Browse > Article
http://dx.doi.org/10.5909/JBE.2019.24.6.992

Moving Object Preserving Seamline Estimation  

Gwak, Moonsung (Ulsan Institute of Science and Technology, UNIST)
Lee, Chanhyuk (Ulsan Institute of Science and Technology, UNIST)
Lee, HeeKyung (Electronics and Telecommunications Research Institute, ETRI)
Cheong, Won-Sik (Electronics and Telecommunications Research Institute, ETRI)
Yang, Seungjoon (Ulsan Institute of Science and Technology, UNIST)
Publication Information
Journal of Broadcast Engineering / v.24, no.6, 2019 , pp. 992-1001 More about this Journal
Abstract
In many applications, images acquired from multiple cameras are stitched to form an image with a wide viewing angle. We propose a method of estimating a seam line using motion information to stitch multiple images without distortion of the moving object. Existing seam estimation techniques usually utilize an energy function based on image gradient information and parallax. In this paper, we propose a seam estimation technique that prevents distortion of moving object by adding temporal motion information, which is calculated from the gradient information of each frame. We also propose a measure to quantify the distortion level of stitched images and to verify the performance differences between the existing and proposed methods.
Keywords
image stitching; moving object; seam estimation; distortion quantitative measurement; temporal motion information;
Citations & Related Records
연도 인용수 순위
  • Reference
1 L. Juan and O. Gwun, "SURF applied in panorama image stitching", IEEE 2010 2nd international conference on image processing theory, tools and applications, p. 495-499, July, 2010.
2 Y. Li, Y. Wang, W. Huang and Z. Zhang, "Automatic image stitching using SIFT", IEEE 2008 International Conference on Audio, Language and Image Processing, pp. 568-571, July, 2008.
3 W. Y. Lin, S. Liu, Y. Matsushita, T. T. Ng and L. F. Cheong, "Smoothly varying affine stitching", IEEE Conference on Computer Vision and Pattern Recognition 2011, pp. 345-352, June, 2011.
4 C.H. Chang, Y. Sato, and Y.Y. Chuang, "Shape-preserving half-projective warps for image stitching", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3254-3261, 2014.
5 J. Zaragoza, T. J. Julio, M.S. Brown and D. Suter, "As-projective-as-possible image stitching with moving DLT", Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2339-2346, 2013.
6 S. Avidan and A. Shamir, "Seam carving for content-aware image resizing", ACM Transactions on graphics (TOG), Vol. 26, No. 3, p. 10, 2007.   DOI
7 S. Goferman, L. Zelinik-Manor, and A. Tal, "Context-aware saliency detection", IEEE transactions on pattern analysis and machine intelligence, Vol. 34, No. 10, pp. 1915-1926, 2011.   DOI
8 B. He and S. Yu, "Parallax-robust surveillance video stitching", Sensors, Vol. 15, No. 7, 2015.
9 J. Gao, Y. Li, T. J. Chin and M. S. Brown, "Seam-Driven Image Stitching", In Eurographics (Short Papers), pp. 45-48, May, 2013.
10 C. Herrmann C. Wang, R. Strong Bowen, E. Keyder and R. Zabih, "Object-centered image stitching", Proceedings of the European Conference on Computer Vision (ECCV), pp. 821-835, 2018.
11 N. Li, T. Liao and C. Wang, "Perception-based seam cutting for image stitching", Signal, Image and Video Processing, Vol 12, No. 5, p967-974, 2018.   DOI