Интеллектуальный видеоанализ опасных ситуаций
https://doi.org/10.30932/1992-3252-2017-15-6-18
- Р Р‡.МессенРТвЂВВВВВВВВжер
- РћРТвЂВВВВВВВВнокласснРСвЂВВВВВВВВРєРСвЂВВВВВВВВ
- LiveJournal
- Telegram
- ВКонтакте
- РЎРєРѕРїРСвЂВВВВВВВВровать ссылку
Полный текст:
Аннотация
Об авторах
Л. Н. АнищенкоРоссия
С. И. Ивашов
Россия
А. В. Скребков
Россия
Список литературы
1. Advances Recognition Systems: Rapid-Access Biometric and Credential Solution, NeoFace Express [Электронный ресурс] / Офиц. сайт корпорации NEC, 2017.URL: https://www.necam.com docs/?id=6c812b4d-2a12-40ed-9fea-fae81550c7aa (Доступ 05.11.2017).
2. SMARTGLASSES7 [Электронный ресурс] / Офиц. сайт компании ODG, 2017.URL: https://www.osterhoutgroup.com/pub/static/version1515417478 frontend/Infortis/ultimo/en_US/pdf/R-7-TechSheet.pdf (Доступ 05.11.2017).
3. Yaniv Taigman, Ming Yang, Marc’Aurelio Ranzato, Lior Wolf.«DeepFace: Closing the Gap to Human-Level Performance in Face Verification», Conference on Computer Vision and Pattern Recognition (CVPR), June 24, 2014.
4. Parkhi [et al].Deep Face Recognition [Электронный ресурс]: URL: https://www.robots.ox.ac.uk/~vgg publications/2015/Parkhi15/parkhi15.pdf (Доступ 05.11.2017).
5. Mohammadian A., Aghaeinia H., Towhidkhah F. Video-based facial expression recognition by removing the style variations in Image Processing, IET, 2015, vol.9, No.7, pp.596-603.
6. Iosifidis A., Tefas A., Pitas I. Class-specific Reference Discriminant Analysis with application in Human Behavior Analysis, IEEE Transactions on Human-Machine Systems, 2015, vol.45, no.3, pp.315- 326.
7. Maddalena L., Petrosino A. Stopped Object Detection by Learning Foreground Model in Videos, in IEEE Transactions on Neural Networks and Learning Systems, May 2013, vol.24, no.5, pp.723-735.
8. Amrutha M. P., Vince Paul.Study of Different Obstacle Detection Methods in Railway Track, International Journal of Innovative Research in Computer and Communication Engineering, Jan 2017, vol.5, No.1, pp.1204-1208.
9. Filonenko A., Hernández D. C., Jo K. H. Real-time smoke detection for surveillance, 2015, IEEE13th International Conference on Industrial Informatics (INDIN), Cambridge, 2015, pp.568-571.
10. Rougier C., Meunier J., St-Arnaud A., Rousseau J. Fall detection from human shape and motion history using video surveillance, Proc.21st Int. Conf. AINAW, 2007, vol.2, pp.875-880.
11. Lee T., Mihailidis A. An intelligent emergency response system: Preliminary development and testing of automated fall detection, J. Telemed. Telecare, 2005, vol.11, no.4, pp.194-198.
12. Charfi I., Miteran J., Dubois J., Atri M., Tourki R. Optimised spatio-temporal descriptors for real-time fall detection: comparison of SVM and Adaboost based classification, Journal of Electronic Imaging (JEI), Vol.22.Iss.4, pp.17, October 2013.
13. MathWork Documentation: Create Kalman filter for object tracking [Электронный ресурс] / Офиц. сайт MathWorks, 1994-2017.URL: https://www.mathworks.com/help/vision/ref/configurekalmanfilter.html (Доступ 05.11.2017).
14. Mori G., Malik J. Estimating human body configurations using shape context matching, in Proc. Eur. Conf. Comput. Vision, 2002, vol.2352, pp.150-180.
15. Rougier C., Meunier J., St-Arnaud A., Rousseau J. Robust Video Surveillance for Fall Detection Based on Human Shape Deformation, in IEEE Transactions on Circuits and Systems for Video Technology, May 2011, vol.21, no.5, pp.611-622.
Рецензия
Для цитирования:
Анищенко Л.Н., Ивашов С.И., Скребков А.В. Интеллектуальный видеоанализ опасных ситуаций. Мир транспорта. 2017;15(6):182-193. https://doi.org/10.30932/1992-3252-2017-15-6-18
For citation:
Anishchenko L.N., Ivashov S.I., Skrebkov A.V. INTELLIGENT VIDEO ANALYSIS OF DANGEROUS SITUATIONS. World of Transport and Transportation. 2017;15(6):182-193. https://doi.org/10.30932/1992-3252-2017-15-6-18