{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T13:54:11Z","timestamp":1775742851024,"version":"3.50.1"},"publisher-location":"Cham","reference-count":98,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030801281","type":"print"},{"value":"9783030801298","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-80129-8_53","type":"book-chapter","created":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T09:04:22Z","timestamp":1625475862000},"page":"784-803","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Towards Automated Surveillance: A Review of Intelligent Video Surveillance"],"prefix":"10.1007","author":[{"given":"Romas","family":"Vijeikis","sequence":"first","affiliation":[]},{"given":"Vidas","family":"Raudonis","sequence":"additional","affiliation":[]},{"given":"Gintaras","family":"Dervinis","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"53_CR1","doi-asserted-by":"crossref","unstructured":"Chen, N., Chen, Y., Blasch, E., Ling, H., You, Y., Ye, X.: Enabling smart urban surveillance at the edge. IEEE (2017)","DOI":"10.1109\/SmartCloud.2017.24"},{"key":"53_CR2","unstructured":"European Commission: Smart cities. Cities using technological solutions to improve the management and efficiency of the urban environment (2021)"},{"key":"53_CR3","doi-asserted-by":"publisher","first-page":"17069","DOI":"10.1007\/s11042-017-5276-7","volume":"77","author":"L Lopez-Fuentes","year":"2017","unstructured":"Lopez-Fuentes, L., van de Weijer, J., Hidalgo, M.G., Skinnemoen, H., Bagdanov, A.D.: Review on computer vision techniques in emergency situation. Multimed. Tools Appl. 77, 17069\u201317107 (2017)","journal-title":"Multimed. Tools Appl."},{"key":"53_CR4","doi-asserted-by":"crossref","unstructured":"Alexandrie, G.: Surveillance cameras and crime: a review of randomized and natural experiments (2017)","DOI":"10.1080\/14043858.2017.1387410"},{"key":"53_CR5","doi-asserted-by":"crossref","unstructured":"Sikandar, T., Ghazali, K.H., Rabbi, M.F.: ATM crime detection using image processing integrated video surveillance: a systematic review (2018)","DOI":"10.1007\/s00530-018-0599-4"},{"key":"53_CR6","doi-asserted-by":"crossref","unstructured":"Nambiar, A., Bernardino, A., Nascimento, J.C.: Gait-based Person Re-identification: A Survey. ACM (2019)","DOI":"10.1145\/3243043"},{"key":"53_CR7","doi-asserted-by":"crossref","unstructured":"Shidik, G.F., Noersasongko, E., Nugraha, A., Andono, P.N., Jumanto, J., Kusuma, E.J.: A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets. IEEE (2019)","DOI":"10.1109\/ACCESS.2019.2955387"},{"key":"53_CR8","doi-asserted-by":"crossref","unstructured":"Huang, T.: Traffic Speed Estimation from Surveillance Video Data. IEEE (2018)","DOI":"10.1109\/CVPRW.2018.00029"},{"key":"53_CR9","unstructured":"Cropley, J.: Global professional video surveillance equipment market set for third year of near double-digit growth in 2019 (2019)"},{"key":"53_CR10","doi-asserted-by":"crossref","unstructured":"Ma, J., Dai, Y., Hirota, K.: A survey of video-based crowd anomaly detection in dense scenes (2017)","DOI":"10.20965\/jaciii.2017.p0235"},{"key":"53_CR11","unstructured":"Armas, J.S., Gil, P.C., Gil, C.C.: Video surveillance robot powered by raspberry pi. In: IML 2017 (2017)"},{"key":"53_CR12","unstructured":"Liu, X., Wang, J., Yang, Y., Cao, Z., Xiong, G., Xia, W.: Inferring Behaviors via Encrypted Video Surveillance Traffic by Machine Learning. IEEE (2019)"},{"key":"53_CR13","doi-asserted-by":"crossref","unstructured":"Arifoglu, D., Bouchachia, A.: Activity Recognition and Abnormal Behaviour Detection with Recurrent Neural Networks. ISSN (2017)","DOI":"10.1016\/j.procs.2017.06.121"},{"key":"53_CR14","doi-asserted-by":"crossref","unstructured":"Nikouei, S.Y., Chen, Y., Song, S., Xu, R., Choi, B.-Y., Faughnan, T.R.: Smart Surveillance as an Edge Network Service: from HarrCascade, SVM to a Lightweight CNN (2018)","DOI":"10.1109\/CIC.2018.00042"},{"key":"53_CR15","doi-asserted-by":"crossref","unstructured":"Datta, S., Sarkar: Automation, Security and Surveillance for a Smart City. IEEE (2018)","DOI":"10.1109\/CALCON.2017.8280689"},{"key":"53_CR16","unstructured":"Kong, Y., Fu, Y.: Human Action Recognition and Prediction: A Survey (2018)"},{"key":"53_CR17","doi-asserted-by":"crossref","unstructured":"Stergiou, C., Psannis, K.E., Plageras, A.P., Kokkonis, G., Ishibashi, Y.: Architecture for security monitoring in IoT environments. IEEE (2017)","DOI":"10.1109\/ISIE.2017.8001447"},{"key":"53_CR18","doi-asserted-by":"crossref","unstructured":"Rego, A., Canovas, A., Jim\u00e9nez, J.M., Lloret, J.: An Intelligent System for Video Surveillance in IoT Environments. IEEE (2018)","DOI":"10.1109\/ACCESS.2018.2842034"},{"key":"53_CR19","unstructured":"McKinsey Global Institute: Tech for Good. Smoothing disruption, improving well-being (2019)"},{"key":"53_CR20","doi-asserted-by":"crossref","unstructured":"Ahmed, E., Rehmani, M.H.: Mobile edge computing: opportunities, solutions, and challenges (2017)","DOI":"10.1016\/j.future.2016.09.015"},{"key":"53_CR21","unstructured":"Deloitte: Insights \u201cTechnology, Media and Telecommunications Prediction 2019\""},{"key":"53_CR22","unstructured":"Deloitte: Insights \u201cTech Trends 2019. Beyond the digital frontier\u201d. 10th Anniversary Edn"},{"key":"53_CR23","unstructured":"Gartner: Ed. by Cearley, D.W., Distinguished VP Analyst. Gartner \u201cTop 10 Strategic Technology Trends for 2019\""},{"key":"53_CR24","unstructured":"Bullhound, G.P.: Technology Predictions. Trends & Innovations shaping the global tech sector (2019)"},{"key":"53_CR25","unstructured":"HiPEAC: HiPEAC Vision 2019. High Performance and Embedded Architecture and Compilation (2019)"},{"key":"53_CR26","doi-asserted-by":"crossref","unstructured":"Kumar, Y., Aggarwal, M., Nawal, P., Satoh, S., Shah, R.R., Zimmermann, R.: Harnessing AI for Speech Reconstruction using Multi-view Silent Video Feed. ACM (2018)","DOI":"10.1145\/3240508.3241911"},{"key":"53_CR27","doi-asserted-by":"crossref","unstructured":"Ferraz, C.T., Saito, J.H.: A comprehensive analysis of local binary convolutional neural network for fast face recognition in surveillance video. In: WebMedia 2018 (2018)","DOI":"10.1145\/3243082.3267444"},{"key":"53_CR28","doi-asserted-by":"crossref","unstructured":"Noh, Y., Lee, D.: Low-level human action change detection using the motion history image. In: ICSCA 2019 (2019)","DOI":"10.1145\/3316615.3316725"},{"key":"53_CR29","doi-asserted-by":"crossref","unstructured":"Lin, H., Kong, Z., Wang, W., Liang, K., Chen, J.: Pedestrian detection in fish-eye images using deep learning: combine faster R-CNN with an effective cutting method. In: SPML 2018 (2018)","DOI":"10.1145\/3297067.3297069"},{"key":"53_CR30","doi-asserted-by":"crossref","unstructured":"Fu, Y., Xin, R., Ye, O.: A novel attention-based neural network for video scene classification in complex background. In: CASA 2019 (2019)","DOI":"10.1145\/3328756.3328768"},{"key":"53_CR31","doi-asserted-by":"crossref","unstructured":"Eda, T., Muramatsu, S., Mikami, K., Xu, S.: A Practical Person Monitoring System for City Security. IEEE (2018)","DOI":"10.1109\/AVSS.2018.8639168"},{"key":"53_CR32","doi-asserted-by":"crossref","unstructured":"Muchtar, K., Rahman, F., Munggaran, M.R., Dwiyantoro, A.P.J., Dharmadi, R., Nugraha, I.: A unified smart surveillance system incorporating adaptive foreground extraction and deep learning-based classification. In: ICAIIC 2019 (2019)","DOI":"10.1109\/ICAIIC.2019.8669017"},{"key":"53_CR33","doi-asserted-by":"crossref","unstructured":"Liu, Y., Yang, F., Ginhac, D.: Accurate single-stream action detection in real-time. In: ICDSC 2019 (2019)","DOI":"10.1145\/3349801.3349821"},{"key":"53_CR34","doi-asserted-by":"crossref","unstructured":"Saini, R., Kumar, P., Roy, P.P., Dogra, D.P.: An efficient approach for trajectory classification using FCM and SVM. In: IEEE (2017)","DOI":"10.1109\/TENCONSpring.2017.8070076"},{"key":"53_CR35","doi-asserted-by":"crossref","unstructured":"Fok, W.W.T., Chan, L.C.W., Chen, C.: Artificial intelligence for sport actions and performance analysis using recurrent neural network (RNN) with long short-term memory (LSTM). In: ICRAI 2018 (2018)","DOI":"10.1145\/3297097.3297115"},{"key":"53_CR36","doi-asserted-by":"crossref","unstructured":"Hu, L., Ni, Q., Yuan, F.: Big data oriented novel background subtraction algorithm for urban surveillance systems (2018)","DOI":"10.26599\/BDMA.2018.9020013"},{"key":"53_CR37","doi-asserted-by":"crossref","unstructured":"Xia, H., Li, T., Liu, W., Zhong, X., Yuan, J.L.: Abnormal event detection method in surveillance video based on temporal CNN and sparse optical flow. In: ICCDE 2019 (2019)","DOI":"10.1145\/3330530.3330538"},{"key":"53_CR38","doi-asserted-by":"crossref","unstructured":"Ramos da Costa, J., Nedjah, N., de Macedo Mourelle, L., Ramos da Costa, D.: Crowd abnormal detection using artificial bacteria colony and Kohonen\u2019s neural network. IEEE (2017)","DOI":"10.1109\/LA-CCI.2017.8285685"},{"key":"53_CR39","doi-asserted-by":"crossref","unstructured":"Cai, N., Chen, H., Li, Y., Peng, Y.: Intrusion detection and tracking at railway crossing. In: AIAM 2019 (2019)","DOI":"10.1145\/3358331.3358388"},{"key":"53_CR40","doi-asserted-by":"crossref","unstructured":"Luo, Z., He, W., Liwang, M., Huang, L., Zhao, Y., Geng, J.: Real-time detection algorithm of abnormal behavior in crowds based on Gaussian mixture model. In: ICCSE 2017 (2017)","DOI":"10.1109\/ICCSE.2017.8085486"},{"key":"53_CR41","doi-asserted-by":"crossref","unstructured":"Wang, J., Zheng, H., Huang, Y., Ding, X.: Vehicle Type Recognition in Surveillance Images From Labeled Web-Nature Data Using Deep Transfer Learning. IEEE (2018)","DOI":"10.1109\/TITS.2017.2765676"},{"key":"53_CR42","doi-asserted-by":"crossref","unstructured":"Wang, S., Zeng, Y., Liu, Q., Zhu, C., Zhu, E., Yin, J.: Detecting abnormality without knowing normality: a two-stage approach for unsupervised video abnormal event detection. In: ACM MM 2018 (2018)","DOI":"10.1145\/3240508.3240615"},{"key":"53_CR43","doi-asserted-by":"crossref","unstructured":"Susarla, P., Agrawal, U., Jayagopi, D.B.: Human weapon-activity recognition in surveillance videos using structural-RNN. In: MedPRAI 2018 (2018)","DOI":"10.1145\/3177148.3180080"},{"key":"53_CR44","doi-asserted-by":"crossref","unstructured":"Chackravarthy, S., Schmitt, S., Yang, L.: Intelligent crime anomaly detection in smart cities using deep learning. In: CIC 2018 (2018)","DOI":"10.1109\/CIC.2018.00060"},{"key":"53_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, F., Cui, L., Wang, H.: Research on children\u2019s fall detection by characteristic operator. In: ICAIP 2017 (2017)","DOI":"10.1145\/3133264.3133268"},{"key":"53_CR46","doi-asserted-by":"crossref","unstructured":"Nikouei, S.Y., Chen, Y., Song, S., Xu, R., Choi, B., Faughnan, T.: Smart Surveillance As An Edge Network Service: From Harr-Cascade, SVM to a Lightweight CNN. IEEE (2018)","DOI":"10.1109\/CIC.2018.00042"},{"key":"53_CR47","doi-asserted-by":"crossref","unstructured":"Thomas, S.S., Gupta, S., Subramanian, V.K.: Smart Surveillance Based on Video Summarization. IEEE (2017)","DOI":"10.1109\/TENCONSpring.2017.8070003"},{"key":"53_CR48","doi-asserted-by":"crossref","unstructured":"Guangli, W., Liping, L., Chen, Z., Dengtai, T.: Video Abnormal Event Detection Based on ELM. IEEE (2019)","DOI":"10.1109\/SIPROCESS.2019.8868910"},{"key":"53_CR49","doi-asserted-by":"crossref","unstructured":"Iva\u0161i\u0107-Kos, M., Kri\u0161to, M., Pobar, M.: Human Detection in Thermal Imaging Using YOLO. In: ICCTA 2019 (2019)","DOI":"10.1145\/3323933.3324076"},{"key":"53_CR50","doi-asserted-by":"crossref","unstructured":"Xia, H., Liu, W., Li, T., Zhong, X., Yuan, J.: The ground target detection and tracking method in surveillance video. In: ICCDE 2019 (2019)","DOI":"10.1145\/3330530.3330537"},{"key":"53_CR51","doi-asserted-by":"crossref","unstructured":"Huang, Y., Liu, Z., Jiang, M., Yu, X., Ding, X.: Cost-Effective Vehicle Type Recognition in Surveillance Images With Deep Active Learning and Web Data. IEEE (2020)","DOI":"10.1109\/TITS.2018.2888698"},{"key":"53_CR52","doi-asserted-by":"crossref","unstructured":"Nikouei, S.Y., Chen, Y., Song, S., Faughnan, T.R.: Kerman: A Hybrid Lightweight Tracking Algorithm to Enable Smart Surveillance as an Edge Service. IEEE (2019)","DOI":"10.1109\/CCNC.2019.8651791"},{"key":"53_CR53","doi-asserted-by":"crossref","unstructured":"Ghahremani, A., Kong, Y., Bondarev, E., de With, P.H.N.: Re-identification of vessels with convolutional neural networks. In: ICCTA 2019 (2019)","DOI":"10.1145\/3323933.3324075"},{"key":"53_CR54","doi-asserted-by":"crossref","unstructured":"Feng, X., Ye, M., Swaminathan, V., Wei, S.: Towards the Security of Motion Detection-based Video Surveillance on IoT Devices. ACM (2017)","DOI":"10.1145\/3126686.3126713"},{"key":"53_CR55","doi-asserted-by":"crossref","unstructured":"Baldoni, G., Melita, M., Micalizzi, S., Rametta, C., Schembra, G., Vassallo, A.: A dynamic, plug-and-play and efficient video surveillance platform for smart cities. IEEE (2017)","DOI":"10.1109\/CCNC.2017.7983190"},{"key":"53_CR56","doi-asserted-by":"crossref","unstructured":"Camboim, H.B., Neto, A.J.V., Rodrigues, J.J.P.C., Zhao, Z.: Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. IEEE (2017)","DOI":"10.1109\/S3C.2017.8501398"},{"key":"53_CR57","doi-asserted-by":"crossref","unstructured":"Nagothu, D., Xu, R., Nikouei, S.Y., Chen, Y.: A Microservice-enabled Architecture for Smart Surveillance using Blockchain Technology. IEEE (2018)","DOI":"10.1109\/ISC2.2018.8656968"},{"key":"53_CR58","doi-asserted-by":"crossref","unstructured":"Fiaz, M., Mahmood, A., Javed, S., Jung, S.K.: Handcrafted and Deep Trackers: Recent Visual Object Tracking Approaches and Trends. ACM (2019)","DOI":"10.1145\/3309665"},{"key":"53_CR59","doi-asserted-by":"crossref","unstructured":"Qezavati, H., Majidi, B., Manzuri, M.T.: Partially covered face detection in presence of headscarf for surveillance applications. In: IPRIA 2019 (2019)","DOI":"10.1109\/PRIA.2019.8786004"},{"key":"53_CR60","doi-asserted-by":"crossref","unstructured":"Mathur, G., Somwanshi, D., Bundele, M.M.: Intelligent video surveillance based on object tracking. In: ICRAIE 2018 (2018)","DOI":"10.1109\/ICRAIE.2018.8710421"},{"key":"53_CR61","doi-asserted-by":"crossref","unstructured":"Rothkrantz, L.: Person identification by smart cameras. In: 2SCSP 2017 (2017)","DOI":"10.1109\/SCSP.2017.7973347"},{"key":"53_CR62","doi-asserted-by":"crossref","unstructured":"Yao, G., Liu, X., Lei, T.: Action recognition with 3D ConvNet-GRU architecture. In: ICRCA 2018 (2018)","DOI":"10.1145\/3265639.3265672"},{"key":"53_CR63","doi-asserted-by":"crossref","unstructured":"Babiker, M., Khalifa, O.O., Htike, K.K., Hassan, A., Zaharadeen, M.: Automated Daily Human Activity Recognition For Video Surveillance Using Neural Network. IEEE (2017)","DOI":"10.1109\/ICSIMA.2017.8312024"},{"key":"53_CR64","doi-asserted-by":"crossref","unstructured":"Yao, T., Liu, J.: Human behavior understanding: from action recognition to complex event detection. In: ACM MM 2018 (2018)","DOI":"10.1145\/3240508.3241474"},{"key":"53_CR65","doi-asserted-by":"crossref","unstructured":"Han, P.Y., Yee, K.E., Yin, O.S.: Localized Temporal Representation in Human Action Recognition. In: ICNCC 2018 (2018)","DOI":"10.1145\/3301326.3301338"},{"key":"53_CR66","doi-asserted-by":"crossref","unstructured":"Jiang, N., Bai, S., Xu, Y., Xing, C., Zhou, Z., Wu, W.: Online inter-camera trajectory association exploiting person re-identification and camera topology. In: ACM MM 2018 (2018)","DOI":"10.1145\/3240508.3240663"},{"key":"53_CR67","doi-asserted-by":"crossref","unstructured":"Lee, B., Lee, M., Zhang, P., Tessier, A., Khan, A.: Semantic human activity annotation tool using skeletonized surveillance videos. In: ACM UbiComp\/ISWC 2019 Adjunct (2019)","DOI":"10.1145\/3341162.3343807"},{"key":"53_CR68","doi-asserted-by":"crossref","unstructured":"Nguyen, T.N., Ly, N.Q.: Abnormal activity detection based on dense spatial-temporal features and improved one-class learning. In: SoICT 2017 (2017)","DOI":"10.1145\/3155133.3155147"},{"key":"53_CR69","doi-asserted-by":"crossref","unstructured":"Chebi, H., Acheli, D., Kesraoui, M.: Strategy of detecting abnormal behaviors by fuzzy logic. In: ISCV 2017 (2017)","DOI":"10.1109\/ISACV.2017.8054982"},{"key":"53_CR70","doi-asserted-by":"crossref","unstructured":"Fu, E.Y., Huang, M.X., Leong, H.V., Ngai, G.: Cross-species learning: a low-cost approach to learning human fight from animal fight. In: ACM MM 2018 (2018)","DOI":"10.1145\/3240508.3240710"},{"key":"53_CR71","doi-asserted-by":"crossref","unstructured":"Zhang, F., Cui, L., Wang, H.: Research on children\u2019s fall detection by characteristic operator. In: ICAIP 2017 (2017)","DOI":"10.1145\/3133264.3133268"},{"key":"53_CR72","doi-asserted-by":"crossref","unstructured":"Zha, Y., Li, Y., Gopalakrishnan, S., Li, B., Kambhampati, S.: Recognizing plans by learning embeddings from observed action distributions. In: AAMAS 2018 (2018)","DOI":"10.65109\/PCGG9004"},{"key":"53_CR73","doi-asserted-by":"crossref","unstructured":"Ben Dhief, Y., Djemaiel, Y., Rekhis, S., Boudriga, N.: Cloud-based global monitoring system for smart cities. In: WAINA 2018 (2018)","DOI":"10.1109\/WAINA.2018.00103"},{"key":"53_CR74","doi-asserted-by":"crossref","unstructured":"Akbar, M.A., Azhar, T.N.: Concept of cost efficient smart CCTV network for cities in developing country. In: ICT ICISS 2018 (2018)","DOI":"10.1109\/ICTSS.2018.8550016"},{"key":"53_CR75","doi-asserted-by":"crossref","unstructured":"Peixoto, M.L.M., et al.: Data missing problem in smart surveillance environment. In: HPCS 2018 (2018)","DOI":"10.1109\/HPCS.2018.00152"},{"key":"53_CR76","doi-asserted-by":"crossref","unstructured":"Alshammari, A., Rawat, D.B.: Intelligent multi-camera video surveillance system for smart city applications. In: IEEE CCWC (2019)","DOI":"10.1109\/CCWC.2019.8666579"},{"key":"53_CR77","doi-asserted-by":"crossref","unstructured":"Pollok, T.: A new multi-camera dataset with surveillance, mobile and stereo cameras for tracking, situation analysis and crime scene investigation applications. In: ICVIP 2018 (2018)","DOI":"10.1145\/3301506.3301542"},{"key":"53_CR78","doi-asserted-by":"crossref","unstructured":"Rohit, K., Mistree, K., Lavji, J.: A review on abnormal crowd behavior detection. In: ICIIECS 2017 (2017)","DOI":"10.1109\/ICIIECS.2017.8275999"},{"key":"53_CR79","doi-asserted-by":"crossref","unstructured":"Lahiri, S., Jyoti, N., Pyati, S., Dewan, J.: Abnormal crowd behavior detection using image processing. In: ICCUBEA 2018 (2018)","DOI":"10.1109\/ICCUBEA.2018.8697356"},{"key":"53_CR80","doi-asserted-by":"crossref","unstructured":"Sah, M., Direkoglu, C.: Semantic annotation of surveillance videos for abnormal crowd behaviour search and analysis. In: IEEE (2017)","DOI":"10.1109\/AVSS.2017.8078537"},{"key":"53_CR81","doi-asserted-by":"crossref","unstructured":"Rold\u00e1n, J.J., Garcia-Aunon, P., Pe\u00f1a-Tapia, E., Barrientos, A.: SwarmCity project: can an aerial swarm monitor traffic in a smart city?. IEEE (2019)","DOI":"10.1109\/PERCOMW.2019.8730677"},{"key":"53_CR82","doi-asserted-by":"crossref","unstructured":"Xu, Z., Sinha, S., Harshil, S., Ramachandran, U.: Space-time vehicle tracking at the edge of the network. In: HotEdgeVideo 2019 (2019)","DOI":"10.1145\/3349614.3356025"},{"key":"53_CR83","doi-asserted-by":"crossref","unstructured":"Gao, L., Huang, D., Guo, Y., Wang, Y.: Pedestrian attribute recognition via hierarchical multi-task learning and relationship attention. In: ACM MM 2019 (2019)","DOI":"10.1145\/3343031.3351003"},{"key":"53_CR84","doi-asserted-by":"crossref","unstructured":"Alam, A., Ullah, I., Lee, Y.: Video Big Data Analytics in the Cloud: A Reference Architecture, Survey, Opportunities, and Open Research Issues. IEEE (2020)","DOI":"10.1109\/ACCESS.2020.3017135"},{"key":"53_CR85","doi-asserted-by":"crossref","unstructured":"Husain, A.A., Maity, T., Yadav, R.K.: Vehicle detection in intelligent transport system under a hazy environment: a survey. In: IET 2020 (2020)","DOI":"10.1049\/iet-ipr.2018.5351"},{"key":"53_CR86","unstructured":"Espinosa, J.E., Velast\u00edn, S.A., Branch, J.W.: Detection of Motorcycles in Urban Traffic Using Video Analysis: A Review. IEEE (2020)"},{"key":"53_CR87","doi-asserted-by":"crossref","unstructured":"Singh, R., Srivastava, R.: Some Contemporary approaches for human activity recognition: a survey. In: PARC 2020 (2020)","DOI":"10.1109\/PARC49193.2020.236672"},{"key":"53_CR88","doi-asserted-by":"crossref","unstructured":"Gupta, A., Gupta, K., Gupta, K., Gupta, K.: A survey on human activity recognition and classification. In: ICCSP 2020 (2020)","DOI":"10.1109\/ICCSP48568.2020.9182416"},{"key":"53_CR89","doi-asserted-by":"crossref","unstructured":"Jing, Y., Wang, W., Wang, L., Tan, T.: Cross-modal cross-domain moment alignment network for person search. In: IEEE\/CVF CVPR 2020 (2020)","DOI":"10.1109\/CVPR42600.2020.01069"},{"key":"53_CR90","doi-asserted-by":"crossref","unstructured":"Reddy, R.V., Reddy, V.J., Reddy, E.M.: Automatic face expressions and gesture detection system using blockchain security. In: ICIEM 2020 (2020)","DOI":"10.1109\/ICIEM48762.2020.9160325"},{"key":"53_CR91","doi-asserted-by":"crossref","unstructured":"Tian, J., et al.: Automated analysis of seizure behavior in video: methods and challenges. In: WSAI 2020 (2020)","DOI":"10.1109\/WSAI49636.2020.9143279"},{"key":"53_CR92","doi-asserted-by":"crossref","unstructured":"Nadeem, A., Jalal, A., Kim, K.: Human actions tracking and recognition based on body parts detection via artificial neural network. In: ICACS 2020 (2020)","DOI":"10.1109\/ICACS47775.2020.9055951"},{"key":"53_CR93","doi-asserted-by":"crossref","unstructured":"Zhang, K., Ling, W.: Joint Motion Information Extraction and Human Behavior Recognition in Video Based on Deep Learning. IEEE (2020)","DOI":"10.1109\/JSEN.2019.2959582"},{"key":"53_CR94","doi-asserted-by":"crossref","unstructured":"Ezatzadeh, S., Keyvanpour, M.R.: Fall detection for elderly in assisted environments: video surveillance systems and challenges. In: IKT 2017 (2017)","DOI":"10.1109\/IKT.2017.8258624"},{"key":"53_CR95","doi-asserted-by":"crossref","unstructured":"Khan, J., et al.: SMSH: Secure Surveillance Mechanism on Smart Healthcare IoT System With Probabilistic Image Encryption. IEEE (2020)","DOI":"10.1109\/ACCESS.2020.2966656"},{"key":"53_CR96","doi-asserted-by":"crossref","unstructured":"Jhapate, A.K., Malviya, S., Jhapate, M.: Unusual crowd activity detection using OpenCV and Motion Influence Map. In: IDEA 2020","DOI":"10.1109\/IDEA49133.2020.9170704"},{"key":"53_CR97","doi-asserted-by":"crossref","unstructured":"Hao, Q., Qin, L.: The Design of Intelligent Transportation Video Processing System in Big Data Environment. IEEE (2020)","DOI":"10.1109\/ACCESS.2020.2964314"},{"key":"53_CR98","doi-asserted-by":"crossref","unstructured":"Peri, N., et al.: Towards real-time systems for vehicle re-identification, multi-camera tracking, and anomaly detection. In: IEEE\/CVF CVPRW 2020 (2020)","DOI":"10.1109\/CVPRW50498.2020.00319"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-80129-8_53","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T07:14:25Z","timestamp":1771658065000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-80129-8_53"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030801281","9783030801298"],"references-count":98,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-80129-8_53","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 July 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}