{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T03:58:27Z","timestamp":1775361507415,"version":"3.50.1"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"the NNSFC and CAAC","award":["U2133211"],"award-info":[{"award-number":["U2133211"]}]},{"name":"the Young Scientists Fund of the National Natural Science Foundation of China","award":["62203452"],"award-info":[{"award-number":["62203452"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>At present, occlusion and similar appearance pose serious challenges to the task of person re-identification. In this work, we propose an efficient multi-scale channel attention network (EMCA) to learn robust and more discriminative features to solve these problems. Specifically, we designed a novel cross-channel attention module (CCAM) in EMCA and placed it after different layers in the backbone. The CCAM includes local cross-channel interaction (LCI) and channel weight integration (CWI). LCI focuses on both the maximum pooling features and the average pooling features to generate channel weights through convolutional layers, respectively. CWI combines the two channel weights to generate richer and more discriminant channel weights. Experiments on four popular person Re-ID datasets (Market-1501, DukeMTMC-ReID, CUHK-03 (detected) and MSMT17) show that the performance of our EMCA is consistently significantly superior to the existing state-of-the-art methods.<\/jats:p>","DOI":"10.1007\/s00371-023-03049-9","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T10:02:42Z","timestamp":1692784962000},"page":"3515-3527","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["An efficient multi-scale channel attention network for person re-identification"],"prefix":"10.1007","volume":"40","author":[{"given":"Qian","family":"Luo","sequence":"first","affiliation":[]},{"given":"Jie","family":"Shao","sequence":"additional","affiliation":[]},{"given":"Wanli","family":"Dang","sequence":"additional","affiliation":[]},{"given":"Long","family":"Geng","sequence":"additional","affiliation":[]},{"given":"Huaiyu","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,23]]},"reference":[{"issue":"2","key":"3049_CR1","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1109\/TPAMI.2017.2666805","volume":"40","author":"Y-C Chen","year":"2017","unstructured":"Chen, Y.-C., Zhu, X., Zheng, W.-S., Lai, J.-H.: Person re-identification by camera correlation aware feature augmentation. IEEE Trans. Pattern Anal. Mach. Intell. 40(2), 392\u2013408 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3049_CR2","doi-asserted-by":"crossref","unstructured":"Zahra, A., Perwaiz, N., Shahzad, M., Fraz, M.M.: Person re-identification: a retrospective on domain specific open challenges and future trends. arXiv preprint arXiv:2202.13121 (2022)","DOI":"10.1016\/j.patcog.2023.109669"},{"key":"3049_CR3","doi-asserted-by":"crossref","unstructured":"Luo, H., Gu, Y., Liao, X., Lai, S., Jiang, W.: Bag of tricks and a strong baseline for deep person re-identification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 0\u20130 (2019)","DOI":"10.1109\/CVPRW.2019.00190"},{"key":"3049_CR4","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":"3049_CR5","doi-asserted-by":"crossref","unstructured":"Ristani, E., Solera, F., Zou, R., Cucchiara, R., Tomasi, C.: Performance measures and a data set for multi-target, multi-camera tracking. In: European Conference on Computer Vision, pp. 17\u201335. Springer (2016)","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"3049_CR6","doi-asserted-by":"publisher","first-page":"1654","DOI":"10.1007\/s11263-019-01259-0","volume":"128","author":"J Yin","year":"2020","unstructured":"Yin, J., Wu, A., Zheng, W.-S.: Fine-grained person re-identification. Int. J. Comput. Vis. 128, 1654\u20131672 (2020)","journal-title":"Int. J. Comput. Vis."},{"key":"3049_CR7","doi-asserted-by":"publisher","first-page":"7578","DOI":"10.1109\/TIP.2020.3004267","volume":"29","author":"Q Zhou","year":"2020","unstructured":"Zhou, Q., Zhong, B., Lan, X., Sun, G., Zhang, Y., Zhang, B., Ji, R.: Fine-grained spatial alignment model for person re-identification with focal triplet loss. IEEE Trans. Image Process. 29, 7578\u20137589 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR8","doi-asserted-by":"crossref","unstructured":"Gao, S., Wang, J., Lu, H., Liu, Z.: Pose-guided visible part matching for occluded person reid. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11744\u201311752 (2020)","DOI":"10.1109\/CVPR42600.2020.01176"},{"key":"3049_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2021.103172","volume":"205","author":"Z Li","year":"2021","unstructured":"Li, Z., Lv, J., Chen, Y., Yuan, J.: Person re-identification with part prediction alignment. Comput. Vis. Image Underst. 205, 103172 (2021)","journal-title":"Comput. Vis. Image Underst."},{"key":"3049_CR10","doi-asserted-by":"publisher","first-page":"2908","DOI":"10.1109\/TIP.2021.3055952","volume":"30","author":"P Wang","year":"2021","unstructured":"Wang, P., Zhao, Z., Su, F., Zu, X., Boulgouris, N.V.: Horeid: deep high-order mapping enhances pose alignment for person re-identification. IEEE Trans. Image Process. 30, 2908\u20132922 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR11","doi-asserted-by":"crossref","unstructured":"Chen, T., Ding, S., Xie, J., Yuan, Y., Chen, W., Yang, Y., Ren, Z., Wang, Z.: Abd-net: attentive but diverse person re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8351\u20138361 (2019)","DOI":"10.1109\/ICCV.2019.00844"},{"key":"3049_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108567","volume":"126","author":"Y Chen","year":"2022","unstructured":"Chen, Y., Wang, H., Sun, X., Fan, B., Tang, C., Zeng, H.: Deep attention aware feature learning for person re-identification. Pattern Recognit. 126, 108567 (2022)","journal-title":"Pattern Recognit."},{"key":"3049_CR13","doi-asserted-by":"publisher","first-page":"3405","DOI":"10.1109\/TIP.2021.3060909","volume":"30","author":"K Wang","year":"2021","unstructured":"Wang, K., Wang, P., Ding, C., Tao, D.: Batch coherence-driven network for part-aware person re-identification. IEEE Trans. Image Process. 30, 3405\u20133418 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107937","volume":"116","author":"J Sun","year":"2021","unstructured":"Sun, J., Li, Y., Chen, H., Zhang, B., Zhu, J.: Memf: multi-level-attention embedding and multi-layer-feature fusion model for person re-identification. Pattern Recognit. 116, 107937 (2021)","journal-title":"Pattern Recognit."},{"key":"3049_CR15","doi-asserted-by":"publisher","first-page":"8384","DOI":"10.1109\/TIP.2021.3113183","volume":"30","author":"Y Zhong","year":"2021","unstructured":"Zhong, Y., Wang, Y., Zhang, S.: Progressive feature enhancement for person re-identification. IEEE Trans. Image Process. 30, 8384\u20138395 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR16","doi-asserted-by":"crossref","unstructured":"Rao, Y., Chen, G., Lu, J., Zhou, J.: Counterfactual attention learning for fine-grained visual categorization and re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1025\u20131034 (2021)","DOI":"10.1109\/ICCV48922.2021.00106"},{"key":"3049_CR17","doi-asserted-by":"crossref","unstructured":"Yan, C., Pang, G., Wang, L., Jiao, J., Feng, X., Shen, C., Li, J.: Bv-person: a large-scale dataset for bird-view person re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10943\u201310952 (2021)","DOI":"10.1109\/ICCV48922.2021.01076"},{"issue":"1","key":"3049_CR18","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/TETCI.2020.3034606","volume":"5","author":"D Wu","year":"2021","unstructured":"Wu, D., Wang, C., Wu, Y., Wang, Q.-C., Huang, D.-S.: Attention deep model with multi-scale deep supervision for person re-identification. IEEE Trans. Emerg. Top. Comput. Intell. 5(1), 70\u201378 (2021)","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"3049_CR19","doi-asserted-by":"crossref","unstructured":"Zhao, S., Gao, C., Zhang, J., Cheng, H., Han, C., Jiang, X., Guo, X., Zheng, W.-S., Sang, N., Sun, X.: Do not disturb me: Person re-identification under the interference of other pedestrians. In: European Conference on Computer Vision, pp. 647\u2013663. Springer (2020)","DOI":"10.1007\/978-3-030-58539-6_39"},{"key":"3049_CR20","doi-asserted-by":"publisher","first-page":"7663","DOI":"10.1109\/TIP.2021.3107211","volume":"30","author":"G Chen","year":"2021","unstructured":"Chen, G., Gu, T., Lu, J., Bao, J.-A., Zhou, J.: Person re-identification via attention pyramid. IEEE Trans. Image Process. 30, 7663\u20137676 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR21","doi-asserted-by":"publisher","first-page":"203700","DOI":"10.1109\/ACCESS.2020.3036985","volume":"8","author":"Y Gong","year":"2020","unstructured":"Gong, Y., Wang, L., Li, Y., Du, A.: A discriminative person re-identification model with global\u2013local attention and adaptive weighted rank list loss. IEEE Access 8, 203700\u2013203711 (2020)","journal-title":"IEEE Access"},{"key":"3049_CR22","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"3049_CR23","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"3049_CR24","doi-asserted-by":"crossref","unstructured":"Li, W., Zhao, R., Xiao, T., Wang, X.: Deepreid: deep filter pairing neural network for person re-identification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 152\u2013159 (2014)","DOI":"10.1109\/CVPR.2014.27"},{"key":"3049_CR25","doi-asserted-by":"crossref","unstructured":"Wei, L., Zhang, S., Gao, W., Tian, Q.: Person transfer gan to bridge domain gap for person re-identification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 79\u201388 (2018)","DOI":"10.1109\/CVPR.2018.00016"},{"issue":"8","key":"3049_CR26","doi-asserted-by":"publisher","first-page":"3140","DOI":"10.1109\/TCSVT.2020.3037179","volume":"31","author":"S Lian","year":"2020","unstructured":"Lian, S., Jiang, W., Hu, H.: Attention-aligned network for person re-identification. IEEE Trans. Circuits Syst. Video Technol. 31(8), 3140\u20133153 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3049_CR27","doi-asserted-by":"publisher","first-page":"7104","DOI":"10.1109\/TIP.2020.2998931","volume":"29","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Xie, Y., Li, D., Zhang, W., Tian, Q.: Learning to align via Wasserstein for person re-identification. IEEE Trans. Image Process. 29, 7104\u20137116 (2020)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"3049_CR28","first-page":"5056","volume":"44","author":"K Zhou","year":"2021","unstructured":"Zhou, K., Yang, Y., Cavallaro, A., Xiang, T.: Learning generalisable omni-scale representations for person re-identification. IEEE Trans. Pattern Anal. Mach. Intell. 44(9), 5056\u20135069 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3049_CR29","doi-asserted-by":"crossref","unstructured":"Yang, J., Zhang, J., Yu, F., Jiang, X., Zhang, M., Sun, X., Chen, Y.-C., Zheng, W.-S.: Learning to know where to see: a visibility-aware approach for occluded person re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 11885\u201311894 (2021)","DOI":"10.1109\/ICCV48922.2021.01167"},{"key":"3049_CR30","doi-asserted-by":"crossref","unstructured":"Somers, V., De\u00a0Vleeschouwer, C., Alahi, A.: Body part-based representation learning for occluded person re-identification. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 1613\u20131623 (2023)","DOI":"10.1109\/WACV56688.2023.00166"},{"key":"3049_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108155","volume":"120","author":"Z Zhang","year":"2021","unstructured":"Zhang, Z., Zhang, H., Liu, S., Xie, Y., Durrani, T.S.: Part-guided graph convolution networks for person re-identification. Pattern Recognit. 120, 108155 (2021)","journal-title":"Pattern Recognit."},{"key":"3049_CR32","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Lan, C., Zeng, W., Jin, X., Chen, Z.: Relation-aware global attention for person re-identification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3186\u20133195 (2020)","DOI":"10.1109\/CVPR42600.2020.00325"},{"key":"3049_CR33","doi-asserted-by":"crossref","unstructured":"Liao, S., Shao, L.: Graph sampling based deep metric learning for generalizable person re-identification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7359\u20137368 (2022)","DOI":"10.1109\/CVPR52688.2022.00721"},{"key":"3049_CR34","doi-asserted-by":"publisher","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., Hu, Q.: Eca-net: efficient channel attention for deep convolutional neural networks. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11531\u201311539 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.01155","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"3049_CR35","doi-asserted-by":"crossref","unstructured":"Li, Y., He, J., Zhang, T., Liu, X., Zhang, Y., Wu, F.: Diverse part discovery: occluded person re-identification with part-aware transformer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2898\u20132907 (2021)","DOI":"10.1109\/CVPR46437.2021.00292"},{"key":"3049_CR36","doi-asserted-by":"crossref","unstructured":"He, S., Luo, H., Wang, P., Wang, F., Li, H., Jiang, W.: Transreid: transformer-based object re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 15013\u201315022 (2021)","DOI":"10.1109\/ICCV48922.2021.01474"},{"key":"3049_CR37","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"3049_CR38","doi-asserted-by":"crossref","unstructured":"Lai, S., Chai, Z., Wei, X.: Transformer meets part model: adaptive part division for person re-identification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4150\u20134157 (2021)","DOI":"10.1109\/ICCVW54120.2021.00461"},{"key":"3049_CR39","doi-asserted-by":"crossref","unstructured":"Pervaiz, N., Fraz, M., Shahzad, M.: Per-former: rethinking person re-identification using transformer augmented with self-attention and contextual mapping. Vis. Comput. 1\u201316 (2022)","DOI":"10.1007\/s00371-022-02577-0"},{"key":"3049_CR40","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"3049_CR41","doi-asserted-by":"crossref","unstructured":"Bolle, R.M., Connell, J.H., Pankanti, S., Ratha, N.K., Senior, A.W.: The relation between the roc curve and the cmc. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID\u201905), pp. 15\u201320. IEEE (2005)","DOI":"10.1109\/AUTOID.2005.48"},{"issue":"6","key":"3049_CR42","doi-asserted-by":"publisher","first-page":"2872","DOI":"10.1109\/TPAMI.2021.3054775","volume":"44","author":"M Ye","year":"2021","unstructured":"Ye, M., Shen, J., Lin, G., Xiang, T., Shao, L., Hoi, S.C.: Deep learning for person re-identification: a survey and outlook. IEEE Trans. Pattern Anal. Mach. Intell. 44(6), 2872\u20132893 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3049_CR43","doi-asserted-by":"crossref","unstructured":"He, L., Liu, W.: Guided saliency feature learning for person re-identification in crowded scenes. In: European Conference on Computer Vision, pp. 357\u2013373. Springer (2020)","DOI":"10.1007\/978-3-030-58604-1_22"},{"key":"3049_CR44","doi-asserted-by":"publisher","first-page":"2060","DOI":"10.1109\/TIP.2021.3050839","volume":"30","author":"Y Liu","year":"2021","unstructured":"Liu, Y., Zhou, W., Liu, J., Qi, G.-J., Tian, Q., Li, H.: An end-to-end foreground-aware network for person re-identification. IEEE Trans. Image Process. 30, 2060\u20132071 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, A., Gao, Y., Niu, Y., Liu, W., Zhou, Y.: Coarse-to-fine person re-identification with auxiliary-domain classification and second-order information bottleneck. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 598\u2013607 (2021)","DOI":"10.1109\/CVPR46437.2021.00066"},{"key":"3049_CR46","doi-asserted-by":"publisher","first-page":"1935","DOI":"10.1109\/TIP.2021.3049943","volume":"30","author":"X Chen","year":"2021","unstructured":"Chen, X., Zheng, X., Lu, X.: Bidirectional interaction network for person re-identification. IEEE Trans. Image Process. 30, 1935\u20131948 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR47","doi-asserted-by":"crossref","unstructured":"Gu, X., Chang, H., Ma, B., Bai, S., Shan, S., Chen, X.: Clothes-changing person re-identification with rgb modality only. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1060\u20131069 (2022)","DOI":"10.1109\/CVPR52688.2022.00113"},{"key":"3049_CR48","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhu, F., Tang, S., Zhao, R., He, L., Song, J.: Feature erasing and diffusion network for occluded person re-identification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4754\u20134763 (2022)","DOI":"10.1109\/CVPR52688.2022.00471"},{"key":"3049_CR49","doi-asserted-by":"publisher","first-page":"2936","DOI":"10.1007\/s11263-020-01349-4","volume":"128","author":"S Li","year":"2020","unstructured":"Li, S., Song, W., Fang, Z., Shi, J., Hao, A., Zhao, Q., Qin, H.: Long-short temporal\u2013spatial clues excited network for robust person re-identification. Int. J. Comput. Vis. 128, 2936\u20132961 (2020)","journal-title":"Int. J. Comput. Vis."},{"key":"3049_CR50","doi-asserted-by":"publisher","first-page":"7306","DOI":"10.1109\/TIP.2020.3000904","volume":"29","author":"N Martinel","year":"2020","unstructured":"Martinel, N., Foresti, G.L., Micheloni, C.: Deep pyramidal pooling with attention for person re-identification. IEEE Trans. Image Process. 29, 7306\u20137316 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"3049_CR51","doi-asserted-by":"crossref","unstructured":"Pu, N., Chen, W., Liu, Y., Bakker, E.M., Lew, M.S.: Lifelong person re-identification via adaptive knowledge accumulation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7901\u20137910 (2021)","DOI":"10.1109\/CVPR46437.2021.00781"},{"key":"3049_CR52","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03049-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-023-03049-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03049-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T16:53:23Z","timestamp":1729961603000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-023-03049-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,23]]},"references-count":52,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["3049"],"URL":"https:\/\/doi.org\/10.1007\/s00371-023-03049-9","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,23]]},"assertion":[{"value":"27 July 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 August 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}