Aerial roaming aerial photography path planning based on areas of interest

被引:0
|
作者
Chen, Gang [1 ]
Yao, Zhengwei [1 ]
机构
[1] Hangzhou Normal Univ, Sch Informat Sci & Technol, Hangzhou, Peoples R China
关键词
virtual reality; path planning; air roaming; salient features;
D O I
10.1145/3650400.3650689
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In virtual reality, traditional roaming methods are limited to a single ground roaming. In order to enrich tourists' roaming experience, this paper proposes an aerial photography path planning method based on areas of interest. First, by obtaining the characteristic information of the landmark, including the outline of the landmark and the middle area of the top surface of the landmark, the corresponding saliency value of the landmark surface is calculated. Then, a landmark-centered viewpoint quality field is constructed to guide local virtual camera motion. In this process, the saliency value is combined with the center composition and the rule of thirds composition in photography techniques to calculate the viewpoint quality score. Finally, a diagonal composition method was adopted to provide an excellent visual experience for flying between landmarks. Experiments show that the aerial photography path obtained by this method allows users to appreciate the beautiful scenery of the city from an aerial perspective in a short period of time, and has strong practicability and applicability.
引用
收藏
页码:1731 / 1737
页数:7
相关论文
共 50 条
  • [21] Dynamic Path Planning Based on Neural Networks for Aerial Inspection
    Gabriel G. R. de Castro
    Milena F. Pinto
    Iago Z. Biundini
    Aurelio G. Melo
    Andre L. M. Marcato
    Diego B. Haddad
    Journal of Control, Automation and Electrical Systems, 2023, 34 : 85 - 105
  • [22] Dynamic Path Planning Based on Neural Networks for Aerial Inspection
    de Castro, Gabriel G. R.
    Pinto, Milena F.
    Biundini, Iago Z.
    Melo, Aurelio G.
    Marcato, Andre L. M.
    Haddad, Diego B.
    JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS, 2023, 34 (01) : 85 - 105
  • [23] UNMANNED AERIAL VEHICLE PATH PLANNING BASED ON TLBO ALGORITHM
    Yu, Guolin
    Song, Hui
    Gao, Jie
    INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 2014, 7 (03) : 1310 - 1325
  • [24] Risk-Based Path Planning Optimization Methods for Unmanned Aerial Vehicles Over Inhabited Areas
    Rudnick-Cohen, Eliot
    Herrmann, Jeffrey W.
    Azarm, Shapour
    JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING, 2016, 16 (02)
  • [25] Optimal path planning for an unmanned aerial vehicle
    KrishnamurthyGopalan, A
    Davari, A
    Manish, A
    PROCEEDINGS OF THE THIRTY-SEVENTH SOUTHEASTERN SYMPOSIUM ON SYSTEM THEORY, 2005, : 258 - 261
  • [26] Learning Reconstructability for Drone Aerial Path Planning
    Liu, Yilin
    Lin, Liqiang
    Hu, Yue
    Xie, Ke
    Fu, Chi-Wing
    Zhang, Hao
    Huang, Hui
    ACM TRANSACTIONS ON GRAPHICS, 2022, 41 (06):
  • [27] Aerial Path Planning for Multi-Vehicles
    Asif, Rizwan
    Loffel, Hendrik
    Assavasangthong, Vorapol
    Martinelli, Giulio
    Gajland, Phillip
    Galvez, Borja Rodriguez
    2019 IEEE SECOND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND KNOWLEDGE ENGINEERING (AIKE), 2019, : 267 - 272
  • [28] Research on Unmanned Aerial Vehicle Path Planning
    Luo, Junhai
    Tian, Yuxin
    Wang, Zhiyan
    DRONES, 2024, 8 (02)
  • [29] Ellipsoidal Path Planning for Unmanned Aerial Vehicles
    Villasenor, Carlos
    Gallegos, Alberto A.
    Lopez-Gonzalez, Gehova
    Gomez-Avila, Javier
    Hernandez-Barragan, Jesus
    Arana-Daniel, Nancy
    APPLIED SCIENCES-BASEL, 2021, 11 (17):
  • [30] A Path Planning Method of Unmanned Aerial Vehicle
    Zhao, Peihai
    Wang, Mimi
    Cao, Ruihao
    2019 11TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC 2019), VOL 2, 2019, : 202 - 206