129.
  • Fiala M (2010) Designing highly reliable fiducial markers, IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(7), 1317-1324.
  • Demuynck O, Menendez J M (2013) Magic Cards: A New Augmented Reality Approach, IEEE Computer Graphics and Applications, 33(1), 12-19.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171424446

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