Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 11-15.

• Review • Previous Articles     Next Articles

Survey on Applications of Visual Crowdsensing

ZHAI Shu-ying1, LI Ru1, LI Bo1, HAO Shao-yang2   

  1. Mingde College,Northwestern Polytechnical University,Xi'an 710124,China1;
    School of Computer Science,Northwestern Polytechnical University,Xi'an 710129,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: In recent years,Visual Crowdsensing(VCS) that sensed through images and video,has become a predominant sensing paradigm of Mobile Crowdsensing(MCS),which is one of the current research hotspots.VCS requires people to capture the details of sensing objects in the real world in the form of pictures or video,which is widely used in various fields.However,there is no article summarizing the development and current situation of VCS in China.To this end,this paper summarized the latest applications of VCS,including floor plan generation,indoor scene reconstruction,outdoor scene reconstruction,event reconstruction,indoor localization,indoor navigation and disaster relief,and summarized some unique problems of VCS at present.

Key words: Event reconstruction, Indoor localization, Indoor navigation, Mobile crowdsensing, Visual crowdsensing

CLC Number: 

  • TP391
[1]GUO B,WANG Z,YU Z,et al.Mobile Crowd Sensing and Computing:The Review of an Emerging Human-Powered Sensing Paradigm[J].Acm Computing Surveys,2015,48(1):7.
[2]WANG L,ZHANG D,WANG Y,et al.Sparse mobile crow-dsensing:challenges and opportunities[J].IEEE Communications Magazine,2016,54(7):161-167.
[3]GUO B,HAN Q,CHEN H,et al.The Emergence of Visual Crowdsensing:Challenges and Opportunities[J].IEEE Communications Surveys & Tutorials,2017,PP(99):1.
[4]TENG X,GUO D,GUO Y,et al.SISE:Self-updating of Indoor Semantic Floorplans for General Entities[J].IEEE Transactions on Mobile Computing,2018,PP(99):1.
[5]ZHANG Q,ZHANG Q,SHI W,et al.Firework:Data Proces-sing and Sharing for Hybrid Cloud-Edge Analytics[J].IEEE Transactions on Parallel & Distributed Systems,2018,PP(99):1.
[6]TENG X,GUO D,GUO Y,et al.IONavi:an indoor-outdoor navigation service via mobile crowdsensing[J].ACM Transactions on Sensor Networks,2017,13(2):12.
[7]ZUO P,HUA Y,LIU X,et al.BEES:Bandwidth- and Energy- Efficient Image Sharing for Real-Time Situation Awareness[C]∥IEEE,International Conference on Distributed Computing Systems.IEEE,2017:1510-1520.
[8]CHEN S,LI M,REN K,et al.Crowd Map:Accurate Recon-struction of Indoor Floor Plans from Crowdsourced Sensor-Rich Videos∥2015 IEEE 35th International Conference on Distributed Computing Systems.IEEE,2015:1-10.
[9]GAO R,ZHAO M,YE T,et al.Jigsaw:indoor floor plan reconstruction via mobile crowdsensing[C]∥International Confe-rence on Mobile Computing and NETWORKING.ACM,2014:249-260.
[10]SANKAR A,SEITZ S.Capturing indoor scenes with smartphones[C]∥ACM Symposium on User Interface Software and Technology.ACM,2012:403-412.
[11]PENG Z,GAO S,XIAO B,et al.CrowdGIS:Updating Digital Maps via Mobile Crowdsensing[J].IEEE Transactions on Automation Science & Engineering,2017,PP(99):1-12.
[12]TUITE K,SNAVELY N,HSIAO D Y,et al.PhotoCity:train-ing experts at large-scale image acquisition through a competitive game∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.ACM,2011:1383-1392.
[13]RAYCHOUDHURY V,SHRIVASTAV S,SANDHA S S,et al. CROWD-PAN-360:Crowdsourcing Based Context-Aware Panoramic Map Generation for Smartphone Users[J].IEEE Transactions on Parallel & Distributed Systems,2015,26(8):2208-2219.
[14]KIM S H,LU Y,SHI J,et al.Key Frame Selection Algorithms for Automatic Generation of Panoramic Images from Crow-dsourced Geo-tagged Videos[C]∥International Symposium on Web and Wireless Geographical Information Systems.Springer,Berlin,Heidelberg,2014:67-84.
[15]BAO X,CHOUDHURY R R.MoVi:mobile phone based video highlights via collaborative sensing[C]∥International Confe-rence on Mobile Systems,Applications,and Services.ACM,2010:357-370.
[16]GIRIDHAR P,WANG S,ABDELZAHER T,et al.On localizing urban events with instagram[C]∥INFOCOM 2017-IEEE Conference on Computer Communications.IEEE,2017:1-9.
[17]BANO S,CAVALLARO A.Discovery and organization of multi-camera user-generated videos of the same event[J].Information Sciences,2015,302:108-121.
[18]CARLIER A,CALVET L,GURDJOS P,et al.Querying Multiple Simultaneous Video Streams with 3D Interest Maps[M]∥Visual Content Indexing and Retrieval with Psycho-Visual Mo-dels.Springer,Cham,2017:125-144.
[19]RODRIGUES J,MARQUES E R B,SILVA J,et al.Video Dissemination in Untethered Edge-Clouds:A Case Study[C]∥IFIP International Conference on Distributed Applications and Interoperable Systems.Springer,Cham,2018:137-152.
[20]BOHEZ S,DANEELS G,VAN HERZEELE L,et al.The crowd as a cameraman:on-stage display of crowdsourced mobile video at large-scale events[J].Multimedia Tools and Applications,2018,77(1):597-629.
[21]XU H,YANG Z,ZHOU Z,et al.Enhancing wifi-based localization with visual clues[C]∥Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing.ACM,2015:963-974.
[22]CHON Y,LANE N D,LI F,et al.Automatically characterizing places with opportunistic crowdsensing using smartphones[C]∥Proceedings of the 2012 ACM Conference on Ubiquitous Computing.ACM,2012:481-490.
[23]DONG J,XIAO Y,NOREIKIS M,et al.iMoon:Using Smart-phones for Image-based Indoor Navigation[C]∥ACM Con-ference on Embedded Networked Sensor Systems.ACM,2015:85-97.
[24]https://mspg.azurewebsites.net.
[25]ROY Q,PERRAULT S T,DAVIS R C,et al.Follow-My-Lead:Intuitive Indoor Path Creation and Navigation Using Interactive Videos[C]∥CHI Conference on Human Factors in Computing Systems.ACM,2017:5703-5715.
[26]YIN Z,WU C,YANG Z,et al.Peer-to-peer indoor navigation using smartphones[J].IEEE Journal on Selected Areas in Communications,2017,35(5):1141-1153.
[27]SHU Y,SHIN K G,HE T,et al.Last-mile navigation using sma-rtphones[C]∥Proceedings of the 21st Annual International Conference on Mobile Computing and Networking.ACM,2015:512-524.
[28]RICHERZHAGEN B,WULFHEIDE J,KOEPPL H,et al.Enabling crowdsourced live event coverage with adaptive collaborative upload strategies[C]∥World of Wireless,Mobile and Multimedia Networks.IEEE,2016:1-3.
[29]WU Y,CAO G.VideoMec:a metadata-enhanced crowdsourcing system for mobile videos[C]∥ACM/IEEE International Conference on Information Processing in Sensor Networks.IEEE,2017:143-154.
[30]DAO T,ROYCHOWDHURY A K,MADHYASTHA H V,et al. Managing Redundant Content in Bandwidth Constrained Wireless Networks[J].IEEE/ACM Transactions on Networking,2017,PP(99):1-16.
[31]WU Y,WANG Y,HU W,et al.Resource-Aware Photo Crow-dsourcing Through Disruption Tolerant Networks[C]∥IEEE,International Conference on Distributed Computing Systems.IEEE,2016:374-383.
[32]WU Y,WANG Y,HU W,et al.Smartphoto:a resource-aware crowdsourcing approach for image sensing with smartphones[J].IEEE Transactions on Mobile Computing,2016,15(5):1249-1263.
[33]WEINSBERG U,LI Q,TAFT N,et al.CARE:content aware redundancy elimination for challenged networks[C]∥Procee-dings of the 11th ACM Workshop on Hot Topics in Networks.ACM,2012:127-132.
[34]MERGEL I.Distributed Democracy:SeeClickFix.Com for Crowdsourced Issue Reporting[J].Ssrn Electronic Journal,2012.
[35]LU Y,COLMENARES J A.Efficient Detection of Points of Interest from Georeferenced Visual Content∥Proceedings of the 6th ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data.ACM,2017:27-36.
[36]LI Y,XUE F,FAN X,et al.Pedestrian walking safety system based on smartphone built-in sensors[J].IET Communications,2018,12(6):751-758.
[37]KIM S,ROBSON C,ZIMMERMAN T,et al.Creek watch:pairing usefulness and usability for successful citizen science∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.ACM,2011:2125-2134.
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