Application of consumer RGB-D cameras for fruit detection and localization in field: A critical review

被引:165
|
作者
Fu, Longsheng [1 ,3 ,4 ,5 ]
Gao, Fangfang [1 ]
Wu, Jingzhu [2 ]
Li, Rui [1 ]
Karkee, Manoj [5 ]
Zhang, Qin [5 ]
机构
[1] Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Shaanxi, Peoples R China
[2] Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China
[3] Minist Agr & Rural Affairs, Key Lab Agr Internet Things, Yangling 712100, Shaanxi, Peoples R China
[4] Shaanxi Key Lab Agr Informat Percept & Intelligen, Yangling 712100, Shaanxi, Peoples R China
[5] Washington State Univ, Ctr Precis & Automated Agr Syst, Prosser, WA 99350 USA
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Structured light; Time of flight; Active infrared stereo; Infrared image; Depth image; VISION-BASED CONTROL; FASTER R-CNN; APPLE DETECTION; STRUCTURED LIGHT; CITRUS DETECTION; DEPTH FEATURES; KINECT V2; D SENSORS; SYSTEM; COLOR;
D O I
10.1016/j.compag.2020.105687
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Fruit detection and localization are essential for future agronomic management of fruit crops such as yield prediction, yield mapping and automated harvesting. However, to perform robust and efficient fruit detection and localization in orchard is a challenging task under variable illumination, low-resolutions and heavy occlusion by neighboring fruits, foliage, or branches. Therefore, researches of fruit detection and localization by getting more information of objects are essential. RGB-D (Red, Green, Blue-Depth) cameras are promising sensors and widely used in fruit detection and localization given that they provide depth information and infrared information in addition to RGB information. After presenting a discussion on the advantages and disadvantages of RGB-D cameras with different depth measurement principles and application fields, this paper reviews various types of RGB-D sensor systems and image processing methods used for fruit detection and localization in the field. Finally, major challenges for the successful application of RGB-D camera-based machine vision system, and potential future directions for the research and development in this area are discussed.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] Dense Visual SLAM for RGB-D Cameras
    Kerl, Christian
    Sturm, Juergen
    Cremers, Daniel
    2013 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2013, : 2100 - 2106
  • [22] Depth Error Elimination for RGB-D Cameras
    Gao, Yue
    Yang, You
    Zhen, Yi
    Dai, Qionghai
    ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2015, 6 (02)
  • [23] FusionMLS: Highly dynamic 3D reconstruction with consumer-grade RGB-D cameras
    Meerits S.
    Thomas D.
    Nozick V.
    Saito H.
    Computational Visual Media, 2018, 4 (4) : 287 - 303
  • [24] An extrinsic calibration method for multiple RGB-D cameras in a limited field of view
    Jia Chaochuan
    Yang Ting
    Wang Chuanjiang
    Fan Binghui
    He Fugui
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2020, 31 (04)
  • [25] Semantic Monte-Carlo Localization in Changing Environments using RGB-D Cameras
    Himstedt, Marian
    Maehle, Erik
    2017 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR), 2017,
  • [26] In-field tea shoot detection and 3D localization using an RGB-D camera
    Li, Yatao
    He, Leiying
    Jia, Jiangming
    Lv, Jun
    Chen, Jianneng
    Qiao, Xin
    Wu, Chuanyu
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 185
  • [27] First Attempts in Deception Detection in HRI by using Thermal and RGB-D cameras
    Iacob, David-Octavian
    Tapus, Adriana
    2018 27TH IEEE INTERNATIONAL SYMPOSIUM ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (IEEE RO-MAN 2018), 2018, : 652 - 658
  • [28] Real-Time Passable Area Segmentation With Consumer RGB-D Cameras for the Visually Impaired
    Zou, Wenbin
    Hua, Guoguang
    Zhuang, Yue
    Tian, Shishun
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [29] 3D Reconstruction with Mirrors and RGB-D Cameras
    Akay, Abdullah
    Akgul, Yusuf Sinan
    PROCEEDINGS OF THE 2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, THEORY AND APPLICATIONS (VISAPP 2014), VOL 3, 2014, : 325 - 334
  • [30] Structure Selective Depth Superresolution for RGB-D Cameras
    Kim, Youngjung
    Ham, Bumsub
    Oh, Changjae
    Sohn, Kwanghoon
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 25 (11) : 5227 - 5238