Matches in SemOpenAlex for { <https://semopenalex.org/work/W4286508592> ?p ?o ?g. }
- W4286508592 endingPage "104064" @default.
- W4286508592 startingPage "104064" @default.
- W4286508592 abstract "Since the start of the COVID-19 pandemic, social distancing (SD) has played an essential role in controlling and slowing down the spread of the virus in smart cities. To ensure the respect of SD in public areas, visual SD monitoring (VSDM) provides promising opportunities by (i) controlling and analyzing the physical distance between pedestrians in real-time, (ii) detecting SD violations among the crowds, and (iii) tracking and reporting individuals violating SD norms. To the authors' best knowledge, this paper proposes the first comprehensive survey of VSDM frameworks and identifies their challenges and future perspectives. Typically, we review existing contributions by presenting the background of VSDM, describing evaluation metrics, and discussing SD datasets. Then, VSDM techniques are carefully reviewed after dividing them into two main categories: hand-crafted feature-based and deep-learning-based methods. A significant focus is paid to convolutional neural networks (CNN)-based methodologies as most of the frameworks have used either one-stage, two-stage, or multi-stage CNN models. A comparative study is also conducted to identify their pros and cons. Thereafter, a critical analysis is performed to highlight the issues and impediments that hold back the expansion of VSDM systems. Finally, future directions attracting significant research and development are derived." @default.
- W4286508592 created "2022-07-22" @default.
- W4286508592 creator A5024641789 @default.
- W4286508592 creator A5033695027 @default.
- W4286508592 creator A5037331113 @default.
- W4286508592 creator A5042823692 @default.
- W4286508592 creator A5051848738 @default.
- W4286508592 creator A5056297603 @default.
- W4286508592 creator A5073274738 @default.
- W4286508592 date "2022-10-01" @default.
- W4286508592 modified "2023-10-18" @default.
- W4286508592 title "Deep visual social distancing monitoring to combat COVID-19: A comprehensive survey" @default.
- W4286508592 cites W1536680647 @default.
- W4286508592 cites W1976959044 @default.
- W4286508592 cites W1992503120 @default.
- W4286508592 cites W2015148749 @default.
- W4286508592 cites W2031489346 @default.
- W4286508592 cites W2049409070 @default.
- W4286508592 cites W2102605133 @default.
- W4286508592 cites W2117539524 @default.
- W4286508592 cites W2158634074 @default.
- W4286508592 cites W2204750386 @default.
- W4286508592 cites W2557728737 @default.
- W4286508592 cites W2570343428 @default.
- W4286508592 cites W2601564443 @default.
- W4286508592 cites W2799108620 @default.
- W4286508592 cites W2962721361 @default.
- W4286508592 cites W2963037989 @default.
- W4286508592 cites W2963150697 @default.
- W4286508592 cites W2963351448 @default.
- W4286508592 cites W2963766909 @default.
- W4286508592 cites W2963786238 @default.
- W4286508592 cites W2966926453 @default.
- W4286508592 cites W2971926293 @default.
- W4286508592 cites W3008804154 @default.
- W4286508592 cites W3012991084 @default.
- W4286508592 cites W3024585647 @default.
- W4286508592 cites W3034758157 @default.
- W4286508592 cites W3041542482 @default.
- W4286508592 cites W3043529077 @default.
- W4286508592 cites W3045576536 @default.
- W4286508592 cites W3049296443 @default.
- W4286508592 cites W3080468264 @default.
- W4286508592 cites W3080889385 @default.
- W4286508592 cites W3082280594 @default.
- W4286508592 cites W3082591845 @default.
- W4286508592 cites W3083344977 @default.
- W4286508592 cites W3084486024 @default.
- W4286508592 cites W3085809395 @default.
- W4286508592 cites W3094713880 @default.
- W4286508592 cites W3094795122 @default.
- W4286508592 cites W3095178570 @default.
- W4286508592 cites W3097373657 @default.
- W4286508592 cites W3097720782 @default.
- W4286508592 cites W3114687924 @default.
- W4286508592 cites W3118387413 @default.
- W4286508592 cites W3120684604 @default.
- W4286508592 cites W3121468932 @default.
- W4286508592 cites W3124304280 @default.
- W4286508592 cites W3128882018 @default.
- W4286508592 cites W3130213149 @default.
- W4286508592 cites W3131321978 @default.
- W4286508592 cites W3137725667 @default.
- W4286508592 cites W3144095145 @default.
- W4286508592 cites W3147892880 @default.
- W4286508592 cites W3153088880 @default.
- W4286508592 cites W3154019088 @default.
- W4286508592 cites W3155096667 @default.
- W4286508592 cites W3156383855 @default.
- W4286508592 cites W3157078579 @default.
- W4286508592 cites W3157095620 @default.
- W4286508592 cites W3158998520 @default.
- W4286508592 cites W3159594293 @default.
- W4286508592 cites W3164328378 @default.
- W4286508592 cites W3164429310 @default.
- W4286508592 cites W3176739647 @default.
- W4286508592 cites W3177465897 @default.
- W4286508592 cites W3177587866 @default.
- W4286508592 cites W3180134609 @default.
- W4286508592 cites W3182649111 @default.
- W4286508592 cites W3186952419 @default.
- W4286508592 cites W3190647944 @default.
- W4286508592 cites W3193123183 @default.
- W4286508592 cites W3193756932 @default.
- W4286508592 cites W3196328959 @default.
- W4286508592 cites W3198737741 @default.
- W4286508592 cites W3201094278 @default.
- W4286508592 cites W3201942373 @default.
- W4286508592 cites W3203286708 @default.
- W4286508592 cites W3204579221 @default.
- W4286508592 cites W3204897525 @default.
- W4286508592 cites W3205049433 @default.
- W4286508592 cites W3207165655 @default.
- W4286508592 cites W3211302483 @default.
- W4286508592 cites W3212800268 @default.
- W4286508592 cites W3214450481 @default.
- W4286508592 cites W3214830888 @default.
- W4286508592 cites W3217658296 @default.