Научные интересы: компьютерная графика; цифровая обработка изображений.
1. A. Makovetskii, V. Kober, “Analysis of the gradient descent method in problems of the signals and images restoration,” Pattern Recognition and Image Analysis, January 2015, Volume 25, Issue 1, P. 53-59, 2015. DOI: 10.1134/S1054661815010101 (Indexed in Scopus)
2. Makovetskii A., Voronin S. and Kober V., “Explicit solutions of one-dimensional total variation problem,” Proc. SPIE's 60 Annual Meeting: Applications of Digital Image Processing XXXVIII, Vol. 9599, P. 959926-1, 2015. DOI: 10.1117/12.2187866 (Indexed in WoS, Scopus, Accession Number WOS: 000366385200063)
3. С.М. Воронин, А.Ю. Маковецкий, В.И. Кобер, В.Н. Карнаухов, ”Свойства точных решений задачи регуляризации полной вариации функций одной переменной,” Информационные процессы, Том 15, No 2, стр. 162–168, 2015. (РИНЦ)
4. Voronin S., Makovetskii A., Kober V. and Karnauhov V., ”Properties of exact solutions of the total variation regularization functions of one variable,” Journal of Communications Technology and Electronics, Vol. 60, No. 12, P. 1356–1359, 2015. DOI: 10.1134/S1064226915120207 (Indexed in WoS, Scopus. Impact Factor: 0.36, Accession Number: WOS: 000366638500011)
5. A. Makovetskii, S. Voronin and V. Kober, ”Total variation regularization with bounded linear variations,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX, Vol. 9971, pp. 99712T-9, 2016. DOI: 10.1117/12.2237162(Indexed in WoS, Scopus. Accession Number WOS:000390023100086)
6. D. Tihonkih, A. Makovetskii and V. Kuznetsov, ”A modified iterative closest point algorithm for shape registration,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX, Vol. 9971, pp. 99712D-1, 2016. DOI: 10. 10.1117/12.2237911 (Indexed in WoS, Scopus. Accession Number WOS: 000390023100072)
7. F. Alekseev, M. Alekseev and A. Makovetskii, ”Fast algorithm for calculation of linear variations,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX,Vol. 9971, 99712J-1, 2016. DOI: 10.1117/12.2237730 (Indexed in WoS, Scopus. Accession Number WOS: 000390023100076)
8. Sochenkov, A. Sochenkova, A. Vokhmintsev, A. Makovetskii and A. Melnikov, ”Effective Indexing for Face Recognition,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX, Vol. 9971, 997124-1, 2016. DOI: 10.1117/12.2238096 (Indexed in WoS, Scopus. Accession Number WOS: 000390023100064)
9. Sochenkov, D. Tihonkih, A. Vokhmintsev, A. Melnikov and A. Makovetskii, ”A face recognition algorithm based on thermal and visible data,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX, Vol. 9971, 99713F-1, 2016. DOI: 10.1117/12.2238224 (Indexed in WoS, Scopus. Accession Number WOS: 000390023100103)
10. D. Tihonkih, A. Makovetskii, and V. Kuznetsov, “The iterative closest points algorithm and affine transformations,” Proc. Int. Conference of Analysis of Images, Social Networks, and Texts (AIST 2016), CEUR Workshop Proceedings, P.349-356, 2016. http://ceur-ws.org/Vol-1710/paper35.pdfISSN: 16130073 (Indexed in Scopus)
11. F. Alekseev, M. Alekseev and A. Makovetskii, “Linear Variation and an Optimization of Algorithms for Connected Components Labeling in a Binary Image,” Proc. Int. Conference of Analysis of Images, Social Networks, and Texts (AIST 2016), CEUR Workshop Proceedings, P. 10-20, 2016. http://ceur-ws.org/Vol-1710/paper2.pdfISSN: 16130073 (Indexed in Scopus)
12. Makovetskii A., Voronin S. and Kober V., “An efficient algorithm for total variation denoising,” Proc. Int. Conference of Analysis of Images, Social Networks, and Texts (AIST 2016), CCIS 661, pp. 326–337, 2017. DOI: 10.1007/978-3-319-52920-2_30 (Indexed in WoS, Scopus, Accession Number: WOS:000407059600030)
13. A. Vokhmintsev, M. Timchenko, A. Melnikov, A. Kozko, A. Makovetskii, “Robot path planning algorithm based on symbolic tags in dynamic environment,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962E, 2017. DOI: 10.1117/12.2273279 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700067)
14. Vokhmintcev, T. Botova, I. Sochenkov, A. Sochenkova, A. Makovetskii, “Robot mapping algorithm based on Kalman filtering and symbolic tags,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962I, 2017. DOI: 10.1117/12.2273562 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700070)
15. Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Dmitrii Tihonkih, “An efficient point-to-plane registration algorithm for affine transformations,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962J, 2017. DOI: 10.1117/12.2273604 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700071)
16. Artyom Makovetskii, Sergei Voronin, Vitaly Kober, “A generalized Condat's algorithm of 1D total variation regularization,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962K, 2017. DOI: 10.1117/12.2273618 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700072)
17. A. Sochenkova, I.Sochenkov, A. Makovetskii, A. Vokhmintsev, A. Melnikov, “Convolutional neural networks and face recognition task,” Proceedings Volume 10396, Applications of Digital Image Processing XL, 103962L, 2017. DOI: 10.1117/12.2273624 ( Indexed in WoS, Scopus, Accession Number WOS: 000418443700073)
18. Dmitry Nikolaev, Dmitrii Tihonkih, Artyom Makovetskii, Sergei Voronin, “An efficient direct method for image registration of flat objects,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL,103962U, 2017. DOI: 10.1117/12.2274101 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700081)
19. Dmitrii Tihonkih, Artyom Makovetskii, Aleksei Voronin, “A modified iterative closest point algorithm for noisy data,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962W, 2017. DOI: 10.1117/12.2274139 ( Indexed in WoS, Scopus, Accession Number WOS:000418443700083)
20. Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Dmitrii Tihonkih, “Affine registration of point clouds based on point-to-plane approach,”’ Procedia Engineering, Volume 201, Pages 322-330, 2017. DOI: 10.1016/j.proeng.2017.09.635 ( Indexed in WoS, Scopus, Accession Number WOS: 000426433500041)
21. Artyom Makovetskii, Sergei Voronin, Vitaly Kober, “A fast one dimensional total variation regularization algorithm,” CEUR Workshop Proceedings Volume 1901, Pages 176-179, 2017. ISSN: 16130073. http://ceur-ws.org/Vol-1901/paper28.pdf(Indexed in Scopus)
22. А. Ю. Маковецкий, С. М. Воронин, Д. В. Тихоньких, М. Н. Алексеев, “Точные решения вариационной задачи алгоритма icp в классе аффинных преобразований,” Челябинский физико-математический журнал, Т. 2, вып. 3, С. 282–294, 2017.
23. A. Makovetskii, S. Voronin, V. Kober, D. Tihonkih, “Affine registration of point clouds based on point-to-plane approach,” Cборник трудов III международной конференции «Информационные технологии и нанотехнологии» (ИТНТ-2017), 684-688, 2017. (РИНЦ)
24. A. Makovetskii, S. Voronin, V. Kober, “A fast one dimensional total variation regularization algorithm,” Cборник трудов IIIмеждународной конференции «Информационные технологии и нанотехнологии» (ИТНТ-2017), 689-692, 2017. (РИНЦ)
25. A. Makovetskii, S. Voronin, V. Kober, A. Voronin, “A non-iterative method for approximation of the exact solution to the point-to-plane variational problem for orthogonal transformations,” Mathematical Methods in the Applied Sciences, Volume41, n. 18, P. 9218-9230, 2018. DOI:10.1002/mma.5173 (Indexed in WoS, Scopus, Q2 WoS, Q1 Scopus, Impact factor: 1.18).
26. A. Makovetskii, S. Voronin, V. Kober, A. Voronin, D. Tihonkih, “Point clouds registration based on the point-to-plane approach for orthogonal transformations,” CEUR Workshop Proceedings Volume 2210, Pages 236-242, 2018. ISSN: 1613-0073 http://ceur-ws.org/Vol-2210/paper31.pdf(Indexed in Scopus)
27. A. Makovetskii, S. Voronin, V. Kober, A.Voronin, "A point-to-plane registration algorithm for orthogonal transformations," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522R, 2018. DOI: 10.1117/12.2321396 (Indexed in WoS, Scopus, Accession Number WOS: 000450861700092)
28. D. Tihonkih, A. Voronin, A. Makovetskii, J. Diaz-Escobar, "Reducing number of points for ICP algorithm based on geometrical properties," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522P, 2018. DOI: 10.1117/12.2321282 (Indexed in WoS, Scopus, Accession Number WOS: 000450861700090)
29. S. Voronin, V. Kober, A. Makovetskii, "Image dehazing usingtotal variation regularization," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522T, 2018. DOI: 10.1117/12.2321636 (Indexed in WoS, Scopus, Accession Number WOS:000450861700094)
30. S. Leonov, A. Vasilyev, A. Makovetskii, V.Kuznetsov, J. Diaz-Escobar, "An algorithm for selecting face features usingdeep learning techniques based on autoencoders," Proc. SPIE 10752,Applications of Digital Image Processing XLI, 107522M,2018.DOI: 10.1117/12.2321068(Indexed in WoS, Scopus, Accession Number WOS:000450861700087)
31. S. Leonov, A. Vasilyev, A. Makovetskii, J. Diaz-Escobar,"An algorithm of face recognition based on generative adversarial networks,"Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522L,2018. DOI: 10.1117/12.2321039(Indexed in WoS, Scopus, Accession Number WOS:000450861700086)
32. S. Voronin, A. Makovetskii, A. Voronin, J. Diaz-Escobar, "Aregularization algorithm for registration of deformable surfaces," Proc. SPIE10752, Applications of Digital Image Processing XLI, 107522S, 2018. DOI: 10.1117/12.2321521(Indexed in WoS, Scopus, Accession Number WOS:000450861700093)
33. A. Makovetskii, S. Voronin, V. Kober, "An efficient algorithm of3D total variation regularization," Proc. SPIE 10752, Applications of DigitalImage Processing XLI, 107522V,2018. DOI:10.1117/12.2321646 (Indexed in WoS, Scopus, Accession Number WOS:000450861700096)
34. A. Vokhmintsev,M. Timchenko, T. Botova, K. Mironov, A. Makovetskii, A.Kober, "Development of a method for constructing a 3D accurate map of thesurrounding environment ," Proc. SPIE 10752, Applications of Digital ImageProcessing XLI, 107521X,2018. DOI: 10.1117/12.2320194(Indexed in WoS, Scopus, Accession Number WOS:000450861700063)
35. A. Vokhmintcev, A. Melnikov, M. Timchenko, A. Kozko, A. Makovetskii, A.Kober, "Development of methods for selecting features using deep learning techniques based on auto encoders," Proc.SPIE 10752, Applications of DigitalImage Processing XLI, 1075227,2018. DOI: 10.1117/12.2320189(Indexed in WoS, Scopus, Accession Number WOS:000450861700073)
36. A. Makovetskii, S. Voronin, V. Kober, “A fast total variation regularization algorithm for 2D piecewise constant radially symmetric functions,” Journal of Physics: Conference Series,Volume 1096, n. 1, 012041, 2018. DOI: 10.1088/1742-6596/1096/1/012041 (Indexed in Scopus)
37. A. Makovetskii, S. Voronin, V. Kober, A. Voronin, D. Tihonkih, “Approximation of the exact solution of point clouds registration based on point-to-plane approach for orthogonal transformations,” Proc. ITNT-2018 (Сборник Трудов ИТНТ-2018, IV международная конференция и молодежная школа «Информационные технологии и нанотехнологии»), P.939-945, 2018. ISBN: 978-5-88940-146-9 (Indexed in RINC)
38. A. Makovetskii, S. Voronin, V. Kober, “A fast total variation regularization algorithm for 2d piecewise constant radially symmetric functions,” Proc. ITNT-2018 (Сборник Трудов ИТНТ-2018, IV международная конференция и молодежная школа «Информационные технологии и нанотехнологии»), P. 930-938, 2018. ISBN: 978-5-88940-146-9 (Indexed in RINC)
39. Sergey S. Leonov, Alexander N. Vasilyev, Artyom Makovetskii, “Analysis of the convolutional neural network architectures in image classification problems,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372E, 2019. DOI: 10.1117/12.2529232 (Indexed in WoS, Scopus)
40. Dmitrii Tihonkih, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin “An efficient 3D mapping framework,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372L,2019. DOI: 10.1117/12.2529632 (Indexed in WoS, Scopus)
41. Sergei Voronin, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin, “Image dehazing using spatially displaced images,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372M,2019. DOI: 10.1117/12.2529684 (Indexed in WoS, Scopus)
42. Sergei Voronin, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin, “Non-rigid ICP and 3D facial models,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372K,2019. DOI: 10.1117/12.2529525 (Indexed in WoS, Scopus)
43. Artyom Makovetskii,Sergei Voronin, Vitaly Kober, Aleksei Voronin, “A Generalized Point-to-Point Approach for Orthogonal Transformations,”CCIS, volume 1090,pp. 217-231,2019.DOI: 10.1007/978-3-030-33394-2_17 (Indexed in WoS, Scopus)
44. Dmitrii Tihonkih, Artyom Makovetskii, Vitaly Kober, Aleksei Voronin, “Preliminary ICP stage for data-thinning based on object geometry,” Journal of Physics: Conference Series, Volume 1368, 032010,2019. DOI: 10.1088/1742-6596/1368/3/032010 (Indexed in Scopus)
45. КоберВ.И., Маковецкий А.Ю., Воронин С.М., Карнаухов В.Н., “Быстрый алгоритм регуляризации полной вариации для класса радиально-симметричных функций,” Информационные процессы, Т. 19,No 1,С. 33-46,2019. (Indexed inRINC)
46. V. I. Kober, ,A. Yu. Makovetskii, S. M. Voronin, and V. N. Karnaukhov, “A Fast Algorithm of Regularization of the Total Variation for the Class of Radially Symmetrical Functions,”Journal of Communications Technology and Electronics, Vol. 64, No. 12, pp. 1500–1507,2019.DOI: 10.1134/S1064226919120064 (Indexed in WoS, Scopus,Q2 Scopus)
47. A. Makovetskii, S. Voronin, V. Kober, A.Voronin, “A regularized point cloud registration approach for orthogonal transformations,” Journal of Global Optimization, 2020. DOI: 10.1007/s10898-020-00934-8 (Indexed in WoS, Scopus, Q1 WoS, Q1 Scopus, Impact factor 1.805)
48. A. Makovetskii, S. Voronin, V. Kober, A.Voronin, “Tube-based taut string algorithms for total variation regularization,” Mathematics, Volume 8, Issue 7, 1141, 2020. DOI: 10.3390/math8071141 (Indexed in WoS, Scopus, Q1 WoS, Q1 Scopus, Impact factor 1.74)
49. A. Makovetskii, S. Voronin, V. Kober, A.Voronin, “An efficient algorithm for non-rigid object registration,” Computer Optics, Volume 44, Issue 1, , pp. 67-73, 2020. DOI: 10.18287/2412-6179-CO-586 (Indexed in WoS, Scopus, Q1 Scopus)
50. Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, "An efficient algorithm of total variation regularization in the two-dimensional case," Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115102Y (21 August 2020), 2020. DOI: 10.1117/12.2568954 (Indexed in WoS, Scopus)
51
. Sergei Voronin, Artyom Makovetskii, Aleksei Voronin, Dmitrii Zhernov, "Neural network and non-rigid ICP in facial recognition problem," Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115102Z (21 August 2020), 2020. DOI: 10.1117/12.2568961 (Indexed in WoS, Scopus)
52. Sergei Voronin, Artyom Makovetskii, Vitaly Kober, Aleksei Voronin, Tatyana Makovetskaya, "Image dehazing based on microscanning approach," Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115102X (21 August 2020), 2020. DOI: 10.1117/12.2568946 (Indexed in WoS, Scopus)
53. Makovetskii A., Kober V., Voronin A., Zhernov D., “Facial recognition and 3d non-rigid registration,” ИТНТ-2020, Сборник трудов по материалам VI Международной конференции, 656-660, 2020. (Indexed in RINC)
54. Makovetskii A., Voronin S., Kober V., Voronin A., “An algorithm for rough alignment of point clouds in threedimensional space,” ИТНТ-2020, Сборник трудов по материалам VI Международной конференции, 652-655, 2020. (Indexed in RINC)
55. A. Makovetskii, S. Voronin, V. Kober and A. Voronin, "An algorithm for rough alignment of point clouds in three-dimensional space," 2020 International Conference on Information Technology and Nanotechnology (ITNT), Samara, Russia, IEEE Proceedings, pp. 1-4, 2020. DOI: 10.1109/ITNT49337.2020.9253338 (Indexed in WoS, Scopus)
56. A. Makovetskii, V. Kober, A. Voronin and D. Zhernov, "Facial recognition and 3D non-rigid registration," 2020 International Conference on Information Technology and Nanotechnology (ITNT), Samara, Russia, IEEE Proceedings, pp. 1-4, 2020. DOI: 10.1109/ITNT49337.2020.9253224 (Indexed in WoS, Scopus)
Участник грантов (руководитель)
1. Грант РФФИ № 18-07-00963 «Разработка точных методов и алгоритмов для решения задачи построения моделей поверхностей в трехмерном пространстве», 2018-2020.
2. Грант РФФИ № 20-47-740007\20 «Разработка новых алгоритмов построения динамической, трехмерной карты для функционирования мобильных роботов в неизвестной окружающей среде», 2021.
3. Грант РНФ № 21-11-00095 «Анализ и разработка высокоточных методов реконструкции трехмерной окружающей среды: алгоритмы классического типа и нейросетевые алгоритмы».
Участник грантов (исполнитель):
1. Грант РФФИ № 13-01-00735 «Топологические методы фильтрации и восстановления изображений», 2013-2015.
2. Грант Министерства образования и науки РФ в рамках реализации государственного задания в сфере научной деятельности № 2.1766.2014К «Разработка адаптивных методов для надежного слежения за трехмерными объектами», 2014-2016.
3. Грант РНФ № 15-19-10010 «Разработка алгоритмической модели технической системы для идентификации личности по мультисенсорным биометрическим данным», 2015-2017.
4. Грант Министерства образования и науки РФ в рамках научных проектов, выполняемых научными коллективами исследовательских центров и (или) научных лабораторий образовательных организаций высшего образования № 1743.2017/ПЧ «Разработка адаптивных методов трехмерной реконструкции окружающего пространства по динамическим мультисенсорным данным», 2017-2019.
5. Грант РФФИ № 18-08-00782 «Разработка алгоритмической модели технической системы для восстановления изображений, искаженных атмосферными явлениями», 2018-2020.
6. Грант РНФ № 15-19-10010/П «Разработка алгоритмической модели технической системы для идентификации личности по мультисенсорным биометрическим данным», 2018-2019.
