References
- 1. Ali, A. T. and Dagless, E. L. (1992) A parallel processing model for real-time computer vision-aided road traffic monitoring, Parallel Processing Letters, 2, 257–264.10.1142/S0129626492000398
- 2. Allgeuer, P. and Behnke, S. (2018) Fused Angles and the Deficiencies of Euler Angles. In: IEEE International Conference on Intelligent Robots and Systems. doi: 10.1109/IROS.2018.8593384.10.1109/IROS.2018.8593384
- 3. Andrei, C. (2006) 3D affine coordinate transformations, Geometria.
- 4. Anitha, J. J. and Deepa, S. M. (2014) Tracking and Recognition of Objects using SURF Descriptor and Harris Corner Detection, International Journal of Current Engineering and Technology, 4(2), 775–778.
- 5. Baetslé, P.-L. (1966) Conformal transformations in three dimensions, Photogrammetric engineering and remote sensing.
- 6. Banachowicz, A. et al. (2008) Badania dostępności systemu DGPS na dolnej Odrze, Czasopismo Techniczne Politechniki Krakowskiej.
- 7. Brazeal, R. (2013) Three dimensional coordinate transformations for registering terrestrial laser scanning datasets based on tie points, (SUR 6905-Point Cloud Analysis). doi: 10.13140/2.1.1993.9204.
- 8. Brazetti, L. and Scaioni, M. (2009) Automatic orientation of image sequences for 3D object reconstruction: first results of a method integrating photogrammetric and computer vision algorithms, International Archives of Photogrammetry, Remote Sensing, XXXVIII(5/W1).
- 9. Cao, X. et al. (2020) Ship recognition method combined with image segmentation and deep learning feature extraction in video surveillance, Multimedia Tools and Applications. Springer, 79(13–14), 9177–9192. doi: 10.1007/s11042-018-7138-3.10.1007/s11042-018-7138-3
- 10. Chen, Y., Shen, Y. and Liu, D. (2004) Simplified model of three dimensional-datum transformation adapted to big rotation angle, Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University.
- 11. Colomina, I. and Molina, P. (2014) Unmanned aerial systems for photogrammetry and remote sensing : A review, ISPRS Journal of Photogrammetry and Remote Sensing. International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS), 92, 79–97. doi: 10.1016/j.isprsjprs.2014.02.013.10.1016/j.isprsjprs.2014.02.013
- 12. Deakin, R. (2006) A note on the Bursa-Wolf and Molodensky-Badekas transformations, (May 2006), 1–21.
- 13. Deakin, R. E. (1998) 3-D coordinate transformations, Surveying and Land Information Systems. doi: 10.1201/9781315108858-16.10.1201/9781315108858-16
- 14. Dickinson, K. W. and Waterfall, R. C. (1984) Video image processing for monitoring road traffic. In: IEE Conference Publication, 105–109.
- 15. Diebel, J. (2006) Representing attitude: Euler angles, unit quaternions, and rotation vectors, Matrix. doi: 10.1093/jxb/erm298.10.1093/jxb/erm29818182420
- 16. El-Ashmawy, K. L. A. (2015) A comparison between analytical aerial photogrammetry, laser scanning, total station and global positioning system surveys for generation of digital terrain model, Geocarto International. doi: 10.1080/10106049.2014.883438.10.1080/10106049.2014.883438
- 17. Europe, E. C. for and COMMITTEE, I. T. (2005) Guidelines and recommendations for river information services. Geneva.
- 18. European Commisin (2007) Rozporządzenie Komisji Wspólnoty Europejskiej. Poland.
- 19. Frost, D. and Tapamo, J. (2013) Detection and tracking of moving objects in a maritime environment using level set with shape priors, EURASIP Journal on Image Video Processing, 1–16.10.1186/1687-5281-2013-42
- 20. Grewal, M. S., Weill, L. R. and Andrews, A. P. (2006) Global Positioning Systems, Inertial Navigation, and Integration, Second Edition, Global Positioning Systems, Inertial Navigation, and Integration, Second Edition. doi: 10.1002/9780470099728.
- 21. Huang, J. and You, S. (2012) Point cloud matching based on 3D self-similarity. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. doi: 10.1109/CVPRW.2012.6238913.10.1109/CVPRW.2012.6238913
- 22. Jue, L. (2008) Research on close-range photogrammetry with big rotation angle, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII(Part B6b), 11–14.
- 23. Kandil, H. and Atwan, A. (2012) A Comparative Study between SIFT- Particle and SURF-Particle Video Tracking Algorithms, International Journal of Signal Processing, Image Processing and Pattern Recognition, 5(3), 111–122.
- 24. Kolecki, J. et al. (2020) Calibration of industrial cameras for aerial photogrammetric mapping, Remote Sensing. doi: 10.3390/RS12193130.10.3390/rs12193130
- 25. Kujawski, A. (2015) Inland waterway vessels tracking using Closed Circuit Television Video, Scientific Journals of the Maritime University of Szczecin, 44(116), 135–140.
- 26. Kujawski, A. and Stępień, G. (2017) A method of determining inland vessel position using a single stationary, non-metric camera, Scientific Journals of the Maritime University of Szczecin, 52(124), 103–111. doi: 10.17402/251.
- 27. Li, R., Liu, C. and School, F. N. (2013) An Object Tracking Algorithm Based on Global SURF Feature, Journal of Information and Computational Science, 10(7), 2159–2167. doi: 10.12733/jics20101694.10.12733/jics20101694
- 28. Luhmann, T. et al. (2014) Close-range photogrammetry and 3D imaging. 2nd edn. Berlin/Boston: Walter de Gruyter.10.1515/9783110302783
- 29. Maddalena, L. and Petrosino, A. (2008) A self-organizing approach to background subtraction for visual surveillance applications, IEEE Transactions on Image Processing, 17(7), 1168–1177.10.1109/TIP.2008.92428518586624
- 30. Mataija, M., Pogarčić, M. and Pogarčić, I. (2014) Helmert Transformation of Reference Coordinating Systems for Geodesic Purposes in Local Frames, Procedia Engineering. Elsevier B.V., 69, 168–176. doi: 10.1016/j.proeng.2014.02.217.10.1016/j.proeng.2014.02.217
- 31. Matthies, L., Kanade, T. and Szeliski, R. (1989) Kalman filter-based algorithms for estimating depth from image sequences, International Journal of Computer Vision, 3, 209–238. doi: 10.1007/BF00133032.10.1007/BF00133032
- 32. Moreira, R. D. S. et al. (2014) A survey on video detection and tracking of maritime vessels, IJRRAS, 20(July), 37–50.
- 33. Nie, X., Yang, M. and Liu, R. W. (2019) Deep Neural Network-Based Robust Ship Detection Under Different Weather Conditions, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. IEEE, 47–52. doi: 10.1109/ITSC.2019.8917475.10.1109/ITSC.2019.8917475
- 34. Pamuła, W. (2014) Detection of vehicles in a video stream using spatial frequency domain features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).10.1007/978-3-319-11331-9_59
- 35. Parliament, T. H. E. E. et al. (2005) Directive 2005/44/EC of the European Parliament and of the Council of 7 september 2005, Official Journal of the European Union, 2005(1882), 12–25.
- 36. Ruffhead, A. C. (2020) Equivalence properties of 3D conformal transformations and their application to reverse transformations, Survey Review. doi: 10.1080/00396265.2019.1708604.10.1080/00396265.2019.1708604
- 37. Sawhney, H. S. (1994) 3D geometry from planar parallax. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. doi: 10.1109/cvpr.1994.323927.10.1109/CVPR.1994.323927
- 38. Seedahmed, G. and Habib, A. (2002) Linear recovery of the exterior orientation parameters in a planar object space, (The Ohio State University).
- 39. Späth, H. (2004) A Numerical Method for Determining the Spatial HELMERT Transformation in the Case of Different Scale Factors, Fachbeiträge, 4(6), 255–257.
- 40. Specht, C., Specht, M. and Dąbrowski, P. S. (2019) Polish DGPS system: 1995-2018 – studies of reference station operating zones, TransNav, 13(3), 581–586. doi: 10.12716/1001.13.03.13.10.12716/1001.13.03.13
- 41. Stępień, G. (2018) Method of the Determination of Exterior Orientation of Sensors in Hilbert Type Space, Sensors, 18(3), 891. doi: 10.3390/s18030891.10.3390/s18030891587712529562598
- 42. Stępień, G. et al. (2020) Dimensioning method of floating offshore objects by means of quasi-similarity transformation with reduced tolerance errors, Sensors (Switzerland). doi: 10.3390/s20226497.10.3390/s20226497770904333203050
- 43. Titterton, D. and Weston, J. (2004) Strapdown inertial navigation technology, Second Edition, The Institution of Electronical Engineers, Reston USA.10.1049/PBRA017E
- 44. Wang, N., Wang, Y. and Er, M. J. (2020) Review on deep learning techniques for marine object recognition: Architectures and algorithms, Control Engineering Practice. Elsevier Ltd, (December 2019), 104458. doi: 10.1016/j.conengprac.2020.104458.10.1016/j.conengprac.2020.104458
- 45. Wawrzyniak, N., Hyla, T. and Popik, A. (2019) Vessel Detection and Tracking Method Based on Video Surveillance, Sensors, 19(5230), 1–14.
- 46. Wawrzyniak, N. and Stateczny, A. (2018) Automatic watercraft recognition and identification on water areas covered by video monitoring as extension for sea and river traffic supervision systems, Polish Maritime Research, 25(97), 5–13.10.2478/pomr-2018-0016
- 47. Wigan, M. R. and Cullinan, M. (1984) MACHINE VISION AND ROAD RESEARCH: NEW TASKS, OLD PROBLEMS. In: Proceedings - Conference of the Australian Road Research Board.
- 48. Wigan, M R and Cullinan, M. C. (1984) Digital image processing: an applications review for road research applications. In: Australasian Conference on Computer Graphics, 2nd, 1984, Melbourne, Australia (AusGraph).
- 49. Wisniewski, B., Bruniecki, K. and Moszynski, M. (2013) Evaluation of RTKLIB’s Positioning Accuracy Using low-cost GNSS Receiver and ASG-EUPOS, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 7(2), 79–85. doi: 10.12716/1001.07.01.10.10.12716/1001.07.01.10
- 50. Zhang, D. (2010) Exploitation of photogrammetry measurement system, Optical Engineering. doi: 10.1117/1.3364057.10.1117/1.3364057
- 51. Zhou, S. et al. (2021) Integrating computer vision and traffic modeling for near-real-time signal timing optimization of multiple intersections, Sustainable Cities and Society. Elsevier Ltd, 68(September 2020), 102775.