{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T13:01:07Z","timestamp":1755694867345,"version":"3.37.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"42","license":[{"start":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T00:00:00Z","timestamp":1710288000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T00:00:00Z","timestamp":1710288000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["No.52171332"],"award-info":[{"award-number":["No.52171332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Key projects of Heilongjiang Natural Science Foundation","award":["No.ZD2022F001"],"award-info":[{"award-number":["No.ZD2022F001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-024-18852-2","type":"journal-article","created":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T08:55:41Z","timestamp":1710320141000},"page":"90375-90392","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["OARPD: occlusion-aware rotated people detection in overhead fisheye images"],"prefix":"10.1007","volume":"83","author":[{"given":"Rengjie","family":"Qiao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3475-6098","authenticated-orcid":false,"given":"Chengtao","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Haiyang","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jie","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,13]]},"reference":[{"key":"18852_CR1","doi-asserted-by":"publisher","first-page":"3975","DOI":"10.1109\/TMM.2022.3169055","volume":"25","author":"K Wu","year":"2023","unstructured":"Wu K, Yang Y, Member S et al (2023) Focal Stack Image Compression Based on Basis-Quadtree Representation. IEEE Trans Multimedia 25:3975\u20133988. https:\/\/doi.org\/10.1109\/TMM.2022.3169055","journal-title":"IEEE Trans Multimedia"},{"key":"18852_CR2","doi-asserted-by":"publisher","unstructured":"Wakai N, Sato S, Ishii Y, Yamashita T (2022) Rethinking Generic Camera Models for Deep Single Image Camera Calibration to Recover Rotation and Fisheye Distortion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 13678 LNCS:679-698. https:\/\/doi.org\/10.1007\/978-3-031-19797-0_39","DOI":"10.1007\/978-3-031-19797-0_39"},{"key":"18852_CR3","doi-asserted-by":"publisher","first-page":"39483","DOI":"10.1364\/OE.504717","volume":"31","author":"K Wu","year":"2023","unstructured":"Wu K, Liu Q, Yap K, Yang Y (2023) High dimensional optical data - varifocal multiview imaging, compression and evaluation. Optics Express 31:39483\u201339499","journal-title":"Optics Express"},{"key":"18852_CR4","doi-asserted-by":"publisher","first-page":"1532","DOI":"10.1109\/TPAMI.2014.2300479","volume":"36","author":"P Dollar","year":"2014","unstructured":"Dollar P, Appel R, Belongie S, Perona P (2014) Fast feature pyramids for object detection. IEEE Trans Pattern Anal Mach Intell 36:1532\u20131545. https:\/\/doi.org\/10.1109\/TPAMI.2014.2300479","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"18852_CR5","unstructured":"Chiang A, Wang Y HUMAN DETECTION IN FISH-EYE IMAGES USING HOG-BASED DETECTORS OVER ROTATED WINDOWS An-Ti Chiang and Yao Wang Department of Electrical and Computer Engineering , Game Innovation Lab , Polytechnic Institute of NYU , Brooklyn , NY 11201 , USA"},{"key":"18852_CR6","doi-asserted-by":"publisher","unstructured":"Krams O, Kiryati N (2017) People detection in top-view fisheye imaging. 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017. https:\/\/doi.org\/10.1109\/AVSS.2017.8078535","DOI":"10.1109\/AVSS.2017.8078535"},{"key":"18852_CR7","doi-asserted-by":"publisher","unstructured":"Li S, Tezcan MO, Ishwar P, Konrad J (2019) Supervised people counting using an overhead fisheye camera. 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019 0-7. https:\/\/doi.org\/10.1109\/AVSS.2019.8909877","DOI":"10.1109\/AVSS.2019.8909877"},{"key":"18852_CR8","doi-asserted-by":"publisher","unstructured":"Tamura M, Horiguchi S, Murakami T (2019) Omnidirectional pedestrian detection by rotation invariant training. Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019 1989-1998. https:\/\/doi.org\/10.1109\/WACV.2019.00216","DOI":"10.1109\/WACV.2019.00216"},{"key":"18852_CR9","doi-asserted-by":"publisher","unstructured":"Duan Z, Ozan Tezcan M, Nakamura H, et al (2020) RAPiD: Rotation-aware people detection in overhead fisheye images. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2020-June:2700-2709. https:\/\/doi.org\/10.1109\/CVPRW50498.2020.00326","DOI":"10.1109\/CVPRW50498.2020.00326"},{"key":"18852_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2020.104069","volume":"105","author":"SH Chiang","year":"2021","unstructured":"Chiang SH, Wang T, Chen YF (2021) Efficient pedestrian detection in top-view fisheye images using compositions of perspective view patches. Image Vis Comput 105:104069. https:\/\/doi.org\/10.1016\/j.imavis.2020.104069","journal-title":"Image Vis Comput"},{"key":"18852_CR11","doi-asserted-by":"crossref","unstructured":"Yang L, Li L, Xin X, et al (2023) Large-Scale Person Detection and Localization using Overhead Fisheye Cameras","DOI":"10.1109\/ICCV51070.2023.01827"},{"key":"18852_CR12","doi-asserted-by":"publisher","unstructured":"Cao H, Peng B, Jia L, et al (2022) Orientation-aware People Detection and Counting Method based on Overhead Fisheye Camera. IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2022-Septe: https:\/\/doi.org\/10.1109\/MFI55806.2022.9913868","DOI":"10.1109\/MFI55806.2022.9913868"},{"key":"18852_CR13","doi-asserted-by":"publisher","unstructured":"Xu X, Gao Y, Liang H, et al (2022) Fisheye object detection based on standard image datasets with 24-points regression strategy. IEEE International Conference on Intelligent Robots and Systems 2022-Octob. pp 9911-9918. https:\/\/doi.org\/10.1109\/IROS47612.2022.9981891","DOI":"10.1109\/IROS47612.2022.9981891"},{"key":"18852_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2022.103715","volume":"90","author":"X Wei","year":"2023","unstructured":"Wei X, Wei Y, Lu X (2023) HD-YOLO: Using radius-aware loss function for head detection in top-view fisheye images. J Vis Commun Image Represent 90:103715. https:\/\/doi.org\/10.1016\/j.jvcir.2022.103715","journal-title":"J Vis Commun Image Represent"},{"key":"18852_CR15","doi-asserted-by":"publisher","first-page":"4355","DOI":"10.1109\/TIP.2023.3298475","volume":"32","author":"X Wei","year":"2023","unstructured":"Wei X, Su S, Wei Y, Lu X (2023) Rotational Convolution: Rethinking Convolution for Downside Fisheye Images. IEEE Trans Image Process 32:4355\u20134364. https:\/\/doi.org\/10.1109\/TIP.2023.3298475","journal-title":"IEEE Trans Image Process"},{"key":"18852_CR16","doi-asserted-by":"publisher","unstructured":"Chen Y, Zhu D, Li N et al (2023) GET: group equivariant transformer for person detection of overhead fisheye images. Appl Intell 24551\u201324565. https:\/\/doi.org\/10.1007\/s10489-023-04747-6","DOI":"10.1007\/s10489-023-04747-6"},{"key":"18852_CR17","doi-asserted-by":"publisher","unstructured":"Ding J, Xue N, Long Y, et al (2019) Learning roi transformer for oriented object detection in aerial images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2019-June. pp 2844-2853. https:\/\/doi.org\/10.1109\/CVPR.2019.00296","DOI":"10.1109\/CVPR.2019.00296"},{"key":"18852_CR18","doi-asserted-by":"publisher","unstructured":"Han J, Ding J, Xue N, Xia GS (2021) ReDeT: A Rotation-equivariant Detector for Aerial Object Detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pp 2785\u20132794. https:\/\/doi.org\/10.1109\/CVPR46437.2021.00281","DOI":"10.1109\/CVPR46437.2021.00281"},{"key":"18852_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3136350","volume":"60","author":"D Liang","year":"2022","unstructured":"Liang D, Geng Q, Wei Z et al (2022) Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images. IEEE Trans Geosci Remote Sens 60:1\u201313. https:\/\/doi.org\/10.1109\/TGRS.2021.3136350","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"18852_CR20","unstructured":"Xie X, Cheng G, Wang J, et al Oriented R-CNN for Object Detection. pp 1"},{"key":"18852_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2022.3222818","volume":"61","author":"D Wang","year":"2023","unstructured":"Wang D, Zhang Q, Xu Y et al (2023) Advancing Plain Vision Transformer Toward Remote Sensing Foundation Model. IEEE Trans Geosci Remote Sens 61:1\u201315. https:\/\/doi.org\/10.1109\/TGRS.2022.3222818","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"18852_CR22","doi-asserted-by":"publisher","unstructured":"Yang X, Yan J, Feng Z, He T (2021) R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object. 35th AAAI Conference on Artificial Intelligence, AAAI 2021 4A. pp 3163-3171. https:\/\/doi.org\/10.1609\/aaai.v35i4.16426","DOI":"10.1609\/aaai.v35i4.16426"},{"key":"18852_CR23","doi-asserted-by":"crossref","unstructured":"Dai L, Liu H, Tang H, et al (2023) AO2-DETR : Arbitrary-Oriented Object. 33:2342-2356","DOI":"10.1109\/TCSVT.2022.3222906"},{"key":"18852_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3062048","volume":"60","author":"J Han","year":"2022","unstructured":"Han J, Ding J, Li J, Xia GS (2022) Align Deep Features for Oriented Object Detection. IEEE Trans Geosci Remote Sens 60:1\u201310. https:\/\/doi.org\/10.1109\/TGRS.2021.3062048","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"18852_CR25","first-page":"11830","volume":"139","author":"X Yang","year":"2021","unstructured":"Yang X, Yan J, Ming Q et al (2021) Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss. Proc Mach Learn Res 139:11830\u201311841","journal-title":"Proc Mach Learn Res"},{"key":"18852_CR26","first-page":"18381","volume":"22","author":"X Yang","year":"2021","unstructured":"Yang X, Yang X, Yang J et al (2021) Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence. Adv Neural Inf Process Syst 22:18381\u201318394","journal-title":"Adv Neural Inf Process Syst"},{"key":"18852_CR27","doi-asserted-by":"crossref","unstructured":"Yang X, Zhou Y, Zhang G, et al (2022) The KFIoU Loss for Rotated Object Detection. pp 1-18","DOI":"10.1145\/3503161.3548541"},{"key":"18852_CR28","doi-asserted-by":"publisher","unstructured":"Guo Z, Liu C, Zhang X et al (2021) Beyond Bounding-Box: Convex-hull Feature Adaptation for Oriented and Densely Packed Object Detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 8788\u20138797. https:\/\/doi.org\/10.1109\/CVPR46437.2021.00868","DOI":"10.1109\/CVPR46437.2021.00868"},{"key":"18852_CR29","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1016\/j.isprsjprs.2020.09.022","volume":"169","author":"H Wei","year":"2020","unstructured":"Wei H, Zhang Y, Chang Z et al (2020) Oriented objects as pairs of middle lines. ISPRS J Photogramm Remote Sens 169:268\u2013279. https:\/\/doi.org\/10.1016\/j.isprsjprs.2020.09.022","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"18852_CR30","doi-asserted-by":"publisher","first-page":"6670","DOI":"10.1080\/01431161.2021.1941389","volume":"42","author":"Q Guan","year":"2021","unstructured":"Guan Q, Qu Z, Zeng M et al (2021) CGP Box: An effective direction representation strategy for oriented object detection in remote sensing images. Int J Remote Sens 42:6670\u20136691. https:\/\/doi.org\/10.1080\/01431161.2021.1941389","journal-title":"Int J Remote Sens"},{"key":"18852_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/rs13183622","volume":"13","author":"X He","year":"2021","unstructured":"He X, Ma S, He L et al (2021) Learning rotated inscribed ellipse for oriented object detection in remote sensing images. Remote Sensing 13:1\u201326. https:\/\/doi.org\/10.3390\/rs13183622","journal-title":"Remote Sensing"},{"key":"18852_CR32","unstructured":"Lin Y, Feng P, Guan J, et al (2019) IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection. pp 1-12"},{"key":"18852_CR33","unstructured":"Llerena JM, Zeni LF, Kristen LN, Jung C (2021) Gaussian Bounding Boxes and Probabilistic Intersection-over-Union for Object Detection. pp 1-21"},{"key":"18852_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108792","volume":"130","author":"H Tang","year":"2022","unstructured":"Tang H, Yuan C, Li Z, Tang J (2022) Learning attention-guided pyramidal features for few-shot fine-grained recognition. Pattern Recogn 130:108792. https:\/\/doi.org\/10.1016\/j.patcog.2022.108792","journal-title":"Pattern Recogn"},{"key":"18852_CR35","doi-asserted-by":"publisher","unstructured":"Liu S, Qi L, Qin H et al (2018) Path Aggregation Network for Instance Segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 8759\u20138768. https:\/\/doi.org\/10.1109\/CVPR.2018.00913","DOI":"10.1109\/CVPR.2018.00913"},{"key":"18852_CR36","doi-asserted-by":"crossref","unstructured":"Yang G, Lei J, Zhu Z, et al (2023) AFPN: Asymptotic Feature Pyramid Network for Object Detection","DOI":"10.1109\/SMC53992.2023.10394415"},{"key":"18852_CR37","doi-asserted-by":"publisher","unstructured":"Feng C, Zhong Y, Gao Y et al (2021) TOOD: Task-aligned One-stage Object Detection. Proceedings of the IEEE International Conference on Computer Vision 3490\u20133499. https:\/\/doi.org\/10.1109\/ICCV48922.2021.00349","DOI":"10.1109\/ICCV48922.2021.00349"},{"key":"18852_CR38","doi-asserted-by":"publisher","unstructured":"Zheng Z, Wang P, Liu W, et al (2020) Distance-IoU loss: Faster and better learning for bounding box regression. AAAI 2020 - 34th AAAI Conference on Artificial Intelligence 12993-13000. https:\/\/doi.org\/10.1609\/aaai.v34i07.6999","DOI":"10.1609\/aaai.v34i07.6999"},{"key":"18852_CR39","doi-asserted-by":"publisher","unstructured":"Ye Y, Yang K, Xiang K, et al (2020) Universal Semantic Segmentation for Fisheye Urban Driving Images. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 2020-October:648-655. https:\/\/doi.org\/10.1109\/SMC42975.2020.9283099","DOI":"10.1109\/SMC42975.2020.9283099"},{"key":"18852_CR40","doi-asserted-by":"publisher","unstructured":"Tezcan MO, Duan Z, Cokbas M, et al (2022) WEPDTOF: A Dataset and Benchmark Algorithms for In-the-Wild People Detection and Tracking from Overhead Fisheye Cameras. Proceedings - 2022 IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV 2022. pp 1381-1390. https:\/\/doi.org\/10.1109\/WACV51458.2022.00145","DOI":"10.1109\/WACV51458.2022.00145"},{"key":"18852_CR41","doi-asserted-by":"publisher","unstructured":"Seidel R, Apitzsch A, Hirtz G (2019) Improved Person Detection on Omnidirectional Images with Non-maxima Supression. VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 5:474-481. https:\/\/doi.org\/10.5220\/0007388404740481","DOI":"10.5220\/0007388404740481"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-024-18852-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-024-18852-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-024-18852-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,28]],"date-time":"2024-12-28T20:02:47Z","timestamp":1735416167000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-024-18852-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,13]]},"references-count":41,"journal-issue":{"issue":"42","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["18852"],"URL":"https:\/\/doi.org\/10.1007\/s11042-024-18852-2","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2024,3,13]]},"assertion":[{"value":"25 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 February 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 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 declared they had no confilicts of interest with related to this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}