ПРИНЦИПЫ ОРГАНИЗАЦИИ И АНАЛИЗ ПОДХОДОВ К ПОВЫШЕНИЮ ТОЧНОСТИ ПОВТОРНОЙ ИДЕНТИФИКАЦИИ ЛЮДЕЙ В РАСПРЕДЕЛЕННЫХ СИСТЕМАХ ВИДЕОНАБЛЮДЕНИЯ

##plugins.themes.bootstrap3.article.main##

С. А. ИГНАТЬЕВА

Аннотация

Приведена классификация существующих систем повторной идентификации по таким критериям, как тип системы, количество и вид запросов, время работы. Рассмотрена общая схема, отражающая основной принцип работы систем повторной идентификации, а также основные подходы и методы для решения этой задачи с использованием сверточных нейронных сетей. Выполнено исследование существующих способов повышения точности работы алгоритмов и систем повторной идентификации. Проведен анализ влияния выбора гиперпараметров при обучении сверточных нейронных сетей на эффективность и динамику обучения алгоритма повторной идентификации.

##plugins.themes.bootstrap3.article.details##

Как цитировать
(1)
ИГНАТЬЕВА, С. А. ПРИНЦИПЫ ОРГАНИЗАЦИИ И АНАЛИЗ ПОДХОДОВ К ПОВЫШЕНИЮ ТОЧНОСТИ ПОВТОРНОЙ ИДЕНТИФИКАЦИИ ЛЮДЕЙ В РАСПРЕДЕЛЕННЫХ СИСТЕМАХ ВИДЕОНАБЛЮДЕНИЯ. Вестник Полоцкого государственного университета. Серия С. Фундаментальные науки 2022, 38, 13-25.
Раздел
Информатика, вычислительная техника и управление

Библиографические ссылки

Ye, M., Shen, J., Lin, G., Xiang, T., Shao, L., & Hoi, S.C. (2021). Deep Learning for Person Re-identification: A Survey and Outlook. IEEE transactions on pattern analysis and machine intelligence, PP. DOI: 10.1109/TPAMI.2021.3054775.

Mihaescu, R., Chindea, M., Paleologu, C., Carata, S., & Ghenescu, M. (2020). Person Re-Identification across Data Distributions Based on General Purpose DNN Object Detector. Algorithms, 13(12), 343. DOI:10.3390/a13120343.

Liu, H., Qin, L., Cheng, Z., & Huang, Q. (2013). Set-based classification for person re-identification utilizing mutualinformation. 2013 IEEE International Conference on Image Processing (3078–3082). DOI: 10.1109/ICIP15918.2013.

Huang, Y., Wu, Q., Zhong, Y., & Zhang, Z. (2021). Clothing Status Awareness for Long-Term Person Re-Idenification. 2021 IEEE/CVF International Conference on Computer Vision (11895–11904). DOI: 10.1109/ICCV48922.2021.01168.

Zhang, T., Xie, L., Wei, L., Zhuang, Z., Zhang, Y., Li, B., & Tian, Q. (2021). UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (11501–11510). DOI: 10.1109/CVPR46437.2021.01134.

Lewkowycz, A. (2021). How to decay your learning rate. ArXiv, abs/2103.12682. DOI: 10.48550/arXiv.2103.12682.

Lewkowycz, A., Bahri, Y., Dyer, E., Sohl-Dickstein, J., & Gur-Ari, G. (2020). The large learning rate phase of deep learning: the catapult mechanism. ArXiv, abs/2003.02218. DOI: 10.48550/arXiv.2003.02218.

Lee, S., Kang, Q., Madireddy, S., Balaprakash, P., Agrawal, A., Choudhary, A.N., … Liao, W. (2019). Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time. 2019 IEEE International Conference on Big Data (Big Data) (830–839). DOI: 10.1109/BigData47090.2019.9006550.

Zhao, F., Liao, S., Xie, G., Zhao, J., Zhang, K., & Shao, L. (2020). Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification. ECCV. DOI: 10.1007/978-3-030-58621-8_31.

Luo, C., Song, C., & Zhang, Z. (2020). Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup. ECCV. DOI: 10.1007/978-3-030-58555-6_14.

Jin, X., Lan, C., Zeng, W., Chen, Z., & Zhang, L. (2020). Style Normalization and Restitution for Generalizable Person Re-Identification. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (3140–3149). DOI: 10.1109/cvpr42600.2020.00321.

Song, J., Yang, Y., Song, Y., Xiang, T., & Hospedales, T.M. (2019). Generalizable Person Re-Identification by Domain Invariant Mapping Network. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (719–728). DOI: 10.1109/CVPR.2019.00081.

Ihnatsyeva, S., Bohush, R., & Ablameyko, S. (2021). Joint Dataset for CNN-based Person Re-identification. Pattern Recognition and Information Processing (PRIP'2021) Proceedings of the 15th International Conference (33–37). Minsk: United Institute of Informatics Problems of the National Academy of Sciences of Belarus.

Liao, S., Mo, Z., Hu, Y., & Li, S. (2014). Open-set Person Re-identification. ArXiv, abs/1408.0872. DOI: 10.48550/arXiv.1408.0872.

Li, W., Zhao, R., & Wang, X. (2012). Human Reidentification with Transferred Metric Learning. ACCV. DOI: 10.1007/978-3-642-37331-2_3.

Li, W., & Wang, X. (2013). Locally Aligned Feature Transforms across Views. 2013 IEEE Conference on Computer Vision and Pattern Recognition (3594–3601). DOI: 10.1109/CVPR.2013.461.

Li, W., Zhao, R., Xiao, T., & Wang, X. (2014). DeepReID: Deep Filter Pairing Neural Network for Person Re-identification. 2014 IEEE Conference on Computer Vision and Pattern Recognition (152–159). DOI: 10.1109/CVPR.2014.27.

Wei, L., Zhang, S., Gao, W., & Tian, Q. (2018). Person Transfer GAN to Bridge Domain Gap for Person Re-identification. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (79–88). DOI: 10.1109/CVPR.2018.00016.

Ristani, E., Solera, F., Zou, R.S., Cucchiara, R., & Tomasi, C. (2016). Performance Measures and a Data Set for Multitarget, Multi-camera Tracking. ArXiv, abs/1609.01775. DOI: 10.1007/978-3-319-48881-3_2.

Fabbri, M., Brasó, G., Maugeri, G., Cetintas, O., Gasparini, R., Osep, A., … Cucchiara, R. (2021). MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking? 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (10829–10839). DOI: 10.1109/iccv48922.2021.01067.

Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., & Tian, Q. (2015). Scalable Person Re-identification: A Benchmark. 2015 IEEE International Conference on Computer Vision (ICCV) (1116–1124). DOI: 10.1109/ICCV.2015.133.

Barbosa, I. B., Cristani, M., Caputo, B., Rognhaugen, A., & Theoharis, T. (2018). Looking beyond appearances: Synthetic training data for deep CNNs in re-identification. ArXiv, abs/1701.03153. DOI: 10.1016/j.cviu.2017.12.002.

Bąk, S., Carr, P., & Lalonde, J. (2018). Domain Adaptation through Synthesis for Unsupervised Person Re-identification. ECCV. DOI: 10.1007/978-3-030-01261-8_12.

Sun, X., & Zheng, L. (2019). Dissecting Person Re-Identification From the Viewpoint of Viewpoint. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (608–617). DOI: 10.1109/CVPR.2019.00070.

Wang, Y., Liao, S., & Shao, L. (2020). Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification. Proceedings of the 28th ACM International Conference on Multimedia. DOI: 10.1145/3394171.3413815.

Zhong, Z., Zheng, L., Kang, G., Li, S., & Yang, Y. (2020). Random Erasing Data Augmentation. AAAI. DOI: 10.1609/AAAI.V34I07.7000.

Huang, Y., Zha, Z., Fu, X., Hong, R., & Li, L. (2020). Real-World Person Re-Identification via Degradation Invariance Learning. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (14072–14082). DOI: 10.1109/cvpr42600.2020.01409.

Jiang, Y., Chen, W., Sun, X., Shi, X., Wang, F., & Li, H. (2021). Exploring the Quality of GAN Generated Images for Person Re-Identification. Proceedings of the 29th ACM International Conference on Multimedia. DOI: 10.1145/3474085.3475547.

Wang, G., Lai, J., Huang, P., & Xie, X. (2019). Spatial-Temporal Person Re-identification. ArXiv, abs/1812.03282. DOI: 10.1609/aaai.v33i01.33018933.

Hermans, A., Beyer, L., & Leibe, B. (2017). In Defense of the Triplet Loss for Person Re-Identification. ArXiv, abs/1703.07737. DOI: 10.48550/arXiv.1703.07737.

Organisciak, D., Riachy, C., Aslam, N., & Shum, H. (2019). Triplet Loss with Channel Attention for Person Re-identification. J. WSCG, 27. DOI: 10.24132/JWSCG.2019.27.2.9.

Yang, J., Zhang, J., Yu, F., Jiang, X., Zhang, M., Sun, X., … Zheng, W. S., (2021) Learning to Know Where to See: A Visibility-Aware Approach for Occluded Person Re-identification. Proceedings of the IEEE/CVF International Conference on Computer Vision (11885–11894). DOI: 10.1109/ICCV48922.2021.01167.

Chen, X., Liu, X., Liu, W., Zhang, X., Zhang, Y., & Mei, T. (2021). Explainable Person Re-Identification with Attributeguided Metric Distillation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (11793–11802). DOI: 10.1109/ICCV48922.2021.01160.

Choi, S., Kim, T., Jeong, M., Park, H., & Kim, C. (2021). Meta Batch-Instance Normalization for Generalizable Person Re-Identification. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (3424–3434). DOI: 10.1109/CVPR46437.2021.00343.

Sun, Y., Zheng, L., Yang, Y., Tian, Q., & Wang, S. (2018). Beyond Part Models: Person Retrieval with Refined Part Pooling. ECCV. DOI: 10.1007/978-3-030-01225-0_30.

Ignat'eva, S. A. (2021). Sravnitel'nyj analiz funkcij aktivacii i ih vliyanie na tochnost' re-identifikacii lyudej s ispol'zovaniem svertochnyh nejronnyh setej [Comparative activation functions analysis and their impact on the person re-identification accuracy using convolutional neural networks], Sovremennye problemy matematiki i vychislitel'noj tekhniki [Modern problems of mathematics and computer technology] (44–48). Brest: BrSTU (In Russ.).

Ulyanov, D., Vedaldi, A., & Lempitsky, V. S. (2016). Instance Normalization: The Missing Ingredient for Fast Stylization. ArXiv, abs/1607.08022. DOI: 10.48550/arXiv.1607.08022.

Hao, X., Zhao, S., Ye, M., & Shen, J. (2021). Cross-Modality Person Re-Identification via Modality Confusion and Center Aggregation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (16383–16392). DOI: 10.1109/ICCV48922.2021.0160.

Wang, G., Yang, S., Liu, H., Wang, Z., Yang, Y., Wang, S., … Sun, J. (2020). High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ((6448–6457). DOI: 10.1109/CVPR42600.2020.00648.

Sun, K., Xiao, B., Liu, D., & Wang, J. (2019). Deep High-Resolution Representation Learning for Human Pose Estimation. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (5686–5696). DOI: 10.1109/CVPR.2019.00584.

Fang, H., Xie, S., Tai, Y., & Lu, C. (2017). RMPE: Regional Multi-person Pose Estimation. 2017 IEEE International

Conference on Computer Vision (ICCV) (2353–2362). DOI: 10.1109/ICCV.2017.256.

Zhong, Z., Zheng, L., Cao, D., & Li, S. (2017). Re-ranking Person Re-identification with k-Reciprocal Encoding. 2017

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (3652–3661). DOI: 10.1109/CVPR.2017.389.