350 rub
Journal Biomedical Radioelectronics №4 for 2024 г.
Article in number:
A software package for the investigation of spatio-temporal feature descriptors
Type of article: scientific article
DOI: https://doi.org/10.18127/j15604136-202404-07
UDC: 615.47:004.93.1
Authors:

O.V. Melnik1, V.A. Sablina2, A.D. Chernenko3

1–3 FSBEI HE Ryazan State Radio Engineering University named after V.F. Utkin (Ryazan, Russia)

1 omela111@yandex.ru, 2 sablina.v.a@evm.rsreu.ru, 3 anuta201294@yandex.ru

Abstract:

At present time researchers investigate approaches to the automatic facial micro-expression analysis to implement the possibility of the recognition of true human emotions from the image sequence of his face. The modern technologies are based on the use of complex mathematical algorithms with many adjusted parameters; in particular, such algorithms are the algorithms of spatio-temporal feature descriptors. The scientists who are not technical specialists, e.g., psychologists or psychotherapists, when investigating these algorithms may encounter difficulties in writing the program code. Therefore, it became necessary to develop a special software package for the investigation of spatio-temporal feature descriptors.

Aim of the work is development of a special software package for studying various spatial and temporal descriptors of facial micromovement features in video images

A software package for the investigation of spatio-temporal feature descriptors with a graphical interface is developed. The software package makes it possible to investigate the influence of the selection of the descriptor (LBP-TOP, FHOOF or FHOFO) and its parameters on the micro-facial movement detection accuracy for different input datasets of human face image sequences.

The developed software package for the investigation of spatio-temporal feature descriptors can be applied as a software tool for carrying out investigations in the facial micro-expression analysis field.

Pages: 48-55
For citation

Melnik O.V., Sablina V.A., Chernenko A.D. A software package for the investigation of spatio-temporal feature descriptors. Biomedicine Radioengineering. 2024. V. 27. № 4. Р. 48-55. DOI: https://doi.org/10.18127/j15604136-202404-07 (In Russian).

References
  1. Zhao G., Li X., Li Y., Pietikäinen M. Facial Micro-Expressions: An Overview. Proceedings of the IEEE. 2023. V. 111. № 10. P. 1215–1235.
  2. Paul Ekman. Emotion in the Human Face, 2nd Edition. Malor Books. 2013. 456 p.
  3. Nikiforov M.B., Sablina V.A., Chernenko A.D. Primeneniye algoritmov prostranstvenno-vremennykh deskriptorov priznakov dlya analiza mikrovyrazheniy litsa. 78-ya Nauchno-tekhnicheskaya konferentsiya Sankt-Peterburgskogo NTO RES im. A.S. Popova. posvyashchennaya Dnyu radio: Sb. materialov. SPb.: SPbGETU «LETI». 2023. S. 365–370. (in Russian).
  4. Burresi G., Sablina V.A. Micro-Facial Movement Detection Using LBP-TOP Descriptors for Landmark Based Regions, 10th Mediterranean Conference on Embedded Computing (MECO) Proceedings. Budva, Montenegro. 2021. P. 401–404.
  5. Sablina V.A. Tekhnologiya obnaruzheniya mikrolitsevykh dvizheniy dlya vyyavleniya istinnykh emotsiy cheloveka. Biotekhnicheskiye. meditsinskiye i ekologicheskiye sistemy. izmeritelnyye ustroystva i robototekhnicheskiye kompleksy «Biomedsistemy – 2022»: Sb. trudov XXXV Vseros. nauch.-tekhn. konf. studentov. molodykh uchenykh i spetsialistov. Ryazan: IP Konyakhin A.V. (Book Jet). 2022. S. 11–17. (in Russian).
  6. Davison A.K., Lansley C., Costen N., Tan K., Moi Hoon Yap. SAMM: A Spontaneous Micro-Facial Movement Dataset. in IEEE Transactions on Affective Computing. 2018. V. 9. № 1. P. 116–129.
  7. Sablina V.A., Chernenko A.D. Raspoznavaniye vyrazheniy litsa s pomoshchyu deskriptora lokalnykh binarnykh shablonov po trem ortogonalnym ploskostyam. Biotekhnicheskiye. meditsinskiye i ekologicheskiye sistemy. izmeritelnyye ustroystva i robototekhnicheskiye kompleksy «Biomedsistemy – 2021»: Sb. trudov XXXV Vseros. nauch.-tekhn. konf. studentov. molodykh uchenykh i spetsialistov. 2021. S. 287–290. (in Russian).
  8. Melnik O.V., Sablina V.A., Chernenko A.D. Primeneniye deskriptora priznakov FHOOF dlya obnaruzheniya mikrolitsevykh dvizheniy. Biomeditsinskaya radioelektronika. 2023. T. 26. № 3. S. 61–70. (in Russian).
  9. Melnik O.V., Nikiforov M.B., Sablina V.A., Chernenko A.D. Obnaruzheniye mikrolitsevykh dvizheniy s pomoshchyu prostranstvenno-vremenny?kh deskriptorov na osnove opticheskogo potoka. Biomeditsinskaya radioelektronika. 2024. T. 27. № 2. S. 60–68. (in Russian).
  10. Hong X., Xu Y., Zhao G. LBP-TOP: A Tensor Unfolding Revisit, in ACCV 2016. Lecture Notes in Computer Science 2017. V. 10116. P. 513–527.
  11. Happy S.L., Routray A. Fuzzy Histogram of Optical Flow Orientations for Micro-Expression Recognition. IEEE Transactions on Affective Computing. 2017. V. 10. № 3. P. 394–406.
Date of receipt: 22.05.2024
Approved after review: 20.06.2024
Accepted for publication: 22.07.2024