Applications and Challenges in Video Surveillance via Drone: A Brief Survey

被引:0
|
作者
Dilshad, Naqqash [1 ]
Hwang, JaeYoung [1 ]
Song, JaeSeung [1 ]
Sung, NakMyoung [2 ]
机构
[1] Sejong Univ, Dept Informat Secur, Seoul, South Korea
[2] Korea Elect Technol Inst, Autonomous IoT Res Ctr, Gyeonggi Do, South Korea
来源
11TH INTERNATIONAL CONFERENCE ON ICT CONVERGENCE: DATA, NETWORK, AND AI IN THE AGE OF UNTACT (ICTC 2020) | 2020年
关键词
UAV; 5G-IoT; AI; Video Surveillance; Object Detection; Activity Recognition; Video Summarization;
D O I
10.1109/ictc49870.2020.9289536
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Our society is moving quickly towards smart homes and smart cities, requiring more and more deployment of Internet of Things (IoT) devices. To achieve smart urbanization, continuous surveillance is necessary. Research about video surveillance via Closed-Circuit Television (CCTV) cameras is in play for decades but poses different problems, i.e., limited area coverage, no location sharing, and tracking capabilities. On the other hand, vision sensors mounted on drones are more scalable and flexible with more comprehensive surveillance coverage. But at the same time, drones also encounter several challenges, such as limited processing and power resources, trembling camera effects in the video feed, disturbance in transmission signals, etc. Drones surveillance lacks the researcher's attentiveness, and therefore, we collect the related literature and confer their practical viewpoint broadly. This article focuses on video surveillance using drones in object detection and tracking, video summarization, persistent monitoring of the target, search and rescue operation in a hostile environment, traffic management in smart cities, and disaster management in an apocalyptic situation. This brief survey sheds light on the research gaps and profound insights of the methods used in the mentioned articles by opening up future research tracks for the Computer Vision (CV) enthusiasts using Unmanned Aerial Vehicles (UAV).
引用
收藏
页码:728 / 732
页数:5
相关论文
共 50 条
  • [1] VPTDrone: Video Processing Toolkit for Smart Surveillance Drone
    Dalal, Dwip
    Dasgupta, Anirban
    PROCEEDINGS OF 7TH JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MANAGEMENT OF DATA, CODS-COMAD 2024, 2024, : 595 - 596
  • [2] Privacy in Mini-drone Based Video Surveillance
    Bonetto, Margherita
    Korshunov, Pavel
    Ramponi, Giovanni
    Ebrahimi, Touradj
    2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 2464 - 2469
  • [3] Privacy in Mini-drone Based Video Surveillance
    Bonetto, Margherita
    Korshunov, Pavel
    Ramponi, Giovanni
    Ebrahimi, Touradj
    2015 11TH IEEE INTERNATIONAL CONFERENCE AND WORKSHOPS ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG): DE-IDENTIFICATION FOR PRIVACY PROTECTION IN MULTIMEDIA (DEID 2015), VOL 4, 2015,
  • [4] Challenges of automated video surveillance
    Perez Esquivel, Andres
    DERECHO Y CIENCIAS SOCIALES, 2020, (24): : 100 - 122
  • [5] Wireless Video Surveillance: A Survey
    Ye, Yun
    Ci, Song
    Katsaggelos, Aggelos K.
    Liu, Yanwei
    Qian, Yi
    IEEE ACCESS, 2013, 1 : 646 - 660
  • [6] Video Surveillance and Law: Uses and Challenges
    Syed, Hira
    Bouvry, Pascal
    11TH RSEP INTERNATIONAL MULTIDISCIPLINARY CONFERENCE, 2019, : 13 - 32
  • [7] Fuzzy Logic in Surveillance Big Video Data Analysis: Comprehensive Review, Challenges, and Research Directions
    Muhammad, Khan
    Obaidat, Mohammad S.
    Hussain, Tanveer
    Del Ser, Javier
    Kumar, Neeraj
    Tanveer, Mohammad
    Doctor, Faiyaz
    ACM COMPUTING SURVEYS, 2022, 54 (03)
  • [8] Security and Privacy in Video Surveillance: Requirements and Challenges
    Rajpoot, Qasim Mahmood
    Jensen, Christian Damsgaard
    ICT SYSTEMS SECURITY AND PRIVACY PROTECTION, IFIP TC 11 INTERNATIONAL CONFERENCE, SEC 2014, 2014, 428 : 169 - 184
  • [9] Importance of detection for video surveillance applications
    Varona, Javier
    Gonzalez, Jordi
    Rius, Ignasi
    Villanueva, Juan Jose
    OPTICAL ENGINEERING, 2008, 47 (08)
  • [10] Mixture models based background subtraction for video surveillance applications
    Poppe, Chris
    Martens, Gaetan
    Lambert, Peter
    Van de Walle, Rik
    COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS, 2007, 4673 : 28 - 35