{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:32:10Z","timestamp":1772119930483,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1007\/s11760-024-03056-w","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T04:02:18Z","timestamp":1709265738000},"page":"4085-4102","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Depth grid-based local description for 3D point clouds"],"prefix":"10.1007","volume":"18","author":[{"given":"Jiming","family":"Sa","sequence":"first","affiliation":[]},{"given":"Xuecheng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yuyan","family":"Song","sequence":"additional","affiliation":[]},{"given":"Liwei","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Yechen","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,1]]},"reference":[{"key":"3056_CR1","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1109\/34.765655","volume":"21","author":"AE Johnson","year":"1999","unstructured":"Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Trans. Pattern Anal. Mach. Intell. 21, 433\u2013449 (1999). https:\/\/doi.org\/10.1109\/34.765655","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3056_CR2","doi-asserted-by":"publisher","first-page":"1252","DOI":"10.1016\/j.patrec.2007.02.009","volume":"28","author":"H Chen","year":"2007","unstructured":"Chen, H., Bhanu, B.: 3D free-form object recognition in range images using local surface patches. Pattern Recognit. Lett. 28, 1252\u20131262 (2007). https:\/\/doi.org\/10.1016\/j.patrec.2007.02.009","journal-title":"Pattern Recognit. Lett."},{"key":"3056_CR3","doi-asserted-by":"crossref","unstructured":"Rusu, R.B., Blodow, N., Beetz, M.: Fast point feature histograms (FPFH) for 3D registration. In: 2009 IEEE International Conference on Robotics and Automation, pp. 3212\u20133217 (2009)","DOI":"10.1109\/ROBOT.2009.5152473"},{"key":"3056_CR4","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s11263-013-0627-y","volume":"105","author":"Y Guo","year":"2013","unstructured":"Guo, Y., Sohel, F., Bennamoun, M., Lu, M., Wan, J.: Rotational projection statistics for 3D local surface description and object recognition. Int. J. Comput. Vis. 105, 63\u201386 (2013). https:\/\/doi.org\/10.1007\/s11263-013-0627-y","journal-title":"Int. J. Comput. Vis."},{"key":"3056_CR5","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.patcog.2016.11.019","volume":"65","author":"J Yang","year":"2017","unstructured":"Yang, J., Zhang, Q., Xiao, Y., Cao, Z.: TOLDI: an effective and robust approach for 3D local shape description. Pattern Recognit. 65, 175\u2013187 (2017). https:\/\/doi.org\/10.1016\/j.patcog.2016.11.019","journal-title":"Pattern Recognit."},{"key":"3056_CR6","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.ins.2014.09.015","volume":"293","author":"Y Guo","year":"2015","unstructured":"Guo, Y., Sohel, F., Bennamoun, M., Wan, J., Lu, M.: A novel local surface feature for 3D object recognition under clutter and occlusion. Inf. Sci. 293, 196\u2013213 (2015). https:\/\/doi.org\/10.1016\/j.ins.2014.09.015","journal-title":"Inf. Sci."},{"key":"3056_CR7","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.cviu.2014.04.011","volume":"125","author":"S Salti","year":"2014","unstructured":"Salti, S., Tombari, F., Di Stefano, L.: SHOT: unique signatures of histograms for surface and texture description. Comput. Vis. Image Underst. 125, 251\u2013264 (2014). https:\/\/doi.org\/10.1016\/j.cviu.2014.04.011","journal-title":"Comput. Vis. Image Underst."},{"key":"3056_CR8","doi-asserted-by":"crossref","unstructured":"Deng, H., Birdal, T., Ilic, S.: PPFNet: global context aware local features for robust 3D point matching. Presented at the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)","DOI":"10.1109\/CVPR.2018.00028"},{"key":"3056_CR9","doi-asserted-by":"crossref","unstructured":"Deng, H., Birdal, T., Ilic, S.: PPF-FoldNet: unsupervised learning of rotation invariant 3D local descriptors. Presented at the Proceedings of the European Conference on Computer Vision (ECCV) (2018)","DOI":"10.1007\/978-3-030-01228-1_37"},{"key":"3056_CR10","doi-asserted-by":"publisher","first-page":"3368","DOI":"10.1109\/TVCG.2022.3160005","volume":"29","author":"L Li","year":"2023","unstructured":"Li, L., Fu, H., Ovsjanikov, M.: WSDesc: weakly supervised 3D local descriptor learning for point cloud registration. IEEE Trans. Vis. Comput. Graph. 29, 3368\u20133379 (2023). https:\/\/doi.org\/10.1109\/TVCG.2022.3160005","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"3056_CR11","doi-asserted-by":"crossref","unstructured":"Zhong, Y.: Intrinsic shape signatures: a shape descriptor for 3D object recognition. In: 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pp. 689\u2013696 (2009)","DOI":"10.1109\/ICCVW.2009.5457637"},{"key":"3056_CR12","unstructured":"Steder, B., Rusu, R.B., Konolige, K., Burgard, W.: NARF: 3D range image features for object recognition"},{"key":"3056_CR13","doi-asserted-by":"publisher","first-page":"1501","DOI":"10.1007\/s10514-016-9612-y","volume":"41","author":"SM Prakhya","year":"2017","unstructured":"Prakhya, S.M., Liu, B., Lin, W., Jakhetiya, V., Guntuku, S.C.: B-SHOT: a binary 3D feature descriptor for fast keypoint matching on 3D point clouds. Auton. Robots 41, 1501\u20131520 (2017). https:\/\/doi.org\/10.1007\/s10514-016-9612-y","journal-title":"Auton. Robots"},{"key":"3056_CR14","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1007\/978-3-642-04667-4_17","volume-title":"Computer Vision Systems","author":"J Behley","year":"2009","unstructured":"Behley, J., Steinhage, V.: Generation of 3D city models using domain-specific information fusion. In: Fritz, M., Schiele, B., Piater, J.H. (eds.) Computer Vision Systems, pp. 164\u2013173. Springer, Berlin (2009)"},{"key":"3056_CR15","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/978-3-319-54193-8_20","volume-title":"Computer Vision\u2014ACCV 2016","author":"K Tang","year":"2017","unstructured":"Tang, K., Song, P., Chen, X.: Signature of geometric centroids for 3D local shape description and partial shape matching. In: Lai, S.-H., Lepetit, V., Nishino, K., Sato, Y. (eds.) Computer Vision\u2014ACCV 2016, pp. 311\u2013326. Springer, Cham (2017)"},{"key":"3056_CR16","doi-asserted-by":"crossref","unstructured":"Rusu, R.B., Blodow, N., Marton, Z.C., Beetz, M.: Aligning point cloud views using persistent feature histograms. In: 2008 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 3384\u20133391 (2008)","DOI":"10.1109\/IROS.2008.4650967"},{"key":"3056_CR17","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1016\/j.robot.2015.09.027","volume":"75","author":"K Berker Logoglu","year":"2016","unstructured":"Berker Logoglu, K., Kalkan, S., Temizel, A.: CoSPAIR: colored histograms of spatial concentric surflet-pairs for 3D object recognition. Robot. Auton. Syst. 75, 558\u2013570 (2016). https:\/\/doi.org\/10.1016\/j.robot.2015.09.027","journal-title":"Robot. Auton. Syst."},{"key":"3056_CR18","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.ins.2020.02.004","volume":"520","author":"T Sun","year":"2020","unstructured":"Sun, T., Liu, G., Liu, S., Meng, F., Zeng, L., Li, R.: An efficient and compact 3D local descriptor based on the weighted height image. Inf. Sci. 520, 209\u2013231 (2020). https:\/\/doi.org\/10.1016\/j.ins.2020.02.004","journal-title":"Inf. Sci."},{"key":"3056_CR19","doi-asserted-by":"publisher","first-page":"107691","DOI":"10.1016\/j.patcog.2020.107691","volume":"111","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Li, C., Guo, B., Guo, C., Zhang, S.: KDD: a kernel density based descriptor for 3D point clouds. Pattern Recognit. 111, 107691 (2021). https:\/\/doi.org\/10.1016\/j.patcog.2020.107691","journal-title":"Pattern Recognit."},{"key":"3056_CR20","doi-asserted-by":"publisher","first-page":"104339","DOI":"10.1016\/j.imavis.2021.104339","volume":"117","author":"L Hao","year":"2022","unstructured":"Hao, L., Wang, H.: Geometric feature statistics histogram for both real-valued and binary feature representations of 3D local shape. Image Vis. Comput. 117, 104339 (2022). https:\/\/doi.org\/10.1016\/j.imavis.2021.104339","journal-title":"Image Vis. Comput."},{"key":"3056_CR21","doi-asserted-by":"publisher","first-page":"8818","DOI":"10.1364\/AO.437477","volume":"60","author":"J Wang","year":"2021","unstructured":"Wang, J., Wu, B., Kang, J.: Registration of 3D point clouds using a local descriptor based on grid point normal. Appl. Opt. 60, 8818\u20138828 (2021). https:\/\/doi.org\/10.1364\/AO.437477","journal-title":"Appl. Opt."},{"key":"3056_CR22","doi-asserted-by":"publisher","first-page":"1378","DOI":"10.1177\/0278364911415897","volume":"30","author":"Z-C Marton","year":"2011","unstructured":"Marton, Z.-C., Pangercic, D., Blodow, N., Beetz, M.: Combined 2D\u20133D categorization and classification for multimodal perception systems. Int. J. Robot. Res. 30, 1378\u20131402 (2011). https:\/\/doi.org\/10.1177\/0278364911415897","journal-title":"Int. J. Robot. Res."},{"key":"3056_CR23","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.cviu.2015.06.008","volume":"142","author":"D Fehr","year":"2016","unstructured":"Fehr, D., Beksi, W.J., Zermas, D., Papanikolopoulos, N.: Covariance based point cloud descriptors for object detection and recognition. Comput. Vis. Image Underst. 142, 80\u201393 (2016). https:\/\/doi.org\/10.1016\/j.cviu.2015.06.008","journal-title":"Comput. Vis. Image Underst."},{"key":"3056_CR24","doi-asserted-by":"crossref","unstructured":"Beksi, W.J., Papanikolopoulos, N.: Object classification using dictionary learning and RGB-D covariance descriptors. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 1880\u20131885 (2015)","DOI":"10.1109\/ICRA.2015.7139443"},{"key":"3056_CR25","doi-asserted-by":"crossref","unstructured":"Zhao, G., Yuan, J., Dang, K.: Height gradient histogram (HIGH) for 3D scene labeling. In: 2014 2nd International Conference on 3D Vision, pp. 569\u2013576 (2014)","DOI":"10.1109\/3DV.2014.16"},{"key":"3056_CR26","doi-asserted-by":"publisher","first-page":"107272","DOI":"10.1016\/j.patcog.2020.107272","volume":"103","author":"H Zhao","year":"2020","unstructured":"Zhao, H., Tang, M., Ding, H.: HoPPF: a novel local surface descriptor for 3D object recognition. Pattern Recognit. 103, 107272 (2020). https:\/\/doi.org\/10.1016\/j.patcog.2020.107272","journal-title":"Pattern Recognit."},{"key":"3056_CR27","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.ins.2019.04.020","volume":"512","author":"B Zhao","year":"2020","unstructured":"Zhao, B., Xi, J.: Efficient and accurate 3D modeling based on a novel local feature descriptor. Inf. Sci. 512, 295\u2013314 (2020). https:\/\/doi.org\/10.1016\/j.ins.2019.04.020","journal-title":"Inf. Sci."},{"key":"3056_CR28","doi-asserted-by":"publisher","first-page":"3229","DOI":"10.3390\/s21093229","volume":"21","author":"L Wu","year":"2021","unstructured":"Wu, L., Zhong, K., Li, Z., Zhou, M., Hu, H., Wang, C., Shi, Y.: PPTFH: robust local descriptor based on point-pair transformation features for 3D surface matching. Sensors 21, 3229 (2021). https:\/\/doi.org\/10.3390\/s21093229","journal-title":"Sensors"},{"key":"3056_CR29","doi-asserted-by":"crossref","unstructured":"Li, L., Zhu, S., Fu, H., Tan, P., Tai, C.-L.: End-to-end learning local multi-view descriptors for 3D point clouds. Presented at the Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00199"},{"key":"3056_CR30","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.cviu.2017.02.004","volume":"160","author":"J Yang","year":"2017","unstructured":"Yang, J., Zhang, Q., Xian, K., Xiao, Y., Cao, Z.: Rotational contour signatures for both real-valued and binary feature representations of 3D local shape. Comput. Vis. Image Underst. 160, 133\u2013147 (2017). https:\/\/doi.org\/10.1016\/j.cviu.2017.02.004","journal-title":"Comput. Vis. Image Underst."},{"key":"3056_CR31","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14, 239\u2013256 (1992). https:\/\/doi.org\/10.1109\/34.121791","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3056_CR32","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/0262-8856(92)90066-C","volume":"10","author":"Y Chen","year":"1992","unstructured":"Chen, Y., Medioni, G.: Object modelling by registration of multiple range images. Image Vis. Comput. 10, 145\u2013155 (1992). https:\/\/doi.org\/10.1016\/0262-8856(92)90066-C","journal-title":"Image Vis. Comput."},{"key":"3056_CR33","doi-asserted-by":"publisher","first-page":"2241","DOI":"10.1109\/TPAMI.2015.2513405","volume":"38","author":"J Yang","year":"2016","unstructured":"Yang, J., Li, H., Campbell, D., Jia, Y.: Go-ICP: a globally optimal solution to 3D ICP point-set registration. IEEE Trans. Pattern Anal. Mach. Intell. 38, 2241\u20132254 (2016). https:\/\/doi.org\/10.1109\/TPAMI.2015.2513405","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3056_CR34","doi-asserted-by":"publisher","first-page":"103992","DOI":"10.1016\/j.autcon.2021.103992","volume":"133","author":"T Xia","year":"2022","unstructured":"Xia, T., Yang, J., Chen, L.: Automated semantic segmentation of bridge point cloud based on local descriptor and machine learning. Autom. Constr. 133, 103992 (2022). https:\/\/doi.org\/10.1016\/j.autcon.2021.103992","journal-title":"Autom. Constr."},{"key":"3056_CR35","doi-asserted-by":"publisher","first-page":"107446","DOI":"10.1016\/j.patcog.2020.107446","volume":"107","author":"M Feng","year":"2020","unstructured":"Feng, M., Zhang, L., Lin, X., Gilani, S.Z., Mian, A.: Point attention network for semantic segmentation of 3D point clouds. Pattern Recognit. 107, 107446 (2020). https:\/\/doi.org\/10.1016\/j.patcog.2020.107446","journal-title":"Pattern Recognit."},{"key":"3056_CR36","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.measurement.2018.05.029","volume":"125","author":"E Ozbay","year":"2018","unstructured":"Ozbay, E., Cinar, A., Guler, Z.: A hybrid method for skeleton extraction on Kinect sensor data: combination of L1-Median and Laplacian shrinking algorithms. Measurement 125, 535\u2013544 (2018). https:\/\/doi.org\/10.1016\/j.measurement.2018.05.029","journal-title":"Measurement"},{"key":"3056_CR37","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1007\/s11263-012-0545-4","volume":"102","author":"F Tombari","year":"2013","unstructured":"Tombari, F., Salti, S., Di Stefano, L.: Performance evaluation of 3D keypoint detectors. Int. J. Comput. Vis. 102, 198\u2013220 (2013). https:\/\/doi.org\/10.1007\/s11263-012-0545-4","journal-title":"Int. J. Comput. Vis."},{"key":"3056_CR38","doi-asserted-by":"crossref","unstructured":"Drost, B., Ulrich, M., Bergmann, P., Hartinger, P., Steger, C.: Introducing MVTec ITODD\u2014a dataset for 3D object recognition in industry. Presented at the Proceedings of the IEEE International Conference on Computer Vision Workshops (2017)","DOI":"10.1109\/ICCVW.2017.257"},{"key":"3056_CR39","doi-asserted-by":"publisher","first-page":"1584","DOI":"10.1109\/TPAMI.2006.213","volume":"28","author":"AS Mian","year":"2006","unstructured":"Mian, A.S., Bennamoun, M., Owens, R.: Three-dimensional model-based object recognition and segmentation in cluttered scenes. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1584\u20131601 (2006). https:\/\/doi.org\/10.1109\/TPAMI.2006.213","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"3056_CR40","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1115\/1.4048219","volume":"143","author":"I Gonzalez-Perez","year":"2021","unstructured":"Gonzalez-Perez, I., Guirao-Saura, P.L., Fuentes-Aznar, A.: Application of the bilateral filter for the reconstruction of spiral bevel gear tooth surfaces from point clouds[J]. J. Mech. Des. 143(5), 159\u2013162 (2021)","journal-title":"J. Mech. Des."},{"key":"3056_CR41","doi-asserted-by":"publisher","first-page":"101910","DOI":"10.1016\/j.cagd.2020.101910","volume":"81","author":"H Li","year":"2020","unstructured":"Li, H., Su, Z., Li, N., Liu, X., Wang, S., Luo, Z.: Non-rigid 3D shape retrieval based on multi-scale graphical image and joint Bayesian. Comput. Aided Geom. Des. 81, 101910 (2020). https:\/\/doi.org\/10.1016\/j.cagd.2020.101910","journal-title":"Comput. Aided Geom. Des."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03056-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03056-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03056-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T12:10:03Z","timestamp":1731499803000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03056-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,1]]},"references-count":41,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["3056"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03056-w","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3614172\/v1","asserted-by":"object"}]},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,1]]},"assertion":[{"value":"15 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 March 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}