{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T14:07:38Z","timestamp":1769177258532,"version":"3.49.0"},"reference-count":37,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T00:00:00Z","timestamp":1590796800000},"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":["11902349"],"award-info":[{"award-number":["11902349"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Moving object detection under a moving camera is a challenging question, especially in a complex background. This paper proposes a background orientation field reconstruction method based on Poisson fusion for detecting moving objects under a moving camera. As enlightening by the optical flow orientation of a background is not dependent on the scene depth, this paper reconstructs the background orientation through Poisson fusion based on the modified gradient. Then, the motion saliency map is calculated by the difference between the original and the reconstructed orientation field. Based on the similarity in appearance and motion, the paper also proposes a weighted accumulation enhancement method. It can highlight the motion saliency of the moving objects and improve the consistency within the object and background region simultaneously. Furthermore, the proposed method incorporates the motion continuity to reject the false positives. The experimental results obtained by employing publicly available datasets indicate that the proposed method can achieve excellent performance compared with current state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s20113103","type":"journal-article","created":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T09:19:27Z","timestamp":1591089567000},"page":"3103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Moving Object Detection under a Moving Camera via Background Orientation Reconstruction"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3756-5235","authenticated-orcid":false,"given":"Wenlong","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoliang","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qifeng","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.visres.2012.02.006","article-title":"Use of speed cues in the detection of moving objects by moving observers","volume":"59","author":"Royden","year":"2012","journal-title":"Vis. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1109\/TIP.2010.2101613","article-title":"ViBe: A universal background subtraction algorithm for video sequences","volume":"20","author":"Barnich","year":"2010","journal-title":"IEEE Trans. Image Process."},{"key":"ref_3","unstructured":"Elgammal, A., Harwood, D., and Davis, L. (July, January 26). Non-parametric model for background subtraction. Proceedings of the 6th European Conference on Computer Vision, Dublin, Ireland."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1109\/TPAMI.2017.2732350","article-title":"Robust online matrix factorization for dynamic background subtraction","volume":"40","author":"Yong","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Yi, K.M., Yun, K., Kim, S.W., Chang, H.J., Choi, J.Y., and Jeong, H. (2013). Detection of moving objects with non-stationary cameras in 5.8ms: Bringing motion detection to your mobile device. Computer Vision & Pattern Recognition Workshops, IEEE.","DOI":"10.1109\/CVPRW.2013.9"},{"key":"ref_6","first-page":"1","article-title":"Automatic moving object segmentation for freely moving cameras","volume":"2014","author":"Wan","year":"2014","journal-title":"Math. Probl. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"25108","DOI":"10.1088\/0957-0233\/22\/2\/025108","article-title":"Segmenting moving objects from a freely moving camera with an effective segmentation cue","volume":"22","author":"Wu","year":"2011","journal-title":"Meas. Sci. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kurnianggoro, L., Yu, Y., Hernandez, D., and Jo, K.-H. (2016). Online Background-Subtraction with Motion Compensation for Freely Moving Camera. International Conference on Intelligent Computing, IEEE.","DOI":"10.1007\/978-3-319-42294-7_51"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Odobez, J.M., and Bouthemy, P. (1997). Separation of moving regions from background in an image sequence acquired with a mobile camera. Video Data Compression for Multimedia Computing: Statistically Based and Biologically Inspired Techniques, Springer.","DOI":"10.1007\/978-1-4615-6239-9_8"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Hartley, R., and Zisserman, A. (2003). Multiple View Geometry in Computer Vision, Cambridge University Press.","DOI":"10.1017\/CBO9780511811685"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1109\/TCSVT.2018.2854273","article-title":"Background subtraction based on integration of alternative cues in freely moving camera","volume":"29","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1007\/s00138-012-0448-y","article-title":"Detection of moving objects with a moving camera using non-panoramic background model","volume":"24","author":"Kim","year":"2012","journal-title":"Mach. Vis. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Narayana, M., Hanson, A., and Learned-Miller, E. (2013, January 1\u20138). Coherent motion segmentation in moving camera videos using optical flow orientations. Proceedings of the 2013 IEEE International Conference on Computer Vision, Sydney, Australia.","DOI":"10.1109\/ICCV.2013.199"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1145\/882262.882269","article-title":"Poisson image editing","volume":"22","author":"Gangnet","year":"2003","journal-title":"ACM Trans. Graphics"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.cosrev.2018.03.001","article-title":"New trends on moving object detection in video images captured by a moving camera: A survey","volume":"28","author":"Yazdi","year":"2018","journal-title":"Comput. Sci. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chapel, M.-N., and Bouwmans, T. (2020). Moving objects detection with a moving camera: A comprehensive review. arXiv, Available online: https:\/\/arxiv.org\/abs\/2001.05238.","DOI":"10.1016\/j.cosrev.2020.100310"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1007\/s11042-012-1075-3","article-title":"Fast moving object detection with non-stationary background","volume":"67","author":"Kim","year":"2012","journal-title":"Multimedia Tools Appl."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sheikh, Y., Javed, O., and Kanade, T. (October, January 29). Background subtraction for freely moving cameras. Proceedings of the 2009 IEEE 12th International Conference on Computer Vision, Kyoto, Japan.","DOI":"10.1109\/ICCV.2009.5459334"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Brox, T., and Malik, J. (2010, January 5\u201311). Object segmentation by long term analysis of point trajectories. Proceedings of the 11th European Conference on Computer Vision, Heraklion, Greece.","DOI":"10.1007\/978-3-642-15555-0_21"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1109\/TPAMI.2013.242","article-title":"Segmentation of moving objects by long term video analysis","volume":"36","author":"Ochs","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Nonaka, Y., Shimada, A., Nagahara, H., and Taniguchi, R.-I. (2013, January 5\u20138). Real-time foreground segmentation from moving camera based on case-based trajectory classification. Proceedings of the 2013 2nd IAPR Asian Conference on Pattern Recognition, Okinawa, Japan.","DOI":"10.1109\/ACPR.2013.146"},{"key":"ref_22","first-page":"228","article-title":"Online moving camera background subtraction","volume":"7577","author":"Elqursh","year":"2012","journal-title":"Appl. Evol. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.cviu.2008.11.005","article-title":"Detection and segmentation of moving objects in complex scenes","volume":"113","author":"Bugeau","year":"2009","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_24","first-page":"1692","article-title":"Moving object detection with moving camera based on motion saliency","volume":"36","author":"Gao","year":"2016","journal-title":"J. Comput. Appl."},{"key":"ref_25","unstructured":"Huang, J., Zou, W., Zhu, J., and Zhu, Z. (2018). Optical flow based real-time moving object detection in unconstrained scenes. arXiv, Available online: https:\/\/arxiv.org\/abs\/1807.04890."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.image.2019.03.003","article-title":"Motion and appearance based background subtraction for freely moving cameras","volume":"75","author":"Sajid","year":"2019","journal-title":"Signal. Process. Image Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.imavis.2017.07.006","article-title":"Moving object detection and segmentation in urban environments from a moving platform","volume":"68","author":"Zhou","year":"2017","journal-title":"Image Vis. Comput."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Namdev, R.K., Kundu, A., Krishna, K.M., and Jawahar, C.V. (2012, January 14\u201318). Motion segmentation of multiple objects from a freely moving monocular camera. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6224800"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bideau, P., and Learned-Miller, E. (2016, January 8\u201316). It\u2019s Moving! A probabilistic model for causal motion segmentation in moving camera videos. Proceedings of the 14th European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46484-8_26"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Papazoglou, A., and Ferrari, V. (2013, January 1\u20138). Fast object segmentation in unconstrained video. Proceedings of the 2013 IEEE International Conference on Computer Vision, Sydney, Australia.","DOI":"10.1109\/ICCV.2013.223"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1109\/TCSVT.2016.2587387","article-title":"Object-level motion detection from moving cameras","volume":"27","author":"Chen","year":"2016","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1109\/TCSVT.2015.2493499","article-title":"Moving object detection with a freely moving camera via background motion subtraction","volume":"27","author":"Wu","year":"2015","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhu, Y., and Elgammal, A. (2017, January 22\u201329). A multilayer-based framework for online background subtraction with freely moving cameras. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.549"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Trefethen, L.N., and Bau, D. (1997). Numerical Linear Algebra, SIAM.","DOI":"10.1137\/1.9780898719574"},{"key":"ref_35","unstructured":"Hu, J., and Tang, H. (2007). Numerical Method of Differential Equation, Science Press."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Pont-Tuset, J., McWilliams, B., Van Gool, L., Gross, M., and Sorkine-Hornung, A. (2016, January 27\u201330). A benchmark dataset and evaluation methodology for video object segmentation. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.85"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sun, D., Roth, S., and Black, M. (2010, January 13\u201318). Secrets of optical flow estimation and their principles. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5539939"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3103\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:34:11Z","timestamp":1760175251000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3103"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,30]]},"references-count":37,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["s20113103"],"URL":"https:\/\/doi.org\/10.3390\/s20113103","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,30]]}}}