{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:24:12Z","timestamp":1742945052304,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":34,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819988495"},{"type":"electronic","value":"9789819988501"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-8850-1_5","type":"book-chapter","created":{"date-parts":[[2024,2,3]],"date-time":"2024-02-03T18:02:05Z","timestamp":1706983325000},"page":"53-65","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sliding Window Detection and\u00a0Distance-Based Matching for\u00a0Tracking on\u00a0Gigapixel Images"],"prefix":"10.1007","author":[{"given":"Yichen","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiankun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,4]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"Bergmann, P., Meinhardt, T., Leal-Taixe, L.: Tracking without bells and whistles. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 941\u2013951 (2019)","DOI":"10.1109\/ICCV.2019.00103"},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B.: Simple online and realtime tracking. In: Proceedings of the IEEE International Conference on Image Processing, pp. 3464\u20133468 (2016)","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Bras\u00f3, G., Leal-Taix\u00e9, L.: Learning a neural solver for multiple object tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6247\u20136257 (2020)","DOI":"10.1109\/CVPR42600.2020.00628"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Cai, Z., Vasconcelos, N.: Cascade r-cnn: Delving into high quality object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6154\u20136162 (2018)","DOI":"10.1109\/CVPR.2018.00644"},{"key":"5_CR5","doi-asserted-by":"crossref","unstructured":"Chu, P., Ling, H.: Famnet: joint learning of feature, affinity and multi-dimensional assignment for online multiple object tracking. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 6172\u20136181 (2019)","DOI":"10.1109\/ICCV.2019.00627"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Chu, X., Zheng, A., Zhang, X., Sun, J.: Detection in crowded scenes: one proposal, multiple predictions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 12214\u201312223 (2020)","DOI":"10.1109\/CVPR42600.2020.01223"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Dehghan, A., Tian, Y., Torr, P.H., Shah, M.: Target identity-aware network flow for online multiple target tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1146\u20131154 (2015)","DOI":"10.1109\/CVPR.2015.7298718"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Fang, K., Xiang, Y., Li, X., Savarese, S.: Recurrent autoregressive networks for online multi-object tracking. In: Proceedings of IEEE Winter Conference on Applications of Computer Vision, pp. 466\u2013475 (2018)","DOI":"10.1109\/WACV.2018.00057"},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"5_CR12","unstructured":"Hong, Y., Wei, K., Chen, L., Fu, Y.: Crafting object detection in very low light. In: Proceedings of the British Machine Vision Conference, p. 3 (2021)"},{"key":"5_CR13","unstructured":"Hornakova, A., Henschel, R., Rosenhahn, B., Swoboda, P.: Lifted disjoint paths with application in multiple object tracking. In: Proceedings of the IEEE International Conference on Machine Learning, pp. 4364\u20134375 (2020)"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Keuper, M., Levinkov, E., Bonneel, N., Lavou\u00e9, G., Brox, T., Andres, B.: Efficient decomposition of image and mesh graphs by lifted multicuts. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1751\u20131759 (2015)","DOI":"10.1109\/ICCV.2015.204"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"5_CR17","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1016\/j.neucom.2022.01.008","volume":"483","author":"Q Liu","year":"2022","unstructured":"Liu, Q., et al.: Online multi-object tracking with unsupervised re-identification learning and occlusion estimation. Neurocomputing 483, 333\u2013347 (2022)","journal-title":"Neurocomputing"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Liu, Q., Chu, Q., Liu, B., Yu, N.: Gsm: graph similarity model for multi-object tracking. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, pp. 530\u2013536 (2020)","DOI":"10.24963\/ijcai.2020\/74"},{"key":"5_CR19","unstructured":"Liu, Q., Liu, B., Wu, Y., Li, W., Yu, N.: Real-time online multi-object tracking in compressed domain. arXiv preprint arXiv:2204.02081 (2022)"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Liu, W., et al.: SSD: single shot multibox detector. In: Proceedings of European Conference on Computer Vision, pp. 21\u201337 (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"5_CR21","doi-asserted-by":"crossref","unstructured":"Lu, X., Li, B., Yue, Y., Li, Q., Yan, J.: Grid r-cnn. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7363\u20137372 (2019)","DOI":"10.1109\/CVPR.2019.00754"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Pang, J., Chen, K., Shi, J., Feng, H., Ouyang, W., Lin, D.: Libra r-cnn: Towards balanced learning for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 821\u2013830 (2019)","DOI":"10.1109\/CVPR.2019.00091"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"5_CR24","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards real-time object detection with region proposal networks. In: Proceedings of Advances in Neural Information Processing Systems, vol. 28 (2015)"},{"key":"5_CR25","doi-asserted-by":"crossref","unstructured":"Roshan Zamir, A., Dehghan, A., Shah, M.: Gmcp-tracker: global multi-object tracking using generalized minimum clique graphs. In: Proceedings of European Conference on Computer Vision, pp. 343\u2013356 (2012)","DOI":"10.1007\/978-3-642-33709-3_25"},{"key":"5_CR26","doi-asserted-by":"crossref","unstructured":"Tang, S., Andriluka, M., Andres, B., Schiele, B.: Multiple people tracking by lifted multicut and person re-identification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3539\u20133548 (2017)","DOI":"10.1109\/CVPR.2017.394"},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Wang, M., Tighe, J., Modolo, D.: Combining detection and tracking for human pose estimation in videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 11088\u201311096 (2020)","DOI":"10.1109\/CVPR42600.2020.01110"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Panda: a gigapixel-level human-centric video dataset. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3268\u20133278 (2020)","DOI":"10.1109\/CVPR42600.2020.00333"},{"key":"5_CR29","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., Paulus, D.: Simple online and realtime tracking with a deep association metric. In: Proceedings of IEEE International Conference on Image Processing, pp. 3645\u20133649 (2017)","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"5_CR30","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Proceedings of European Conference on Computer Vision, pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"5_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, L., Li, Y., Nevatia, R.: Global data association for multi-object tracking using network flows. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587584"},{"key":"5_CR32","doi-asserted-by":"crossref","unstructured":"Zhang, Y., et al.: Bytetrack: Multi-object tracking by associating every detection box. In: Proceedings of European Conference on Computer Vision, pp. 1\u201321 (2022)","DOI":"10.1007\/978-3-031-20047-2_1"},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Tian, Q.: Scalable person re-identification: A benchmark. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1116\u20131124 (2015)","DOI":"10.1109\/ICCV.2015.133"},{"key":"5_CR34","doi-asserted-by":"crossref","unstructured":"Zhou, X., Koltun, V., Kr\u00e4henb\u00fchl, P.: Tracking objects as points. In: Proceedings of European Conference on Computer Vision, pp. 474\u2013490 (2020)","DOI":"10.1007\/978-3-030-58548-8_28"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8850-1_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,10]],"date-time":"2024-11-10T02:04:07Z","timestamp":1731204247000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8850-1_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819988495","9789819988501"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8850-1_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"4 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CAAI International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Fuzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cicai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cicai.caai.cn\/#\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"376","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"101","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.9","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1.9","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}