{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:25:34Z","timestamp":1740122734026,"version":"3.37.3"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:00:00Z","timestamp":1657756800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:00:00Z","timestamp":1657756800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["61873176"],"award-info":[{"award-number":["61873176"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"natural science foundation of jiangsu province","doi-asserted-by":"publisher","award":["BK20181433"],"award-info":[{"award-number":["BK20181433"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s10489-022-03278-w","type":"journal-article","created":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T10:08:06Z","timestamp":1657793286000},"page":"7093-7107","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Robust stereo inertial odometry based on self-supervised feature points"],"prefix":"10.1007","volume":"53","author":[{"given":"Guangqiang","family":"Li","sequence":"first","affiliation":[]},{"given":"Junyi","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Zhong","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7621-6807","authenticated-orcid":false,"given":"Lei","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Shumin","family":"Fei","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,7,14]]},"reference":[{"key":"3278_CR1","doi-asserted-by":"crossref","unstructured":"Balntas V, Lenc K, Vedaldi A, Mikolajczyk K (2017) HPatches: a benchmark and evaluation of handcrafted and learned local descriptors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5173\u20135182","DOI":"10.1109\/CVPR.2017.410"},{"issue":"3","key":"3278_CR2","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay H, Ess A, Tuytelaars T, van Gool L (2008) Speeded-up robust features (SURF). Comput Vis Image Underst 110(3):346\u2013359","journal-title":"Comput Vis Image Underst"},{"key":"3278_CR3","doi-asserted-by":"crossref","unstructured":"Bloesch M, Omari S, et al. (2015) Robust visual inertial odometry using a direct EKF-based approach. In: 2015 IEEE\/RSJ international conference on intelligent robots and systems (IROS), pp. 298-304","DOI":"10.1109\/IROS.2015.7353389"},{"issue":"10","key":"3278_CR4","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1177\/0278364915620033","volume":"35","author":"M Burri","year":"2016","unstructured":"Burri M, Nikolic J, Gohl P, Schneider T, Rehder J, Omari S, Achtelik MW, Siegwart R (2016) The EuRoC micro aerial vehicle datasets. Int J Robot Res 35(10):1157\u20131163","journal-title":"Int J Robot Res"},{"issue":"10","key":"3278_CR5","doi-asserted-by":"publisher","first-page":"6232","DOI":"10.1109\/TGRS.2016.2584107","volume":"54","author":"Y Chen","year":"2016","unstructured":"Chen Y, Jiang H, Li C, Jia X, Ghamisi P (2016) Deep feature extraction and classification of hyperspectral images based on convolutional neural networks. IEEE Trans Geosci Remote Sens 54(10):6232\u20136251","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"3278_CR6","unstructured":"Christiansen PH, Kragh MF, Brodskiy Y, et al. (2019) Unsuperpoint: end-to-end unsupervised interest point detector and descriptor. arXiv:1907.04011"},{"key":"3278_CR7","doi-asserted-by":"crossref","unstructured":"DeTone D, Malisiewicz T, Rabinovich A (2018) Superpoint: self-supervised interest point detection and description. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 224\u2013236","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"3278_CR8","doi-asserted-by":"crossref","unstructured":"Engel J, Sch\u00f6ps T, Cremers D (2014) LSD-SLAM: Large-scale direct monocular SLAM. In: European Conference on Computer Vision, pp. 834\u2013849","DOI":"10.1007\/978-3-319-10605-2_54"},{"issue":"3","key":"3278_CR9","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1109\/TPAMI.2017.2658577","volume":"40","author":"J Engel","year":"2017","unstructured":"Engel J, Koltun V, Cremers D (2017) Direct sparse odometry. IEEE Trans Pattern Anal Mach Intell 40(3):611\u2013625","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"3278_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TRO.2016.2597321","volume":"33","author":"C Forster","year":"2016","unstructured":"Forster C, Carlone L, Dellaert F, Scaramuzza D (2016) On-manifold Preintegration for real-time visual--inertial Odometry. IEEE Trans Robot 33(1):1\u201321","journal-title":"IEEE Trans Robot"},{"issue":"3","key":"3278_CR11","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TRO.2019.2899783","volume":"35","author":"R Gomez-Ojeda","year":"2019","unstructured":"Gomez-Ojeda R, Moreno FA, Zuniga-No\u00ebl D et al (2019) PL-SLAM: a stereo SLAM system through the combination of points and line segments. IEEE Trans Robot 35(3):734\u2013746","journal-title":"IEEE Trans Robot"},{"key":"3278_CR12","doi-asserted-by":"crossref","unstructured":"Huang H, Ye H, Sun Y, et al. (2020) Monocular visual odometry using learned repeatability and description. In: IEEE international conference on robotics and automation (ICRA), pp. 913-8919","DOI":"10.1109\/ICRA40945.2020.9197406"},{"key":"3278_CR13","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.neuroimage.2016.04.003","volume":"145","author":"H Jang","year":"2017","unstructured":"Jang H, Plis SM, Calhoun VD, Lee JH (2017) Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: evaluation using sensorimotor tasks. NeuroImage 145:314\u2013328","journal-title":"NeuroImage"},{"issue":"4","key":"3278_CR14","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/MRA.2013.2283642","volume":"20","author":"S Lee","year":"2013","unstructured":"Lee S, Lee S (2013) Embedded visual SLAM: applications for low-cost consumer robots. IEEE Robot Autom Mag 20(4):83\u201395","journal-title":"IEEE Robot Autom Mag"},{"issue":"3","key":"3278_CR15","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1177\/0278364914554813","volume":"34","author":"S Leutenegger","year":"2014","unstructured":"Leutenegger S, Lynen S, Bosse M et al (2014) Keyframe-based visual-inertial Odometry using nonlinear optimization. Int J Robot Res 34(3):314\u2013334","journal-title":"Int J Robot Res"},{"issue":"3","key":"3278_CR16","doi-asserted-by":"publisher","first-page":"1179","DOI":"10.1007\/s10846-020-01222-z","volume":"100","author":"G Li","year":"2020","unstructured":"Li G, Yu L, Fei S (2020) A binocular MSCKF-based visual inertial Odometry system using LK optical flow. J Intell Robot Syst 100(3):1179\u20131194","journal-title":"J Intell Robot Syst"},{"key":"3278_CR17","doi-asserted-by":"publisher","first-page":"108403","DOI":"10.1016\/j.measurement.2020.108403","volume":"168","author":"G Li","year":"2021","unstructured":"Li G, Yu L, Fei S (2021) A deep-learning real-time visual SLAM system based on multi-task feature extraction network and self-supervised feature points. Measurement 168:108403","journal-title":"Measurement"},{"issue":"2","key":"3278_CR18","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant Keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"issue":"3","key":"3278_CR19","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1007\/s10489-019-01523-3","volume":"50","author":"T Ma","year":"2020","unstructured":"Ma T, Kuang P, Tian W (2020) An improved recurrent neural networks for 3d object reconstruction. Appl Intell 50(3):905\u2013923","journal-title":"Appl Intell"},{"issue":"11","key":"3278_CR20","doi-asserted-by":"publisher","first-page":"3834","DOI":"10.1007\/s10489-019-01565-7","volume":"49","author":"KJ Morris","year":"2019","unstructured":"Morris KJ, Samonin V, Baltes J, Anderson J, Lau MC (2019) A robust interactive entertainment robot for robot magic performances. Appl Intell 49(11):3834\u20133844","journal-title":"Appl Intell"},{"issue":"2","key":"3278_CR21","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1109\/LRA.2017.2653359","volume":"2","author":"R Mur-Artal","year":"2017","unstructured":"Mur-Artal R, Tard\u00f3s JD (2017) Visual-inertial monocular SLAM with map reuse. IEEE Robot Autom Lett 2(2):796\u2013803","journal-title":"IEEE Robot Autom Lett"},{"issue":"5","key":"3278_CR22","doi-asserted-by":"publisher","first-page":"1255","DOI":"10.1109\/TRO.2017.2705103","volume":"33","author":"R Mur-Artal","year":"2017","unstructured":"Mur-Artal R, Tard\u00f3s JD (2017) Orb-slam2: an open-source slam system for monocular, stereo, and rgb-d cameras. IEEE Trans Robot 33(5):1255\u20131262","journal-title":"IEEE Trans Robot"},{"issue":"1","key":"3278_CR23","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/rob.20103","volume":"23","author":"D Nist\u00e9r","year":"2010","unstructured":"Nist\u00e9r D, Naroditsky O, Bergen JR (2010) Visual odometry for ground vehicle applications. J Field Robot 23(1):3\u201320","journal-title":"J Field Robot"},{"key":"3278_CR24","doi-asserted-by":"crossref","unstructured":"Oskiper T, Samarasekera S, Kumar R (2011) Tightly-coupled robust vision aided inertial navigation algorithm for augmented reality using monocular camera and IMU. In: 2011 10th IEEE international symposium on mixed and augmented reality, pp. 255-256","DOI":"10.1109\/ISMAR.2011.6143485"},{"issue":"1","key":"3278_CR25","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1109\/TPAMI.2008.275","volume":"32","author":"E Rosten","year":"2008","unstructured":"Rosten E, Porter R, Drummond T (2008) Faster and better: a machine learning approach to corner detection. IEEE Trans Pattern Anal Mach Intell 32(1):105\u2013119","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3278_CR26","doi-asserted-by":"crossref","unstructured":"Rublee E, Rabaud V, Konolige K, et al. (2011) ORB: an efficient alternative to SIFT or SURF. In: 2011 international conference on computer vision, pp. 2564-2571","DOI":"10.1109\/ICCV.2011.6126544"},{"issue":"2","key":"3278_CR27","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/LRA.2018.2793349","volume":"3","author":"K Sun","year":"2018","unstructured":"Sun K, Mohta K, Pfrommer B, Watterson M, Liu S, Mulgaonkar Y, Taylor CJ, Kumar V (2018) Robust stereo visual inertial odometry for fast autonomous flight. IEEE Robot Autom Lett 3(2):965\u2013972","journal-title":"IEEE Robot Autom Lett"},{"issue":"2","key":"3278_CR28","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1109\/LRA.2018.2794624","volume":"3","author":"J Tang","year":"2018","unstructured":"Tang J, Folkesson J, Jensfelt P (2018) Geometric correspondence network for camera motion estimation. IEEE Robot Autom Lett 3(2):1010\u20131017","journal-title":"IEEE Robot Autom Lett"},{"issue":"4","key":"3278_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TRO.2018.2861318","volume":"34","author":"Q Tong","year":"2018","unstructured":"Tong Q, Li P, Shen S (2018) VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator. IEEE Trans Robot 34(4):1\u201317","journal-title":"IEEE Trans Robot"},{"issue":"2","key":"3278_CR30","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1109\/LRA.2019.2961227","volume":"5","author":"V Usenko","year":"2019","unstructured":"Usenko V, Demmel N, Schubert D et al (2019) Visual-inertial mapping with non-linear factor recovery. IEEE Robot Autom Lett 5(2):422\u2013429","journal-title":"IEEE Robot Autom Lett"},{"key":"3278_CR31","doi-asserted-by":"crossref","unstructured":"Von Stumberg L, Usenko V, Cremers D (2018) Direct sparse visual-inertial odometry using dynamic marginalization. In: 2018 IEEE international conference on robotics and automation (ICRA), pp. 2510-2517","DOI":"10.1109\/ICRA.2018.8462905"},{"issue":"1","key":"3278_CR32","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/TNNLS.2019.2899936","volume":"31","author":"S Yang","year":"2019","unstructured":"Yang S, Deng B, Wang J et al (2019) Scalable digital neuromorphic architecture for large-scale biophysically meaningful neural network with multi-compartment neurons. IEEE Trans Neural Netw Learn Syst 31(1):148\u2013162","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"3278_CR33","doi-asserted-by":"publisher","first-page":"97","DOI":"10.3389\/fnins.2021.601109","volume":"15","author":"S Yang","year":"2021","unstructured":"Yang S, Gao T, Wang J, Deng B, Lansdell B, Linares-Barranco B (2021) Efficient spike-driven learning with dendritic event-based processing. Front Neurosci 15:97","journal-title":"Front Neurosci"},{"key":"3278_CR34","doi-asserted-by":"crossref","unstructured":"Yang S, Wang J, Deng B, Azghadi MR, Linares-Barranco B (2021) Neuromorphic context-dependent learning framework with fault-tolerant spike routing. IEEE Trans Neural Netw Learn Syst:1\u201315","DOI":"10.1109\/TNNLS.2021.3128269"},{"key":"3278_CR35","doi-asserted-by":"crossref","unstructured":"Yang S, Wang J, Hao X, Li H, Wei X, Deng B, Loparo KA (2021) BiCoSS: toward large-scale cognition brain with multigranular neuromorphic architecture. IEEE Trans Neural Netw Learn Syst:1\u201315","DOI":"10.1109\/TNNLS.2021.3128269"},{"key":"3278_CR36","doi-asserted-by":"crossref","unstructured":"Yang S, Wang J, Zhang N, et al. (2021) CerebelluMorphic: large-scale neuromorphic model and architecture for supervised motor learning. IEEE Trans Neural Netw Learn Syst. 1-15","DOI":"10.1109\/TNNLS.2021.3128269"},{"key":"3278_CR37","doi-asserted-by":"crossref","unstructured":"Yi KM, Trulls E, Lepetit V, et al. (2016) Lift: learned invariant feature transform. In: European Conference on Computer Vision, pp. 467\u2013483","DOI":"10.1007\/978-3-319-46466-4_28"},{"key":"3278_CR38","doi-asserted-by":"crossref","unstructured":"Zhou H, Ummenhofer B, Brox T (2018) Deeptam: deep tracking and mapping. In: proceedings of the European conference on computer vision (ECCV), pp. 822-838","DOI":"10.1007\/978-3-030-01270-0_50"},{"issue":"2","key":"3278_CR39","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1109\/TPAMI.2012.104","volume":"35","author":"D Zou","year":"2012","unstructured":"Zou D, Tan P (2012) Coslam: collaborative visual slam in dynamic environments. IEEE Trans Pattern Anal Mach Intell 35(2):354\u2013366","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03278-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03278-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03278-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,24]],"date-time":"2023-11-24T15:21:44Z","timestamp":1700839304000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03278-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,14]]},"references-count":39,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["3278"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03278-w","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2022,7,14]]},"assertion":[{"value":"19 January 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}