{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T17:07:38Z","timestamp":1732036058166},"reference-count":139,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,4,29]],"date-time":"2016-04-29T00:00:00Z","timestamp":1461888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture.<\/jats:p>","DOI":"10.3390\/s16050618","type":"journal-article","created":{"date-parts":[[2016,5,2]],"date-time":"2016-05-02T14:17:11Z","timestamp":1462198631000},"page":"618","source":"Crossref","is-referenced-by-count":169,"title":["3-D Imaging Systems for Agricultural Applications\u2014A Review"],"prefix":"10.3390","volume":"16","author":[{"given":"Manuel","family":"V\u00e1zquez-Arellano","sequence":"first","affiliation":[{"name":"Institute of Agricultural Engineering, University of Hohenheim, Garbenstrasse 9, Stuttgart 70599, Germany"}]},{"given":"Hans","family":"Griepentrog","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Engineering, University of Hohenheim, Garbenstrasse 9, Stuttgart 70599, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-0158-6456","authenticated-orcid":false,"given":"David","family":"Reiser","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Engineering, University of Hohenheim, Garbenstrasse 9, Stuttgart 70599, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8275-8840","authenticated-orcid":false,"given":"Dimitris","family":"Paraforos","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Engineering, University of Hohenheim, Garbenstrasse 9, Stuttgart 70599, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2016,4,29]]},"reference":[{"key":"ref_1","unstructured":"Hertwich, E. (2010). Assessing the Environmental Impacts of Consumption and Production: Priority Products and Materials, A Report of the Working Group on the Environmental Impacts of Products and Materials to the International Panel for Sustainable Resource Management, UNEP."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/MRA.2013.2255513","article-title":"IEEE Robotics and Automation Society Technical Committee on Agricultural Robotics and Automation","volume":"20","author":"Bergerman","year":"2013","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Nof, S.Y. (2009). Handbook of Automation, Springer.","DOI":"10.1007\/978-3-540-78831-7"},{"key":"ref_4","unstructured":"Joergensen, R.N. (2002). Study on Line Imaging Spectroscopy as a Tool for Nitrogen Diagnostics in Precision Farming, The Royal Veterinary and Agricultural University."},{"key":"ref_5","unstructured":"Eddershaw, T. (2014). IMAGING & Machine Vision Europe, Europa Science."},{"key":"ref_6","unstructured":"Antman, S., Sirovich, L., Marsden, J.E., and Wiggins, S. (2004). An Invitation to 3-D Vision: From Images to Geometric Models, Springer Science+Business Media."},{"key":"ref_7","unstructured":"Bellmann, A., Hellwich, O., Rodehorst, V., and Yilmaz, U. (2007). IEEE Conference on Computer Vision and Pattern Recognition, IEEE."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/TPAMI.1983.4767365","article-title":"A perspective on range finding techniques for computer vision","volume":"PAMI-5","author":"Jarvis","year":"1983","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1117\/1.1631921","article-title":"Review of 20 years of range sensor development","volume":"13","author":"Blais","year":"2004","journal-title":"J. Electron. Imaging"},{"key":"ref_10","first-page":"37","article-title":"A review of automation and robotics for the bioindustry","volume":"1","author":"Grift","year":"2008","journal-title":"J. Biomechatron. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s11370-010-0075-2","article-title":"Applied machine vision of plants: A review with implications for field deployment in automated farming operations","volume":"3","author":"McCarthy","year":"2010","journal-title":"Intell. Serv. Robot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1007\/BF01212277","article-title":"Active, Optical Range Imaging Sensors","volume":"1","author":"Besl","year":"1988","journal-title":"Mach. Vis. Appl."},{"key":"ref_13","unstructured":"B\u00fcttgen, B., Oggier, T., and Lehmann, M. (2005). 1st Range Imaging Research Day, Hilmar Ingensand and Timo Kahlmann."},{"key":"ref_14","unstructured":"J\u00e4hne, B., Hau\u00dfecker, H., and Grei\u00dfler, P. (1999). Handbook of Computer Vision and Applications, Academic Press."},{"key":"ref_15","unstructured":"J\u00e4hne, B., Hau\u00dfecker, H., and Gei\u00dfler, P. (1999). Handbook of Computer Vision and Applications, Academic Press."},{"key":"ref_16","unstructured":"Lange, R. (2000). Time-of-Flight Distance Measurement with Solid-State Image Sensors in CMOS\/CCD-Technology, University of Siegen."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1023\/A:1014573219977","article-title":"A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms","volume":"47","author":"Scharstein","year":"2002","journal-title":"Int. J. Comput. Vis."},{"key":"ref_18","unstructured":"Seitz, S., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R. (2006). IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1109\/34.206955","article-title":"A multiple-baseline stereo","volume":"15","author":"Okutomi","year":"1993","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u201cStructure-from-Motion\u201d photogrammetry: A low-cost, effective tool for geoscience applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/70.238283","article-title":"Three-dimensional reconstruction by zooming","volume":"9","author":"Lavest","year":"1993","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1016\/S0262-8856(02)00112-9","article-title":"Fast optical flow using 3D shortest path techniques","volume":"20","author":"Sun","year":"2002","journal-title":"Image Vis. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/s11263-005-4881-5","article-title":"Shape-From-Silhouette Across Time Part I: Theory and Algorithms","volume":"62","author":"Cheung","year":"2005","journal-title":"Int. J. Comput. Vis."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1023\/A:1008191222954","article-title":"A theory of shape by space carving","volume":"38","author":"Kutulakos","year":"2000","journal-title":"Int. J. Comput. Vis."},{"key":"ref_25","unstructured":"Savarese, S. (2005). Shape Reconstruction from Shadows and Reflections, California Institute of Technology."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/s11263-006-4068-8","article-title":"Shape from Texture without Boundaries","volume":"67","author":"Lobay","year":"2006","journal-title":"Int. J. Comput. Vis."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2666","DOI":"10.1016\/j.patcog.2010.03.004","article-title":"A state of the art in structured light patterns for surface profilometry","volume":"43","author":"Salvi","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_28","unstructured":"Horn, B.K.P. (1970). Shape From Shading: A Method for Obtaining the Shape of a Smooth Opaque Object From One View, Massachusetts Institute of Technology."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1117\/12.7972479","article-title":"Photometric method for determining surface orientation from multiple images","volume":"19","author":"Woodham","year":"1980","journal-title":"Opt. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/34.308479","article-title":"Shape from focus","volume":"16","author":"Nayar","year":"1994","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TPAMI.2005.43","article-title":"A Geometric Approach to Shape from Defocus","volume":"27","author":"Favaro","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_32","unstructured":"Tiziani, H.J. (1989). Ahlers, Rolf-J\u00fcrgen (Hrsg.): Bildverarbeitung: Forschen, Entwickeln, Anwenden, Techn. Akad. Esslingen."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"93","DOI":"10.5194\/isprsarchives-XL-5-W4-93-2015","article-title":"First experiences with Kinect v2 sensor for close range 3D modelling","volume":"Volume XL-5\/W4","author":"Lachat","year":"2015","journal-title":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Griepentrog, H.W., Andersen, N.A., Andersen, J.C., Blanke, M., Heinemann, O., Nielsen, J., Pedersen, S.M., Madsen, T.E., and Wulfsohn, D. (2009, January 6\u20138). Safe and Reliable\u2014Further Development of a Field Robot. 7th European Conference on Precision Agriculture (ECPA).","DOI":"10.3920\/9789086866649_103"},{"key":"ref_35","unstructured":"Shalal, N., Low, T., Mccarthy, C., and Hancock, N. (2013). Innovative Agricultural Technologies for a Sustainable Future, Society for Engineering in Agriculture (SEAg)."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.jterra.2013.03.004","article-title":"A technical review on navigation systems of agricultural autonomous off-road vehicles","volume":"50","author":"Mousazadeh","year":"2013","journal-title":"J. Terramech."},{"key":"ref_37","unstructured":"Ji, B., Zhu, W., Liu, B., Ma, C., and Li, X. (2009). Second International Symposium on Knowledge Acquisition and Modeling, IEEE."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.biosystemseng.2004.12.008","article-title":"A Stereovision-based Crop Row Detection Method for Tractor-automated Guidance","volume":"90","author":"Kise","year":"2005","journal-title":"Biosyst. Eng."},{"key":"ref_39","first-page":"1","article-title":"Autonomous guidance of a corn harvester using stereo vision","volume":"9","author":"Han","year":"2007","journal-title":"Agric. Eng. Int. CIGR Ejournal"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"287","DOI":"10.6090\/jarq.46.287","article-title":"Development of a stereo vision system to assist the operation of agricultural tractors","volume":"46","author":"Hanawa","year":"2012","journal-title":"Jpn. Agric. Res. Q. JARQ"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.compag.2010.10.012","article-title":"Stereo vision with texture learning for fault-tolerant automatic baling","volume":"75","author":"Blas","year":"2011","journal-title":"Comput. Electron. Agric."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.biosystemseng.2011.04.006","article-title":"Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields","volume":"109","author":"Wang","year":"2011","journal-title":"Biosyst. Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"12405","DOI":"10.3390\/s120912405","article-title":"Towards autonomous agriculture: Automatic ground detection using trinocular stereovision","volume":"12","author":"Reina","year":"2012","journal-title":"Sensors"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Reina, G., Milella, A., Nielsen, M., Worst, R., and Blas, M.R. (2016). Ambient awareness for agricultural robotic vehicles. Biosyst. Eng.","DOI":"10.1016\/j.biosystemseng.2015.12.010"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2389","DOI":"10.13031\/2013.20078","article-title":"Obstacle Detection Using Stereo Vision To Enhance Safety of Autonomous Machines","volume":"48","author":"Wei","year":"2005","journal-title":"Trans. Am. Soc. Agric. Eng."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.compag.2012.08.011","article-title":"Human detection for a robot tractor using omni-directional stereo vision","volume":"89","author":"Yang","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.compag.2015.02.001","article-title":"Obstacle detection in a greenhouse environment using the Kinect sensor","volume":"113","author":"Nissimov","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/S1881-8366(12)80021-8","article-title":"Development of a tractor navigation system using augmented reality","volume":"5","author":"Kaizu","year":"2012","journal-title":"Eng. Agric. Environ. Food"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.eaef.2013.12.002","article-title":"Development of a laser scanner-based navigation system for a combine harvester","volume":"7","author":"Choi","year":"2014","journal-title":"Eng. Agric. Environ. Food"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.compag.2013.07.005","article-title":"Development of a target recognition and following system for a field robot","volume":"98","author":"Yin","year":"2013","journal-title":"Comput. Electron. Agric."},{"key":"ref_51","unstructured":"CLAAS CAM PILOT. Available online: http:\/\/www.claas.de\/produkte\/easy\/lenksysteme\/optische-lenksysteme\/cam-pilot."},{"key":"ref_52","unstructured":"IFM Electronic 3D Smart Sensor\u2014Your Assistant on Mobile Machines. Available online: http:\/\/www.ifm.com."},{"key":"ref_53","unstructured":"CLAAS AUTO FILL. Available online: http:\/\/www.claas.de\/produkte\/easy\/cemos\/cemos-automatic."},{"key":"ref_54","unstructured":"New Holland IntelliFill System. Available online: http:\/\/agriculture1.newholland.com\/eu\/en-uk?market=uk."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"16688","DOI":"10.3390\/s150716688","article-title":"Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture","volume":"15","author":"Hernandez","year":"2015","journal-title":"Sensors"},{"key":"ref_56","unstructured":"Naio Technologies Oz. Available online: http:\/\/naio-technologies.com."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"20078","DOI":"10.3390\/s141120078","article-title":"A review of imaging techniques for plant phenotyping","volume":"14","author":"Li","year":"2014","journal-title":"Sensors"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.compag.2011.09.007","article-title":"A review of methods and applications of the geometric characterization of tree crops in agricultural activities","volume":"81","author":"Rosell","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.rse.2012.02.001","article-title":"Lidar sampling for large-area forest characterization: A review","volume":"121","author":"Wulder","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Vos, J., Marcelis, L., de Visser, P., Struik, P., and Evers, J. (2007). Functional\u2013Structural Plant. Modelling in Crop. Production, Springer.","DOI":"10.1007\/1-4020-6034-3"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.jfoodeng.2008.11.004","article-title":"Non-destructive technologies for fruit and vegetable size determination\u2014A review","volume":"92","author":"Moreda","year":"2009","journal-title":"J. Food Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1002\/rob.21525","article-title":"Harvesting Robots for High-value Crops: State-of-the-art Review and Challenges Ahead.","volume":"31","author":"Bac","year":"2014","journal-title":"J. Field Robot."},{"key":"ref_63","unstructured":"CROPS Intelligent Sensing and Manipulation for Sustainable Production and Harvesting of High Value Crops, Clever Robots for Crops. Available online: http:\/\/cordis.europa.eu\/result\/rcn\/90611_en.html."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.compag.2014.09.021","article-title":"In-field crop row phenotyping from 3D modeling performed using Structure from Motion","volume":"110","author":"Jay","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_65","unstructured":"Santos, T.T., and Oliveira, A.A. (2012, January 22\u201325). De Image-based 3D digitizing for plant architecture analysis and phenotyping. Proceedings of the XXV Conference on Graphics, Patterns and Images, Ouro Preto, Brazil."},{"key":"ref_66","first-page":"777","article-title":"Precision analysis of the effect of ephemeral gully erosion on vine vigour using NDVI images","volume":"13","author":"Ramos","year":"2013","journal-title":"Precis. Agric."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.eja.2014.01.004","article-title":"Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods","volume":"55","author":"Angileri","year":"2014","journal-title":"Eur. J. Agron."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"10335","DOI":"10.3390\/rs61110335","article-title":"Combined spectral and spatial modeling of corn yield based on aerial images and crop surface models acquired with an unmanned aircraft system","volume":"6","author":"Geipel","year":"2014","journal-title":"Remote. Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.compag.2014.10.003","article-title":"Vineyard yield estimation by automatic 3D bunch modelling in field conditions","volume":"110","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Moonrinta, J., Chaivivatrakul, S., Dailey, M.N., and Ekpanyapong, M. (2010, January 7\u201310). Fruit detection, tracking, and 3D reconstruction for crop mapping and yield estimation. Proceedings of the 2010 11th International Conference on Control Automation Robotics Vision, Singapore.","DOI":"10.1109\/ICARCV.2010.5707436"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Desai, P.J., Dudek, G., Khatib, O., and Kumar, V. (2013). Experimental Robotics, Springer International Publishing.","DOI":"10.1007\/978-3-319-00065-7"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Stafford, J.V. (2015). Precision Agriculture\u201915, Wageningen Academic Publishers.","DOI":"10.3920\/978-90-8686-814-8"},{"key":"ref_73","unstructured":"UMR Itap Becam. Available online: http:\/\/itap.irstea.fr\/."},{"key":"ref_74","unstructured":"Deepfield Robotics BoniRob. Available online: http:\/\/www.deepfield-robotics.com\/."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"2830","DOI":"10.3390\/s130302830","article-title":"BreedVision\u2014A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding","volume":"13","author":"Busemeyer","year":"2013","journal-title":"Sensors"},{"key":"ref_76","unstructured":"Optimalog Heliaphen. Available online: http:\/\/www.optimalog.com\/."},{"key":"ref_77","unstructured":"The University of Sidney Ladybird. Available online: http:\/\/www.acfr.usyd.edu.au\/."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Koenderink, N.J.J.P., Wigham, M., Golbach, F., Otten, G., Gerlich, R., and van de Zedde, H.J. (2009, January 6\u20138). MARVIN: High speed 3D imaging for seedling classification. Proceedings of the European Conference on Precision Agriculture, Wageningen, The Netherlands.","DOI":"10.3920\/9789086866649_034"},{"key":"ref_79","unstructured":"INRA PhenoArch. Available online: http:\/\/www.inra.fr\/."},{"key":"ref_80","unstructured":"Polder, G., Lensink, D., and Veldhuisen, B. (2013). Phenodays, Wageningen UR."},{"key":"ref_81","unstructured":"Phenospex PlantEye. Available online: https:\/\/phenospex.com\/."},{"key":"ref_82","unstructured":"Aleny\u00e0, G., Dellen, B., Foix, S., and Torras, C. (2012). IROS Workshop on Agricultural Robotics: Enabling Safe, Efficient, Affordable Robots for Food Production, IEEE\/RSJ."},{"key":"ref_83","unstructured":"Alci Visionics & Robotics Sampling Automation System: SAS. Available online: http:\/\/www.alci.fr\/."},{"key":"ref_84","unstructured":"LemnaTec Scanalyzer. Available online: http:\/\/www.lemnatec.com\/."},{"key":"ref_85","unstructured":"Polder, G., van der Heijden, G.W.A.M., Glasbey, C.A., Song, Y., and Dieleman, J.A. (2009, January 10\u201312). Spy-See\u2014Advanced vision system for phenotyping in greenhouses. Proceedings of the MINET Conference: Measurement, Sensation and Cognition, London, UK."},{"key":"ref_86","unstructured":"BLUE RIVER TECHNOLOGY Zea. Available online: http:\/\/www.bluerivert.com\/."},{"key":"ref_87","unstructured":"van Straten, G., Bot, G.P., van Meurs, W.T.M., and Marcelis, L.F. (2005). Acta Horticulturae 691, ISHS."},{"key":"ref_88","first-page":"17","article-title":"Reverse Volumetric Intersection (RVI), a method to generate 3D images of plants using multiple views","volume":"40","author":"Hemming","year":"2005","journal-title":"Bornimer Agrartechn. Berichte"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Tabb, A. (2013, January 23\u201328). Shape from Silhouette probability maps: Reconstruction of thin objects in the presence of silhouette extraction and calibration error. Proceedings of the 2013 IEEE Conference Computer Vision Pattern Recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.28"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"5040","DOI":"10.3390\/s130405040","article-title":"3D image acquisition system based on shape from focus technique","volume":"13","author":"Billiot","year":"2013","journal-title":"Sensors"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1002\/rob.20293","article-title":"Corn plant sensing using real-time stereo vision","volume":"26","author":"Jin","year":"2009","journal-title":"J. F. Robot."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1016\/S2095-3119(12)60116-6","article-title":"Identify Plant Drought Stress by 3D-Based Image","volume":"11","author":"Zhao","year":"2012","journal-title":"J. Integr. Agric."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s11119-010-9205-2","article-title":"Weed detection in 3D images","volume":"12","author":"Piron","year":"2011","journal-title":"Precis. Agric."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1590\/S1413-70542004000100016","article-title":"Fruit profilometry based on shadow Moir\u00e9 techniques","volume":"28","author":"Lino","year":"2001","journal-title":"Ci\u00eanc. Agrotechnol."},{"key":"ref_95","unstructured":"\u0160eatovi\u0107, D., Kuttere, H., Anken, T., and Holpp, M. (2009, January 6\u20137). Automatic weed detection in grassland. Proceedings of the 67th International Conference on Agricultural Engineering, Hanover, Germany."},{"key":"ref_96","unstructured":"Wolff, A. (2012). Ph\u00e4notypisierung in Feldbest\u00e4nden Mittels 3D-Lichtschnitt-Technik, Strube Research GmbH."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.compag.2007.07.002","article-title":"Creating a panoramic field image using multi-spectral stereovision system","volume":"60","author":"Kise","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.biosystemseng.2004.11.013","article-title":"Creation of three-dimensional crop maps based on aerial stereoimages","volume":"90","author":"Zhang","year":"2005","journal-title":"Biosyst. Eng."},{"key":"ref_99","unstructured":"Berghmans, F., Mignani, A.G., and de Moor, P. Multiwavelenght laser line profile sensing for agricultural crop. Proceedings SPIE 9141 Optical Sensing and Detection III."},{"key":"ref_100","unstructured":"Guthrie, A.G., Botha, T.R., and Els, P.S. (2014, January 22\u201325). 3D computer vision contact patch measurements inside off-road vehicles tyres. Proceedings of the 18th International Conference of the ISTVS, Seul, Korea."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.13031\/2013.29118","article-title":"3D surface reconstruction and analysis in automated apple stem-end\/calyx identification","volume":"52","author":"Jiang","year":"2009","journal-title":"Trans. ASABE"},{"key":"ref_102","unstructured":"Ruckelshausen, A., Meyer-Aurich, A., Rath, T., Recke, G., and Theuvsen, B. (2016). Intelligente Systeme\u2014Stand Der Technik Und Neue M\u00f6glichkeiten, Gesellschaft f\u00fcr Informatik e.V. (GI)."},{"key":"ref_103","first-page":"153","article-title":"Phenotyping large tomato plants in the greenhouse usig a 3D light-field camera","volume":"1","author":"Polder","year":"2014","journal-title":"ASABE CSBE\/SCGAB Annu. Int. Meet."},{"key":"ref_104","unstructured":"Vision Robotics Proto Prune. Available online: http:\/\/www.visionrobotics.com\/."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Stafford, J. (2013). Precision Agriculture\u201913, Wageningen Academic Publishers.","DOI":"10.3920\/978-90-8686-778-3"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"17077","DOI":"10.3390\/rs71215870","article-title":"3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds","volume":"7","author":"Garrido","year":"2015","journal-title":"Remote Sens."},{"key":"ref_107","unstructured":"Weiss, U., Biber, P., Laible, S., Bohlmann, K., Zell, A., and Gmbh, R.B. (2010). Machine Learning and Applications, IEEE."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.robot.2011.02.011","article-title":"Plant detection and mapping for agricultural robots using a 3D LIDAR sensor","volume":"59","author":"Weiss","year":"2011","journal-title":"Robot. Auton. Syst."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.biosystemseng.2008.10.003","article-title":"Estimation of the crop density of small grains using LiDAR sensors","volume":"102","author":"Saeys","year":"2009","journal-title":"Biosyst. Eng."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.compag.2011.12.011","article-title":"Automatic inter-plant spacing sensing at early growth stages using a 3D vision sensor","volume":"82","author":"Nakarmi","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_111","unstructured":"Adhikari, B., and Karkee, M. (2011). 3D Reconstruction of apple trees for mechanical pruning. ASABE Annu. Int. Meet., 7004."},{"key":"ref_112","unstructured":"Gongal, A., Amatya, S., and Karkee, M. (2014, January 13\u201316). Identification of repetitive apples for improved crop-load estimation with dual-side imaging. Proceedings of the ASABE and CSBE\/SCGAB Annual International Meeting, Montreal, QC, Canada."},{"key":"ref_113","unstructured":"Tanaka, T., Kataoka, T., Ogura, H., and Shibata, Y. (2014, January 22\u201325). Evaluation of rotary tillage performance using resin-made blade by 3D-printer. Proceedings of the 18th International Conference of the ISTVS, Seoul, Korea."},{"key":"ref_114","unstructured":"Ruckelshausen, A., Meyer-Aurich, A., Rath, T., Recke, G., and Theuvsen, B. (2016). Intelligente Systeme\u2014Stand der Technik und neue M\u00f6glichkeiten, Gesellschaft f\u00fcr Informatik e.V. (GI)."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"9467","DOI":"10.3390\/s111009467","article-title":"Optical sensing method for screening disease in melon seeds by using optical coherence tomography","volume":"11","author":"Lee","year":"2011","journal-title":"Sensors"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1007\/s13580-012-0071-x","article-title":"Application of optical coherence tomography to detect Cucumber green mottle mosaic virus (CGMMV) infected cucumber seed","volume":"53","author":"Lee","year":"2012","journal-title":"Hortic. Environ. Biotechnol."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"2624","DOI":"10.1364\/AO.46.002624","article-title":"Multiwavelength electronic speckle pattern interferometry for surface shape measurement","volume":"46","author":"Barbosa","year":"2007","journal-title":"Appl. Opt."},{"key":"ref_118","first-page":"370","article-title":"Blooming processes in flowers studied by dynamic electronic speckle pattern interferometry (DESPI)","volume":"10","author":"Madjarova","year":"2003","journal-title":"Opt. Soc. Jpn."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1104\/pp.60.1.30","article-title":"Holographic interferometric measurement of motions in mature plants","volume":"60","author":"Fox","year":"1977","journal-title":"Plant. Physiol."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1186\/2193-1801-3-89","article-title":"An optical interferometric technique for assessing ozone induced damage and recovery under cumulative exposures for a Japanese rice cultivar","volume":"3","author":"Thilakarathne","year":"2014","journal-title":"Springerplus"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.compag.2014.11.004","article-title":"Development of a teat sensing system for robotic milking by combining thermal imaging and stereovision technique","volume":"110","author":"Esmonde","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Akhloufi, M. (2014, January 2). 3D vision system for intelligent milking robot automation. Proceedings of the Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, San Francisco, CA, USA.","DOI":"10.1117\/12.2046072"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/0168-1699(91)90006-U","article-title":"Development and application of computer vision systems for use in livestock production","volume":"6","author":"Schofield","year":"1991","journal-title":"Comput. Electron. Agric."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1108\/02602280410545948","article-title":"A stereo imaging system for the metric 3D recovery of porcine surface anatomy","volume":"24","author":"Ju","year":"2004","journal-title":"Sens. Rev."},{"key":"ref_125","unstructured":"Hinz, A. (2012). Objective Grading and Video Image Technology, E+V Technology GmbH & Co. KG."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.compag.2013.11.005","article-title":"Comparison of a three-dimensional and two-dimensional camera system for automated measurement of back posture in dairy cows","volume":"100","author":"Viazzi","year":"2014","journal-title":"Comput. Electron. Agric."},{"key":"ref_127","first-page":"222","article-title":"Three-Dimensional Shape Measurement System for Black Cattle Using KINECT Sensor","volume":"7","author":"Kawasue","year":"2013","journal-title":"Int. J. Circuits, Syst. Signal. Process."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.compag.2014.12.020","article-title":"A preliminarily study for predicting body weight and milk properties in lactating Holstein cows using a three-dimensional camera system","volume":"111","author":"Kuzuhara","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.compag.2014.01.018","article-title":"A low-cost stereovision system to estimate size and weight of live sheep","volume":"103","author":"Menesatti","year":"2014","journal-title":"Comput. Electron. Agric."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.compag.2015.09.019","article-title":"Comparison between manual and stereovision body traits measurements of Lipizzan horses","volume":"118","author":"Pallottino","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.compag.2004.05.003","article-title":"Extracting the three-dimensional shape of live pigs using stereo photogrammetry","volume":"44","author":"Wu","year":"2004","journal-title":"Comput. Electron. Agric."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.compag.2012.07.010","article-title":"The use of computer vision technologies in aquaculture\u2014A review","volume":"88","author":"Zion","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_133","unstructured":"Ingram, L., Cronin, G., and Sutton, L. A robot amongst the herd: Remote detection and tracking of cows. Proceedings of the 4th Australian and New Zealand spatially enabled livestock management symposium."},{"key":"ref_134","unstructured":"Belbachir, A.N., Ieee, M., Schraml, S., Mayerhofer, M., and Hofst\u00e4tter, M. (2014). IEEE Conference on Computer Vision and Pattern Recognition, IEEE."},{"key":"ref_135","unstructured":"Velodyne Puck VLP-16. Available online: http:\/\/velodynelidar.com\/."},{"key":"ref_136","unstructured":"Frey, V. (2010). PMD Cameras for Automotive & Outdoor Applications, IFM Electronic."},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.isprsjprs.2013.11.012","article-title":"Indoor and outdoor depth imaging of leaves with time-of-flight and stereo vision sensors: Analysis and comparison","volume":"88","author":"Kazmi","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_138","first-page":"93","article-title":"Usability of 3D time-of-flight cameras for automatic plant phenotyping","volume":"69","author":"Klose","year":"2011","journal-title":"Bornimer Agrartech. Berichte"},{"key":"ref_139","unstructured":"Odos Imaging Real.iZ VS-1000 High-Resolution Time-of-Flight. Available online: http:\/\/www.odos-imaging.com\/."}],"updated-by":[{"updated":{"date-parts":[[2016,4,29]],"date-time":"2016-04-29T00:00:00Z","timestamp":1461888000000},"DOI":"10.3390\/s16071039","type":"correction","label":"Correction"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/5\/618\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,4]],"date-time":"2024-06-04T21:42:17Z","timestamp":1717537337000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/5\/618"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,29]]},"references-count":139,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2016,5]]}},"alternative-id":["s16050618"],"URL":"https:\/\/doi.org\/10.3390\/s16050618","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,4,29]]}}}