{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:23:18Z","timestamp":1778692998981,"version":"3.51.4"},"reference-count":74,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Image Video Proc."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The work is focused on video compression for the scenarios, where the decoded video serves not only human viewers but also as input for systems implementing various machine vision tasks, such as object detection and tracking. The proposed innovative tool is based on retargeting video frames processed based on Regions of Interest (RoI), corresponding to the individual objects detected in the frames. Experimental evaluation demonstrates significant average bitrate reduction while maintaining the same quality, ranging from 3 to 57% depending on the machine vision task and encoding scenario. The proposal underwent thorough consideration within the MPEG group and was adopted for the upcoming Video Coding for Machines (VCM) technology.<\/jats:p>","DOI":"10.1186\/s13640-025-00682-3","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T09:17:04Z","timestamp":1761297424000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Video coding for machines using region-of-interest-based retargeting"],"prefix":"10.1186","volume":"2025","author":[{"given":"S\u0142awomir","family":"R\u00f3\u017cek","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9691-9094","authenticated-orcid":false,"given":"Olgierd","family":"Stankiewicz","sequence":"additional","affiliation":[]},{"given":"S\u0142awomir","family":"Ma\u0107kowiak","sequence":"additional","affiliation":[]},{"given":"Tomasz","family":"Grajek","sequence":"additional","affiliation":[]},{"given":"Jakub","family":"Stankowski","sequence":"additional","affiliation":[]},{"given":"Maciej","family":"Wawrzyniak","sequence":"additional","affiliation":[]},{"given":"Mateusz","family":"Lorkiewicz","sequence":"additional","affiliation":[]},{"given":"Ding","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Shan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Marek","family":"Doma\u0144ski","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"issue":"12","key":"682_CR1","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1109\/TCSVT.2012.2221191","volume":"22","author":"GJ Sullivan","year":"2012","unstructured":"G.J. Sullivan, J. Ohm, W.J. Han, T. Wiegand, Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649\u20131668 (2012)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"682_CR2","unstructured":"ITU-T Rec. H.265 | ISO\/IEC IS 23008-2, High efficiency coding and media delivery in heterogeneous environment \u2013 Part 2: High efficiency video coding"},{"key":"682_CR3","unstructured":"J. Chen, Y. Ye, S. Kim, Algorithm description for Versatile Video Coding and Test Model 3 (VTM3). Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO\/IEC JTC 1\/SC 29\/WG 11, Doc. JVET L1002, Macao, October 2018"},{"key":"682_CR4","unstructured":"ISO\/IEC DIS 23090\u20133 (2020) \/ ITU-T Recommendation H.266 (08\/2020), Versatile video coding"},{"issue":"10","key":"682_CR5","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1109\/TCSVT.2021.3101953","volume":"31","author":"B Bross","year":"2021","unstructured":"B. Bross, Y.-K. Wang, Y. Ye, S. Liu, J. Chen, G.J. Sullivan, J.-R. Ohm, Overview of the versatile video coding (VVC) standard and its applications. IEEE Trans. Circuits Syst. Video Technol. 31(10), 3736\u20133764 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"7","key":"682_CR6","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1109\/TCSVT.2003.815165","volume":"13","author":"T Wiegand","year":"2003","unstructured":"T. Wiegand, G.J. Sullivan, G. Bjontegaard, A. Luthra, Overview of the h. 264\/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13(7), 560\u2013576 (2003)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"682_CR7","doi-asserted-by":"publisher","first-page":"3171","DOI":"10.1007\/s11263-021-01530-3","volume":"129","author":"D Xu","year":"2021","unstructured":"D. Xu, R. Chellappa, L. Van Gool et al., Guest editorial: special issue on deep learning for video analysis and compression. Int. J. Comput. Vis. 129, 3171\u20133173 (2021). https:\/\/doi.org\/10.1007\/s11263-021-01530-3","journal-title":"Int. J. Comput. Vis."},{"key":"682_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-44660-3","volume-title":"Video object tracking: tasks, datasets, and methods. Springer synthesis lectures on computer vision (SLCV)","author":"N Xu","year":"2024","unstructured":"N. Xu, W. Lin, X. Lu, Y. Wei, Video object tracking: tasks, datasets, and methods. Springer synthesis lectures on computer vision (SLCV) (Springer, Cham, 2024)"},{"issue":"10","key":"682_CR9","doi-asserted-by":"publisher","first-page":"3095","DOI":"10.1109\/TCSVT.2018.2873102","volume":"29","author":"S Ma","year":"2018","unstructured":"S. Ma, X. Zhang, S. Wang, X. Zhang, C. Jia, S. Wang, Joint feature and texture coding: toward smart video representation via front-end intelligence. IEEE Trans. Circuits Syst. Video Technol. 29(10), 3095\u20133105 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"10","key":"682_CR10","doi-asserted-by":"publisher","first-page":"2889","DOI":"10.1007\/s11263-021-01505-4","volume":"129","author":"Q Zhang","year":"2021","unstructured":"Q. Zhang, S. Wang, X. Zhang, S. Ma, W. Gao, Just recognizable distortion for machine vision oriented image and video coding. Int. J. Comput. Vis. 129(10), 2889\u20132906 (2021)","journal-title":"Int. J. Comput. Vis."},{"issue":"1","key":"682_CR11","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1109\/TMM.2015.2502552","volume":"18","author":"J Chao","year":"2016","unstructured":"J. Chao, E. Steinbach, Keypoint encoding for improved feature extraction from compressed video at low bitrates. IEEE Trans. Multimedia 18(1), 25\u201339 (2016)","journal-title":"IEEE Trans. Multimedia"},{"key":"682_CR12","doi-asserted-by":"crossref","unstructured":"L. Galteri, M. Bertini, L. Seidenari, A. Del Bimbo, Video compression for object detection algorithms. 24th International Conference on Pattern Recognition (ICPR), (2018), p. 3007\u20133012","DOI":"10.1109\/ICPR.2018.8546064"},{"key":"682_CR13","doi-asserted-by":"publisher","first-page":"8680","DOI":"10.1109\/TIP.2020.3016485","volume":"29","author":"L Duan","year":"2020","unstructured":"L. Duan, J. Liu, W. Yang, T. Huang, W. Gao, Video coding for machines: a paradigm of collaborative compression and intelligent analytics. IEEE Trans. Image Process. 29, 8680\u20138695 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"682_CR14","doi-asserted-by":"crossref","unstructured":"K. Fischer, F. Brand, C. Herglotz, A. Kaup, Video Coding for Machines with Feature-Based Rate-Distortion Optimization. 22nd International Workshop on Multimedia Signal Processing (MMSP), (2020)","DOI":"10.1109\/MMSP48831.2020.9287136"},{"key":"682_CR15","doi-asserted-by":"crossref","unstructured":"Y. Lee, S. Kim, K. Yoon, H. Lim, S. Kwak, H.-G. Choo, Machine-attention-based Video Coding for Machines. 2023 IEEE International Conference on Image Processing (ICIP), (2023), p. 2700\u20132704","DOI":"10.1109\/ICIP49359.2023.10222037"},{"issue":"1","key":"682_CR16","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1109\/TCSVT.2007.913754","volume":"18","author":"Y Liu","year":"2008","unstructured":"Y. Liu, Z. Li, Y.C. Soh, Region-of-interest based resource allocation for conversational video communications of H.264\/AVC. IEEE Trans. Circuits Syst. Video Technol. 18(1), 134\u2013139 (2008)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"no. 4","key":"682_CR17","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1109\/TCSVT.2005.844458","volume":"15","author":"X Yang","year":"2005","unstructured":"X. Yang, W. Lin, Z. Lu, X. Lin, S. Rahardja, E.P. Ong, S. Yao, Rate control for videophone using local perceptual cues. IEEE Trans. Circuits Syst. Video Technol. 15(4), 496\u2013507 (2005)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"no. 6","key":"682_CR18","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1109\/TCSVT.2010.2045912","volume":"20","author":"Z Chen","year":"2010","unstructured":"Z. Chen, C. Guillemot, Perceptually-friendly H.264\/AVC video coding based on foveated just-noticeable-distortion model. IEEE Trans. Circuits Syst. Video Technol. 20(6), 806\u2013819 (2010)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"7","key":"682_CR19","doi-asserted-by":"publisher","first-page":"1366","DOI":"10.1109\/JSTSP.2011.2164779","volume":"5","author":"M Bosch","year":"2011","unstructured":"M. Bosch, F. Zhu, E.J. Delp, Segmentation-based video compression using texture and motion models. IEEE J. Sel. Top. Signal Process. 5(7), 1366\u20131377 (2011)","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"682_CR20","doi-asserted-by":"publisher","first-page":"3442","DOI":"10.1109\/TIP.2019.2960869","volume":"29","author":"C Cai","year":"2020","unstructured":"C. Cai, L. Chen, X. Zhang, Z. Gao, End-to-end optimized ROI image compression. IEEE Trans. Image Process. 29, 3442\u20133457 (2020). https:\/\/doi.org\/10.1109\/TIP.2019.2960869","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"682_CR21","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1109\/TIP.2013.2282897","volume":"23","author":"H Hadizadeh","year":"2014","unstructured":"H. Hadizadeh, I.V. Baji\u0107, Saliency-aware video compression. IEEE Trans. Image Process. 23(1), 19\u201333 (2014). https:\/\/doi.org\/10.1109\/TIP.2013.2282897","journal-title":"IEEE Trans. Image Process."},{"key":"682_CR22","doi-asserted-by":"crossref","unstructured":"V. Setlur, S. Takagi, R. Raskar, M. Gleicher, B. Gooch, Automatic image retargeting. Proceedings of the 4th International Conference on Mobile and Ubiquitous Multimedia, (2005)","DOI":"10.1145\/1149488.1149499"},{"issue":"6","key":"682_CR23","doi-asserted-by":"publisher","first-page":"160:1","DOI":"10.1145\/1882261.1866186","volume":"29","author":"M Rubinstein","year":"2010","unstructured":"M. Rubinstein, D. Gutierrez, O. Sorkine, A. Shamir, A comparative study of image retargeting. ACM Trans. Graph. 29(6), 160:1-160:10 (2010)","journal-title":"ACM Trans. Graph."},{"key":"682_CR24","doi-asserted-by":"publisher","unstructured":"F. Liu, M. Gleicher, Video retargeting: Automating pan and scan, (2006), p. 241\u2013250. https:\/\/doi.org\/10.1145\/1180639.1180702.","DOI":"10.1145\/1180639.1180702"},{"key":"682_CR25","doi-asserted-by":"publisher","unstructured":"R. Kharsa, R. Alzoubi, M. Alsmirat M. Al-Ayyoub, Image Retargeting Techniques Identification Using Supervised Deep Learning. 2023 Fourth International Conference on Intelligent Data Science Technologies and Applications (IDSTA), Kuwai, Kuwait, (2023), p. 15\u201320, https:\/\/doi.org\/10.1109\/IDSTA58916.2023.10317851.","DOI":"10.1109\/IDSTA58916.2023.10317851"},{"key":"682_CR26","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276390","author":"S Avidan","year":"2007","unstructured":"S. Avidan, A. Shamir, Seam carving for content-aware image resizing. SIGGRAPH (2007). https:\/\/doi.org\/10.1145\/1276377.1276390","journal-title":"SIGGRAPH"},{"issue":"3","key":"682_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1360612.1360615","volume":"27","author":"M Rubinstein","year":"2008","unstructured":"M. Rubinstein, A. Shamir, S. Avidan, Improved seam carving for video retargeting. ACM Trans. Graph. 27(3), 1\u20139 (2008). https:\/\/doi.org\/10.1145\/1360612.1360615","journal-title":"ACM Trans. Graph."},{"key":"682_CR28","doi-asserted-by":"publisher","unstructured":"L. Wolf, M. Guttmann, D. Cohen-Or, Non-homogeneous Content-driven Video-retargeting. Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on. 1, (2007), p. 1\u20136. https:\/\/doi.org\/10.1109\/ICCV.2007.4409010.","DOI":"10.1109\/ICCV.2007.4409010"},{"issue":"5","key":"682_CR29","doi-asserted-by":"publisher","DOI":"10.1145\/1409060.1409071","volume":"27","author":"Y-S Wang","year":"2008","unstructured":"Y.-S. Wang, C.-L. Tai, O. Sorkine, T.-Y. Lee, Optimized scale-and-stretch for image resizing. ACM Trans. Graph. 27(5), Article 118 (2008). https:\/\/doi.org\/10.1145\/1409060.1409071","journal-title":"ACM Trans. Graph."},{"key":"682_CR30","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1111\/j.1467-8659.2012.03001.x","volume":"31","author":"D Panozzo","year":"2012","unstructured":"D. Panozzo, O. Weber, O. Sorkine, Robust image retargeting via axis-aligned deformation. Comput. Graph. Forum. 31, 229\u2013236 (2012). https:\/\/doi.org\/10.1111\/j.1467-8659.2012.03001.x","journal-title":"Comput. Graph. Forum."},{"issue":"3","key":"682_CR31","doi-asserted-by":"publisher","DOI":"10.1145\/1531326.1531329","volume":"28","author":"M Rubinstein","year":"2009","unstructured":"M. Rubinstein, A. Shamir, S. Avidan, Multi-operator media retargeting. ACM Trans. Graph. 28(3), Article 23 (2009). https:\/\/doi.org\/10.1145\/1531326.1531329","journal-title":"ACM Trans. Graph."},{"key":"682_CR32","doi-asserted-by":"publisher","unstructured":"Y. Pritch, E. Kav-Venaki, S. Peleg, Shift-Map Image Editing. Proceedings of the IEEE International Conference on Computer Vision, (2009),p. 151\u2013158. https:\/\/doi.org\/10.1109\/ICCV.2009.5459159","DOI":"10.1109\/ICCV.2009.5459159"},{"key":"682_CR33","doi-asserted-by":"publisher","unstructured":"Z. Zhang, B. Kang, H. Li, Improved seam carving for content-aware image retargeting. 2013 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia), Visakhapatnam, India, (2013), pp. 254\u2013257, https:\/\/doi.org\/10.1109\/PrimeAsia.2013.6731216","DOI":"10.1109\/PrimeAsia.2013.6731216"},{"issue":"10","key":"682_CR34","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1049\/iet-ipr.2015.0559","volume":"10","author":"HC Hsin","year":"2016","unstructured":"H.C. Hsin, Saliency histogram equalisation and its application to image resizing. IET Image Process. 10(10), 787\u2013798 (2016)","journal-title":"IET Image Process."},{"key":"682_CR35","doi-asserted-by":"publisher","first-page":"1862","DOI":"10.1049\/iet-ipr.2019.0236","volume":"13","author":"H Kaur","year":"2019","unstructured":"H. Kaur, S. Kour, D. Sen, Video retargeting through spatio-temporal seam carving using Kalman filter. IET Image Proc. 13, 1862\u20131871 (2019). https:\/\/doi.org\/10.1049\/iet-ipr.2019.0236","journal-title":"IET Image Proc."},{"issue":"1","key":"682_CR36","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1109\/TCSVT.2020.2977943","volume":"31","author":"Y Zhou","year":"2020","unstructured":"Y. Zhou, Z. Chen, W. Li, Weakly supervised reinforced multi-operator image retargeting. IEEE Trans. Circuits Syst. Video Technol. 31(1), 126\u2013139 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"682_CR37","doi-asserted-by":"crossref","unstructured":"R. Kharsa, R. Alzoubi, M. Alsmirat, M. Al-Ayyoub, Image Retargeting Techniques Identification Using Supervised Deep Learning. In 2023 Fourth International Conference on Intelligent Data Science Technologies and Applications (IDSTA), (2023, October), p 15\u201320. IEEE.","DOI":"10.1109\/IDSTA58916.2023.10317851"},{"key":"682_CR38","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/ACCESS.2018.2885347","volume":"7","author":"E Song","year":"2018","unstructured":"E. Song, M. Lee, S. Lee, CarvingNet: content-guided seam carving using deep convolution neural network. IEEE Access 7, 284\u2013292 (2018)","journal-title":"IEEE Access"},{"key":"682_CR39","doi-asserted-by":"crossref","unstructured":"J. Wu, R. Xie, L. Song, B. Liu, Deep feature guided image retargeting. In 2019 IEEE Visual Communications and Image Processing (VCIP), (2019, December), pp. 1\u20134. IEEE.","DOI":"10.1109\/VCIP47243.2019.8966008"},{"issue":"8","key":"682_CR40","doi-asserted-by":"publisher","first-page":"11917","DOI":"10.1007\/s11042-020-10185-0","volume":"80","author":"M Ahmadi","year":"2021","unstructured":"M. Ahmadi, N. Karimi, S. Samavi, Context-aware saliency detection for image retargeting using convolutional neural networks. Multimedia Tools Appl. 80(8), 11917\u201311941 (2021)","journal-title":"Multimedia Tools Appl."},{"key":"682_CR41","doi-asserted-by":"publisher","unstructured":"D. Cho, J. Park, T.H. Oh, Y-W. Tai, I. Kweon, Weakly- and Self-Supervised Learning for Content-Aware Deep Image Retargeting, (2017), p. 4568\u20134577. https:\/\/doi.org\/10.1109\/ICCV.2017.488","DOI":"10.1109\/ICCV.2017.488"},{"issue":"7","key":"682_CR42","doi-asserted-by":"publisher","first-page":"1730","DOI":"10.1109\/TMM.2019.2959925","volume":"22","author":"W Tan","year":"2019","unstructured":"W. Tan, B. Yan, C. Lin, X. Niu, Cycle-ir: deep cyclic image retargeting. IEEE Trans. Multimedia 22(7), 1730\u20131743 (2019)","journal-title":"IEEE Trans. Multimedia"},{"key":"682_CR43","doi-asserted-by":"publisher","unstructured":"Y. Mei, X. Guo, D. Sun, G. Pan, J. Zhang, Deep Supervised Image Retargeting. 2021 IEEE International Conference on Multimedia and Expo (ICME), Shenzhen, China, (2021), p. 1\u20136, https:\/\/doi.org\/10.1109\/ICME51207.2021.9428129","DOI":"10.1109\/ICME51207.2021.9428129"},{"key":"682_CR44","unstructured":"ISO\/IEC, Conclusions of 127th meeting. ISO\/IEC JTC 1\/SC 29\/WG 11, MPEG doc. N18540, July 2019"},{"key":"682_CR45","unstructured":"J. Ascenso, E. Upenik, White Paper on JPEG AI Scope and Framework. ISO\/IEC JTC 1\/SC 29\/WG1, MPEG doc. N90049, 2021"},{"key":"682_CR46","unstructured":"ISO\/IEC JTC1\/SC29\/WG2, Use cases and requirements for Video Coding for Machines. MPEG doc. N18, October 2020"},{"key":"682_CR47","unstructured":"ISO\/IEC JTC1\/SC29\/WG2, Use cases and requirements for Video Coding for Machines. MPEG doc. N0043, January 2021"},{"key":"682_CR48","unstructured":"ISO\/IEC JTC 1\/SC 29\/WG 2, Call for Proposals for Video Coding for Machines. MPEG doc. N191, April 2022"},{"key":"682_CR49","unstructured":"ISO\/IEC JTC 1\/SC 29\/WG 2, CfP response report for Video Coding for Machines. MPEG doc. N248, October 2022"},{"key":"682_CR50","unstructured":"ISO\/IEC JTC 1\/SC 29\/WG 4, Algorithm description of tools in VCM reference software. MPEG doc. N418, December 2023"},{"key":"682_CR51","doi-asserted-by":"crossref","unstructured":"H. Chen, Y. Xu, Video Coding for Machines Based on Motion Assisted Saliency Analysis. Lecture Notes in Computer Science book series, Springer LNCS, 14357, (2023)","DOI":"10.1007\/978-3-031-46311-2_31"},{"key":"682_CR52","unstructured":"S.-K. Kim, M. H. Jeong, J. Y. Lee, H.-K. Lee, H.-G. Choo, S.-H. Jung, [VCM] CfP response: Region-of-Interest based video coding for machine. ISO\/IEC JTC1\/SC29\/WG2 m60758, October 2022"},{"key":"682_CR53","unstructured":"Video Coding for Machines Reference Software, available for MPEG experts: https:\/\/git.mpeg.expert\/MPEG\/Video\/VCM\/VCM-RS"},{"key":"682_CR54","doi-asserted-by":"crossref","unstructured":"J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You Only Look Once: Unified, Real-Time Object Detection. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2016), p. 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"issue":"6","key":"682_CR55","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"S. Ren, K. He, R. Girshick et al., Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"682_CR56","doi-asserted-by":"publisher","first-page":"1016","DOI":"10.1175\/1520-0450(1979)018<1016:LFIOAT>2.0.CO;2","volume":"18","author":"CE Duchon","year":"1979","unstructured":"C.E. Duchon, Lanczos filtering in one and two dimensions. J. Appl. Meteorol. 18(8), 1016\u20131022 (1979)","journal-title":"J. Appl. Meteorol."},{"key":"682_CR57","unstructured":"ISO\/IEC JTC 1\/SC 29\/WG 04, Common test conditions for video coding for machines. MPEG doc. N419, October 2023"},{"key":"682_CR58","unstructured":"Y. Wu, A. Kirillov, F. Massa, et al. Detectron2, https:\/\/github.com\/facebookresearch\/detectron2"},{"key":"682_CR59","doi-asserted-by":"crossref","unstructured":"Z. Wang, L. Zheng, Y. Liu, et al. Towards real-time multi-object tracking. In European Conference on Computer Vision (ECCV), (2020), p. 107\u2013122","DOI":"10.1007\/978-3-030-58621-8_7"},{"key":"682_CR60","unstructured":"H. Choi, E. Hosseini, S. R. Alvar, R. A. Cohen, I. V. Baji\u0107, A. Karabutov, Z. Yin, E. Alshina, [VCM] Object labelled dataset on raw video sequences. ISO\/IEC JTC1\/SC29\/WG11 MPEG doc. m54737, July 2020."},{"key":"682_CR61","doi-asserted-by":"crossref","unstructured":"X. Xu, S. Liu, Z. Li, A Video Dataset for Learning-based Visual Data Compression and Analysis. In 2021 International Conference on Visual Communications and Image Processing (VCIP), Dec.\u00a02021.","DOI":"10.1109\/VCIP53242.2021.9675343"},{"issue":"146","key":"682_CR62","first-page":"10","volume":"2006","author":"S Tomar","year":"2006","unstructured":"S. Tomar, Converting video formats with FFmpeg. Linux J. 2006(146), 10 (2006)","journal-title":"Linux J."},{"issue":"2","key":"682_CR63","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"M. Everingham, L. Van Gool, C.K.I. Williams, J. Winn, A. Zisserman, The PASCAL visual object classes (VOC) challenge. Int. J. Comput. Vis. 88(2), 303\u2013338 (2010). https:\/\/doi.org\/10.1007\/s11263-009-0275-4","journal-title":"Int. J. Comput. Vis."},{"issue":"1","key":"682_CR64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2008\/246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"K. Bernardin, R. Stiefelhagen, Evaluating multiple object tracking performance: the CLEAR MOT metrics. EURASIP J. Image Video Process. 2008(1), 1\u201310 (2008)","journal-title":"EURASIP J. Image Video Process."},{"key":"682_CR65","unstructured":"G. Bj\u00f8ntegaard, Calculation of average PSNR differences between RD-curves. ITU SG16 Doc. VCEG-M33, (2001)"},{"key":"682_CR66","unstructured":"G. Bj\u00f8ntegaard, Improvements of the BD-PSNR model. ITU-T SG16 Q.6 document VCEG-AI11, (2023)"},{"key":"682_CR67","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4302-6713-3","volume-title":"Video quality metrics. In Digital video concepts, methods, and metrics","author":"S Akramullah","year":"2014","unstructured":"S. Akramullah, Video quality metrics. In Digital video concepts, methods, and metrics (Apress, Berkeley, 2014)"},{"key":"682_CR68","unstructured":"A. M. Tourapis, D. Singer, Y. Su, K. Mammou, Bd-rate\/BD-PSNR excel extensions. ISO\/IEC JTC1\/SC29\/WG11 M41482, (2017)"},{"key":"682_CR69","doi-asserted-by":"crossref","unstructured":"S. R\u00f3\u017cek, O. Stankiewicz, S. Ma\u0107kowiak, T. Grajek, M. Wawrzyniak, J. Stankowski, M. Lorkiewicz, D. Cywi\u0144ski, J. Szekie\u0142da, M. Doma\u0144ski, [VCM] Improved RoI preprocessing and retargeting for VCM. ISO\/IEC JTC1\/SC29\/WG4, MPEG doc. m66523, (January, 2024)","DOI":"10.1109\/ICMEW63481.2024.10645441"},{"key":"682_CR70","unstructured":"M. Doma\u0144ski, O. Stankiewicz, S. Ma\u0107kowiak, S. R\u00f3\u017cek, T. Grajek, J. Szekie\u0142da, D. Cywi\u0144ski, J. Siejak, [VCM] Pozna\u0144 University of Technology Proposals A and B in response to CfP on Video Coding for Machines. ISO\/IEC JTC1\/SC29\/WG4, MPEG doc. m61519, (October, 2022)"},{"key":"682_CR71","doi-asserted-by":"crossref","unstructured":"S. R\u00f3\u017cek, O. Stankiewicz, S. Ma\u0107kowiak and M. Doma\u0144ski, Video Coding for Machines using Object Analysis and Standard Video Codecs. 2023 IEEE International Conference on Visual Communications and Image Processing (VCIP), Jeju, Republic of Korea, (2023), p. 1\u20135","DOI":"10.1109\/VCIP59821.2023.10402642"},{"key":"682_CR72","unstructured":"D. Ding [VCM] crosscheck of m66523. ISO\/IEC JTC1\/SC29WG4 MPEG doc. m66778, (January, 2024)"},{"key":"682_CR73","unstructured":"Q. Li Fang, H. Wang, Y. Zhang (China Telecom), [VCM] Cross-check of m66523. ISO\/IEC JTC1\/SC29WG4 MPEG doc. m66769, (January, 2024)"},{"key":"682_CR74","unstructured":"H. Yang, S. Wang, C. Lin, [VCM] Crosscheck report for m66523. ISO\/IEC JTC1\/SC29WG4 MPEG doc. m66907, (January, 2024)"}],"container-title":["EURASIP Journal on Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-025-00682-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13640-025-00682-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13640-025-00682-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T09:17:20Z","timestamp":1761297440000},"score":1,"resource":{"primary":{"URL":"https:\/\/jivp-eurasipjournals.springeropen.com\/articles\/10.1186\/s13640-025-00682-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":74,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["682"],"URL":"https:\/\/doi.org\/10.1186\/s13640-025-00682-3","relation":{},"ISSN":["1687-5281"],"issn-type":[{"value":"1687-5281","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"1 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"18"}}