참고문헌
- Adel, E., Elmogy, M., and Elbakry, H. (2014), Image stitching based on feature extraction techniques - A survey, International Journal of Computer Applications, Vol. 99, No. 6, pp. 1-8. https://doi.org/10.5120/17374-7818
- Aghdasi, H.S., Bisadi, P., Moghaddam, M.E., and Abbaspour, M. (2009), High-resolution images with minimum energy dissipation and maximum field-of-view in camera-based wireless multimedia sensor networks, Sensors, Vol. 9, No. 8, pp. 6385-6410. https://doi.org/10.3390/s90806385
- Alhwarin, F., Wang, C., Durrant, D.R., and Graser, A. (2008), Improved SIFT-features matching for object recognition, Proceedings of BCS International Academic Conference 2008 - Vision of Computer Science, BCS, 22-24 September, London, UK, pp. 179-190.
- Arya, S. (2015), A review on image stitching and its different methods, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 5, pp. 299-303.
- Bay, H., Tuytelaars, T., and Gool, L.V. (2008), Speeded-up robust features (SURF), Computer Vision and Image Understanding, Vol. 110, No. 3, pp. 346-359. https://doi.org/10.1016/j.cviu.2007.09.014
- Besbes, B., Rogozan, A., Rus, A.M., Bensrhair, A., and Broggi, A. (2015), Pedestrian detection in far-infrared daytime images using a hierarchical codebook of SURF, Sensors, Vol. 15, No. 4, pp. 8570-8594. https://doi.org/10.3390/s150408570
- Bheda, D., Joshi, M., and Agrawal, V. (2014), A study on features extraction techniques for images mosaicing, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, No. 3, pp. 3432-3437.
- Fischler, M.A. and Bolles, R.C. (1981), Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, Vol. 24, No. 6, pp. 381-395. https://doi.org/10.1145/358669.358692
- Flir-Systems, (2008), FLIR SC660 R&D Infrared camera system, FLIR Systems, Hong Kong, http://www.flir.com/uploadedFiles/Thermography_APAC/Products/Product_Literture/SC660_Datasheet%20APAC(1).pdf (last date accessed 16 January 2017).
- Hoseini, S.A. and Jafari, S. (2011), An automated method for mosaicking of video frames with projective constraint, International Journal of Science and Advanced Technology, Vol. 1, pp. 112-116.
- Jain, D.K., Saxena, G., and Singh, V.K. (2012), Image mosaicing using corner techniques, Proceedings of International Conference on Communication Systems and Network Technologies, IEEE, 11-13 May, Washington, USA, Vol. 12, pp. 79-84.
- Jia, G., Wang, X., Wang, H.B., and Zhang, Z. (2010), Accuracy analysis of space three line array photogrammetry based on forward intersection, Proceedings of 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE, 20-22 Aug, Chengdu, China, Vol. 1, pp. 391-395.
- Kai, W., Bo, C., and Long, T. (2012), An improved SIFT feature matching algorithm based on maximizing minimum distance cluster, Proceedings of 2011 International Conference on Computer Science and Information Technology, ICCSIT, 10-12 June, Chengdu, China, vol. 51, pp. 255-259.
- Ke, Y. and Sukthankar, R. (2004), PCA-SIFT: A more distinctive representation for local image descriptors, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 27 June - 2 July, Washington DC, USA, Vol. 2, pp. 506-513.
- Lee, W. and Yu, K. (2009), Bundle block adjustment with 3D natural cubic splines, Sensors, Vol. 9, No. 12, pp. 9629-9665. https://doi.org/10.3390/s91209629
- Lingua, A., Marenchino, D., and Nex, F. (2009), Performance analysis of the SIFT operator for automatic feature extraction and matching in photogrammetric applications, Sensors, Vol. 9, No. 5, pp. 3745-3766. https://doi.org/10.3390/s90503745
- Lowe, D.G. (2004), Distinctive image features from scaleinvariant keypoints, International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110. https://doi.org/10.1023/B:VISI.0000029664.99615.94
- Lu, Y., Wang, K., and Fan, G. (2016), Photometric calibration and image stitching for a large field of view multi-camera system, Sensors, Vol. 16, No. 4, 516 p. https://doi.org/10.3390/s16040516
- Luhmann, T., Robson, S., Kyle, S., and Harley, I. (2006), Close Range Photogrammetry Principles, Methods and Applications, Whittles Publishing, Scotland, UK.
- Molnar, B. (2010), Direct linear transformation based photogrammetry software on the web, International Archives of Photogrammetry, Remote Sensing, and Spatial Information Sciences, ISPRS, 21-24 June, Newcastle, UK, Vol. XXXVIII, Part 5, pp. 462-465.
- Pravenaa, S. and Mennaka, R. (2016), A methodical review on image stitching and video stitching techniques, International Journal of Applied Engineering Research, Vol. 11, No. 5, pp. 3442-3448.
- Rosten, E. and Drummond, T. (2006), Machine learning for high-speed corner detection, Proceedings of European Conference on Computer Vision, ECCV, 7-13 May, Graz, Austria, pp. 430-443.
- Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011), ORB: An efficient alternative to SIFT or SURF, Proceedings of 2011 International Conference on Computer Vision, IEEE, 6-13 November, Barcelona, Spain, pp. 2564-2571.
- Sharma, M. (2014), Image mosaicing and producing a panoramic visibility, International Journal on Recent and Innovation Trends Computing and Communation, Vol. 2, No. 2, pp. 198-201.
- Shashank, K., Chaitanya, N.S., Manikanta, G., Balaji, C.N.V., and Murthy, V.V.S.A. (2014), A survey and review over image alignment and stitching methods, International Journal of Electronics & Communication Technology, Vol. 5, No. 3, pp. 50-52.