{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T18:07:47Z","timestamp":1761156467470,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,3,21]],"date-time":"2018-03-21T00:00:00Z","timestamp":1521590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61501009, 61771031 and 61371134"],"award-info":[{"award-number":["61501009, 61771031 and 61371134"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFB0501300, 2016YFB0501302"],"award-info":[{"award-number":["2016YFB0501300, 2016YFB0501302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Aerospace Science and Technology Innovation Fund of CASC"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.<\/jats:p>","DOI":"10.3390\/s18040933","type":"journal-article","created":{"date-parts":[[2018,3,22]],"date-time":"2018-03-22T05:14:55Z","timestamp":1521695695000},"page":"933","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Robust Spacecraft Component Detection in Point Clouds"],"prefix":"10.3390","volume":"18","author":[{"given":"Quanmao","family":"Wei","sequence":"first","affiliation":[{"name":"Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China"},{"name":"Beijing Key Laboratory of Digital Media, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiguo","family":"Jiang","sequence":"additional","affiliation":[{"name":"Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China"},{"name":"Beijing Key Laboratory of Digital Media, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1981-8307","authenticated-orcid":false,"given":"Haopeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China"},{"name":"Beijing Key Laboratory of Digital Media, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Cefola, P.J., and Alfriend, K.T. (2006, January 21\u201324). Sixth US\/Russian Space Surveillance Workshop. Proceedings of the AIAA\/AAS Astrodynamics Specialist Conference and Exhibit, Keystone, CO, USA.","DOI":"10.2514\/6.2006-6673"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/S1000-9361(09)60255-7","article-title":"Full-viewpoint 3D Space Object Recognition Based on Kernel Locality Preserving Projections","volume":"23","author":"Meng","year":"2010","journal-title":"Chin. J. Aeronaut."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.actaastro.2013.05.017","article-title":"Vision-based pose estimation for cooperative space objects","volume":"91","author":"Zhang","year":"2013","journal-title":"Acta Astronaut."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1016\/j.cja.2014.03.021","article-title":"Multi-view space object recognition and pose estimation based on kernel regression","volume":"27","author":"Zhang","year":"2014","journal-title":"Chin. J. Aeronaut."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1109\/TAES.2014.130744","article-title":"Satellite recognition and pose estimation using Homeomorphic Manifold Analysis","volume":"51","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"339","DOI":"10.5194\/isprs-archives-XLII-2-W3-339-2017","article-title":"A Review of Point Clouds Segmentation and Classification Algorithms","volume":"42","author":"Grilli","year":"2017","journal-title":"ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1002\/rob.20420","article-title":"Space shuttle testing of the TriDAR 3D rendezvous and docking sensor","volume":"29","author":"Ruel","year":"2012","journal-title":"J. Field Robot."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s13218-014-0297-0","article-title":"Autonomous navigation for on-orbit servicing","volume":"28","author":"Benninghoff","year":"2014","journal-title":"KI-K\u00fcnstliche Intell."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhang, H., Wei, Q., and Jiang, Z. (2016). Pose Estimation of Space Objects Based on Hybrid Feature Matching of Contour Points. Advances in Image and Graphics Technologies, Proceedings of the 11th Chinese Conference, IGTA 2016, Beijing, China, 8\u20139 July 2016, Springer.","DOI":"10.1007\/978-981-10-2260-9_21"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/TAES.2017.2650785","article-title":"Pose Estimation for Spacecraft Relative Navigation Using Model-Based Algorithms","volume":"53","author":"Opromolla","year":"2017","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_11","unstructured":"Tan, W., Liu, H., Dong, Z., Zhang, G., and Bao, H. (2013, January 1\u20134). Robust monocular SLAM in dynamic environments. Proceedings of the 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Adelaide, Australia."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/TPAMI.2017.2658577","article-title":"Direct Sparse Odometry","volume":"40","author":"Engel","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s11263-007-0107-3","article-title":"Modeling the World from Internet Photo Collections","volume":"80","author":"Snavely","year":"2008","journal-title":"Int. J. Comput. Vis."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, H., Wei, Q., and Jiang, Z. (2017). 3D Reconstruction of Space Objects from Multi-Views by a Visible Sensor. Sensors, 17.","DOI":"10.3390\/s17071689"},{"key":"ref_15","first-page":"33","article-title":"Recognising structure in laser scanner point clouds","volume":"46","author":"Vosselman","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Li, Y., Wu, X., Chrysathou, Y., Sharf, A., Cohen-Or, D., and Mitra, N.J. (2011). GlobFit: Consistently fitting primitives by discovering global relations. ACM SIGGRAPH 2011 Papers, Proceedings of the SIGGRAPH \u201911, Vancouver, BC, Canada, 7\u201311 August 2011, ACM.","DOI":"10.1145\/1964921.1964947"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1016\/j.patcog.2014.12.020","article-title":"Real-time detection of planar regions in unorganized point clouds","volume":"48","author":"Limberger","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4199","DOI":"10.1109\/JSTARS.2014.2349003","article-title":"A methodology for automated segmentation and reconstruction of urban 3-D buildings from ALS point clouds","volume":"7","author":"Chen","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3684","DOI":"10.1080\/01431161.2017.1302112","article-title":"Roof plane extraction from airborne lidar point clouds","volume":"38","author":"Cao","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","first-page":"60","article-title":"Efficient hough transform for automatic detection of cylinders in point clouds","volume":"3","author":"Rabbani","year":"2005","journal-title":"ISPRS WG III\/3, III\/4"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Qiu, R., Zhou, Q.Y., and Neumann, U. (2014). Pipe-Run Extraction and Reconstruction from Point Clouds. Computer Vision\u2014ECCV 2014, Proceedings of the 13th European Conference, Zurich, Switzerland, 6\u201312 September 2014, Springer International Publishing.","DOI":"10.1007\/978-3-319-10578-9_2"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Pang, G., Qiu, R., Huang, J., You, S., and Neumann, U. (2015, January 18\u201322). Automatic 3D industrial point cloud modeling and recognition. Proceedings of the 2015 14th IAPR International Conference on Machine Vision Applications (MVA), Tokyo, Japan.","DOI":"10.1109\/MVA.2015.7153124"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/3DRes.02(2011)3","article-title":"The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design","volume":"2","author":"Borrmann","year":"2011","journal-title":"3D Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for Point-Cloud Shape Detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_25","unstructured":"Yang, M.Y., and F\u00f6rstner, W. (2010, January 9\u201311). Plane detection in point cloud data. Proceedings of the 2nd International Conference on Machine Control Guidance, Bonn, Germany."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s11263-011-0474-7","article-title":"Energy-Based Geometric Multi-model Fitting","volume":"97","author":"Isack","year":"2012","journal-title":"Int. J. Comput. Vis."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., and Liu, D. (2016). Energy-Based Multi-plane Detection from 3D Point Clouds. Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science, Springer International Publishing.","DOI":"10.1007\/978-3-319-46672-9"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11263-011-0437-z","article-title":"Fast Approximate Energy Minimization with Label Costs","volume":"96","author":"Delong","year":"2012","journal-title":"Int. J. Comput. Vis."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1109\/34.969114","article-title":"Fast approximate energy minimization via graph cuts","volume":"23","author":"Boykov","year":"2001","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wei, Q., Jiang, Z., Zhang, H., and Nie, S. (July, January 30). Spacecraft Component Detection in Point Clouds. Proceedings of the 12th Chinese Conference on Advances in Image and Graphics Technologies, IGTA 2017, Beijing, China.","DOI":"10.1007\/978-981-10-7389-2_21"},{"key":"ref_31","unstructured":"Eberly, D.H. (2017, November 18). Geometric Tools. Available online: https:\/\/www.geometrictools.com."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Knapitsch, A., Park, J., Zhou, Q.Y., and Koltun, V. (2017). Tanks and Temples: Benchmarking Large-Scale Scene Reconstruction. ACM Trans. Graph., 36.","DOI":"10.1145\/3072959.3073599"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sch\u00f6ps, T., Sch\u00f6nberger, J.L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., and Geiger, A. (2017, January 21\u201326). A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos. Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.272"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/933\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:58:01Z","timestamp":1760194681000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/933"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,21]]},"references-count":33,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["s18040933"],"URL":"https:\/\/doi.org\/10.3390\/s18040933","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,3,21]]}}}