{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T23:52:17Z","timestamp":1781826737395,"version":"3.54.5"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP210200213"],"award-info":[{"award-number":["LP210200213"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100023630","name":"Faculty of Information Technology, Monash University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100023630","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Field-captured video enables detailed study of animal locomotion, decision-making, and environmental interactions such as predator\u2013prey dynamics and habitat use. While low-cost hardware makes data capture accessible, the storage, processing, and transmission demands of high-resolution video remain a major hurdle for field-deployed edge computing devices. Motion tracking in natural environments presents unique challenges that require tailored video compression strategies not well addressed in other domains. We present a novel end-to-end system comprising a motion analysis-based video compression algorithm specifically designed for camera traps, and a custom video processing methodology for automated analysis of compressed footage to extract behavioural data. We evaluate it through a case study on insect\u2013pollinator motion tracking using three popular edge computing platforms. The compression algorithm operates alongside standard codecs, identifying and storing only image regions containing motion relevant to monitoring tasks, reducing data size by an average of 87% across diverse datasets. When combined with the H.265\/HEVC codec, our approach achieved an additional 47.1% improvement in compression compared to stand-alone H.265. The accompanying video processing algorithm builds upon existing Polytrack software, incorporating new preprocessing and trajectory reconstruction techniques for automated processing of compressed footage with a 97.5% detection rate. Our experiments demonstrate that the system retains critical behavioural information, as verified through both automated and manual analyses. The method presented in this paper enhances the applicability of low-powered computer vision edge devices to remote,\n                    <jats:italic>in situ<\/jats:italic>\n                    animal motion monitoring, and improves the efficiency of playback during behavioural analyses.\n                  <\/jats:p>","DOI":"10.1007\/s11263-026-02803-5","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T06:50:08Z","timestamp":1775544608000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Motion-Based Compression and Tracking System for Video Camera Trap-Based Insect Behaviour Studies"],"prefix":"10.1007","volume":"134","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0976-7019","authenticated-orcid":false,"given":"Malika Nisal","family":"Ratnayake","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0992-2139","authenticated-orcid":false,"given":"Lex","family":"Gallon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5655-5337","authenticated-orcid":false,"given":"Adel N.","family":"Toosi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5456-4835","authenticated-orcid":false,"given":"Alan","family":"Dorin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,7]]},"reference":[{"issue":"6","key":"2803_CR1","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.3390\/rs12061004","volume":"12","author":"Z Ahmed","year":"2020","unstructured":"Ahmed, Z., Hussain, A. J., Khan, W., Baker, T., Al-Askar, H., Lunn, J., & Liatsis, P. (2020). Lossy and lossless video frame compression: A novel approach for high-temporal video data analytics. Remote Sensing, 12(6), 1004.","journal-title":"Remote Sensing"},{"key":"2803_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2023.107707","volume":"207","author":"R Arablouei","year":"2023","unstructured":"Arablouei, R., Wang, L., Currie, L., Yates, J., Alvarenga, F. A., & Bishop-Hurley, G. J. (2023). Animal behavior classification via deep learning on embedded systems. Computers and Electronics in Agriculture, 207, Article 107707.","journal-title":"Computers and Electronics in Agriculture"},{"key":"2803_CR3","doi-asserted-by":"crossref","unstructured":"Bansal, A., Sikka, K., Sharma, G., Chellappa, R., & Divakaran, A. (2018). Zero-shot object detection. Proceedings of the european conference on computer vision (eccv) (pp. 384\u2013400).","DOI":"10.1007\/978-3-030-01246-5_24"},{"key":"2803_CR4","doi-asserted-by":"crossref","unstructured":"Bjerge, K., Mann, H. M., & H\u00f8ye, T. T. (2021). Real-time insect tracking and monitoring with computer vision and deep learning. Remote Sensing in Ecology and Conservation.","DOI":"10.1002\/rse2.245"},{"issue":"16","key":"2803_CR5","doi-asserted-by":"publisher","first-page":"7242","DOI":"10.3390\/s23167242","volume":"23","author":"K Bjerge","year":"2023","unstructured":"Bjerge, K., Frigaard, C. E., & Karstoft, H. (2023). Object detection of small insects in time-lapse camera recordings. Sensors, 23(16), 7242.","journal-title":"Sensors"},{"issue":"1","key":"2803_CR6","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1111\/1365-2664.13755","volume":"58","author":"TD Breeze","year":"2021","unstructured":"Breeze, T. D., Bailey, A. P., Balcombe, K. G., Brereton, T., Comont, R., Edwards, M., et al. (2021). Pollinator monitoring more than pays for itself. Journal of Applied Ecology, 58(1), 44\u201357.","journal-title":"Journal of Applied Ecology"},{"issue":"3","key":"2803_CR7","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1002\/rse2.48","volume":"3","author":"A Caravaggi","year":"2017","unstructured":"Caravaggi, A., Banks, P. B., Burton, A. C., Finlay, C. M., Haswell, P. M., Hayward, M. W., & Wood, M. D. (2017). A review of camera trapping for conservation behaviour research. Remote Sensing in Ecology and Conservation, 3(3), 109\u2013122.","journal-title":"Remote Sensing in Ecology and Conservation"},{"issue":"18","key":"2803_CR8","doi-asserted-by":"publisher","first-page":"7527","DOI":"10.1002\/ece3.3275","volume":"7","author":"RA Collett","year":"2017","unstructured":"Collett, R. A., & Fisher, D. O. (2017). Time-lapse camera trapping as an alternative to pitfall trapping for estimating activity of leaf litter arthropods. Ecology and Evolution, 7(18), 7527\u20137533.","journal-title":"Ecology and Evolution"},{"issue":"Suppl. 1","key":"2803_CR9","first-page":"100","volume":"6","author":"SC Dharmarathne","year":"2022","unstructured":"Dharmarathne, S. C., Jayasekara, E., Mahaulpatha, D., & de Silva, K. (2022). Camera trap data reveals the habitat use and activity patterns of a secretive forest bird, Sri Lanka spurfowl galloperdix bicalcarata. Journal of Wildlife and Biodiversity, 6(Suppl. 1), 100\u2013118.","journal-title":"Journal of Wildlife and Biodiversity"},{"issue":"9","key":"2803_CR10","doi-asserted-by":"publisher","first-page":"3823","DOI":"10.3390\/app14093823","volume":"14","author":"X Dou","year":"2024","unstructured":"Dou, X., Cao, X., & Zhang, X. (2024). Region-of-interest based coding scheme for live videos. Applied Sciences, 14(9), 3823.","journal-title":"Applied Sciences"},{"issue":"8","key":"2803_CR11","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1111\/2041-210X.13618","volume":"12","author":"V Droissart","year":"2021","unstructured":"Droissart, V., Azandi, L., Onguene, E. R., Savignac, M., Smith, T. B., & Deblauwe, V. (2021). Pict: A low-cost, modular, open-source camera trap system to study plant-insect interactions. Methods in Ecology and Evolution, 12(8), 1389\u20131396.","journal-title":"Methods in Ecology and Evolution"},{"issue":"10","key":"2803_CR12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0048073","volume":"7","author":"LG Faber","year":"2012","unstructured":"Faber, L. G., Maurits, N. M., & Lorist, M. M. (2012). Mental fatigue affects visual selective attention. PloS one, 7(10), Article e48073.","journal-title":"PloS one"},{"key":"2803_CR13","unstructured":"Fairhurst, G., Nazir, S., & Verdicchio, F. (2013). Sensor-based digital platform for remote environmental monitoring: National telford institute (wireless sensor networking and its engineering applications). Wireless sensor networking and its engineering applications: New directions in measurement and control."},{"issue":"5","key":"2803_CR14","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1111\/ddi.13237","volume":"27","author":"J Feng","year":"2021","unstructured":"Feng, J., Sun, Y., Li, H., Xiao, Y., Zhang, D., Smith, J. L., & Wang, T. (2021). Assessing mammal species richness and occupancy in a northeast asian temperate forest shared by cattle. Diversity and Distributions, 27(5), 857\u2013872.","journal-title":"Diversity and Distributions"},{"key":"2803_CR15","unstructured":"Food & Agriculture Organization (2019). Global action on pollination services for sustainable agriculture."},{"issue":"1","key":"2803_CR16","doi-asserted-by":"publisher","first-page":"4463","DOI":"10.1038\/s41467-023-40231-y","volume":"14","author":"E Gazzea","year":"2023","unstructured":"Gazzea, E., Bat\u00e1ry, P., & Marini, L. (2023). Global meta-analysis shows reduced quality of food crops under inadequate animal pollination. Nature communications, 14(1), 4463.","journal-title":"Nature communications"},{"key":"2803_CR17","doi-asserted-by":"crossref","unstructured":"Gebauer, E., Thiele, S., Ouvrard, P., Sicard, A., & Risse, B. (2024). Towards a dynamic vision sensor-based insect camera trap. Proceedings of the ieee\/cvf winter conference on applications of computer vision (pp. 7157\u20137166).","DOI":"10.1109\/WACV57701.2024.00700"},{"issue":"2","key":"2803_CR18","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1002\/rse2.309","volume":"9","author":"SE Green","year":"2023","unstructured":"Green, S. E., Stephens, P. A., Whittingham, M. J., & Hill, R. A. (2023). Camera trapping with photos and videos: implications for ecology and citizen science. Remote Sensing in Ecology and Conservation, 9(2), 268\u2013283.","journal-title":"Remote Sensing in Ecology and Conservation"},{"issue":"6","key":"2803_CR19","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1017\/S0266467412000612","volume":"28","author":"JS Head","year":"2012","unstructured":"Head, J. S., Robbins, M. M., Mundry, R., Makaga, L., & Boesch, C. (2012). Remote video-camera traps measure habitat use and competitive exclusion among sympatric chimpanzee, gorilla and elephant in loango national park, gabon. Journal of Tropical Ecology, 28(6), 571\u2013583.","journal-title":"Journal of Tropical Ecology"},{"issue":"4","key":"2803_CR20","doi-asserted-by":"publisher","first-page":"1378","DOI":"10.1093\/icb\/icab095","volume":"61","author":"J Janisch","year":"2021","unstructured":"Janisch, J., Mitoyen, C., Perinot, E., Spezie, G., Fusani, L., & Quigley, C. (2021). Video recording and analysis of avian movements and behavior: Insights from courtship case studies. Integrative and Comparative Biology, 61(4), 1378\u20131393.","journal-title":"Integrative and Comparative Biology"},{"key":"2803_CR21","unstructured":"Jocher, G., & Qiu, J. (2024). Ultralytics yolo11. Retrieved from https:\/\/github.com\/ultralytics\/ultralytics"},{"issue":"18","key":"2803_CR22","doi-asserted-by":"publisher","first-page":"9304","DOI":"10.1002\/ece3.4438","volume":"8","author":"SL Krauss","year":"2018","unstructured":"Krauss, S. L., Roberts, D. G., Phillips, R. D., & Edwards, C. (2018). Effectiveness of camera traps for quantifying daytime and nighttime visitation by vertebrate pollinators. Ecology and Evolution, 8(18), 9304\u20139314.","journal-title":"Ecology and Evolution"},{"key":"2803_CR23","doi-asserted-by":"crossref","unstructured":"Le, H., Zhang, L., Said, A., Sautiere, G., Yang, Y., Shrestha, P., & Wiggers, A. (2022). Mobilecodec: neural inter-frame video compression on mobile devices. Proceedings of the 13th acm multimedia systems conference (pp. 324\u2013330).","DOI":"10.1145\/3524273.3532906"},{"issue":"1","key":"2803_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3368405","volume":"53","author":"D Liu","year":"2020","unstructured":"Liu, D., Li, Y., Lin, J., Li, H., & Wu, F. (2020). Deep learning-based video coding: A review and a case study. ACM Computing Surveys (CSUR), 53(1), 1\u201335.","journal-title":"ACM Computing Surveys (CSUR)"},{"issue":"3","key":"2803_CR25","doi-asserted-by":"publisher","DOI":"10.1002\/ece3.8746","volume":"12","author":"C Lovell","year":"2022","unstructured":"Lovell, C., Li, S., Turner, J., & Carbone, C. (2022). The effect of habitat and human disturbance on the spatiotemporal activity of two urban carnivores: The results of an intensive camera trap study. Ecology and evolution, 12(3), Article e8746.","journal-title":"Ecology and evolution"},{"issue":"4","key":"2803_CR26","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1038\/s42256-022-00477-5","volume":"4","author":"M Marks","year":"2022","unstructured":"Marks, M., Jin, Q., Sturman, O., von Ziegler, L., Kollmorgen, S., von der Behrens, W., & Yanik, M. F. (2022). Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments. Nature machine intelligence, 4(4), 331\u2013340.","journal-title":"Nature machine intelligence"},{"key":"2803_CR27","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.sajb.2014.12.009","volume":"97","author":"CA Melidonis","year":"2015","unstructured":"Melidonis, C. A., & Peter, C. I. (2015). Diurnal pollination, primarily by a single species of rodent, documented in protea foliosa using modified camera traps. South African Journal of Botany, 97, 9\u201315.","journal-title":"South African Journal of Botany"},{"issue":"6","key":"2803_CR28","doi-asserted-by":"publisher","DOI":"10.1002\/ece3.8962","volume":"12","author":"Q Naqvi","year":"2022","unstructured":"Naqvi, Q., Wolff, P. J., Molano-Flores, B., & Sperry, J. H. (2022). Camera traps are an effective tool for monitoring insect-plant interactions. Ecology and Evolution, 12(6), Article e8962.","journal-title":"Ecology and Evolution"},{"key":"2803_CR29","doi-asserted-by":"crossref","unstructured":"Nyk\u00e4nen, M., P\u00f6ys\u00e4, H., Matala, J., & Kunnasranta, M. (2023). Motion detection or time lapse? a comparison of camera trap triggers in the monitoring of elusive ground dwelling birds.","DOI":"10.22541\/au.168571094.40987973\/v1"},{"issue":"3","key":"2803_CR30","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1111\/jzo.12849","volume":"313","author":"C Ortmann","year":"2021","unstructured":"Ortmann, C., & Johnson, S. (2021). How reliable are motion-triggered camera traps for detecting small mammals and birds in ecological studies? Journal of Zoology, 313(3), 202\u2013207.","journal-title":"Journal of Zoology"},{"key":"2803_CR31","unstructured":"Peleg, S., & Pritch, Y. (2012). Method and system for video indexing and video synopsis (No. US8311277B2). Retrieved from https:\/\/patents.google.com\/patent\/US8311277B2\/en"},{"key":"2803_CR32","unstructured":"Pennebaker, W. B., & Mitchell, J. L. (1992). Jpeg: Still image data compression standard. Springer Science & Business Media."},{"key":"2803_CR33","unstructured":"Perugachi-Diaz, Y., Sauti\u00e8re, G., Abati, D., Yang, Y., Habibian, A., & Cohen, T. S. (2022). Region-of-interest based neural video compression. arXiv preprint arXiv:2203.01978."},{"issue":"1","key":"2803_CR34","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s10211-020-00335-w","volume":"23","author":"LE Rampim","year":"2020","unstructured":"Rampim, L. E., Sartorello, L. R., Fragoso, C. E., Haberfeld, M., & Devlin, A. L. (2020). Antagonistic interactions between predator and prey: Mobbing of jaguars (panthera onca) by white-lipped peccaries (tayassu pecari). Acta Ethologica, 23(1), 45\u201348.","journal-title":"Acta Ethologica"},{"key":"2803_CR35","unstructured":"Ratnayake, M. N., Amarathunga, D. C., Zaman, A., Dyer, A. G., & Dorin, A. (2022). Spatial Monitoring and Insect Behavioural Analysis Dataset."},{"key":"2803_CR36","unstructured":"Ratnayake, M. N., Dyer, A., & Dorin, A. (2020). Honeybee video tracking data."},{"key":"2803_CR37","unstructured":"Ratnayake, M. N., Dyer, A. G., & Dorin, A. (2021a). Towards computer vision and deep learning facilitated pollination monitoring for agriculture. Proceedings of the ieee\/cvf conference on computer vision and pattern recognition (pp. 2921\u20132930)."},{"issue":"3","key":"2803_CR38","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s11263-022-01715-4","volume":"131","author":"MN Ratnayake","year":"2023","unstructured":"Ratnayake, M. N., Amarathunga, D. C., Zaman, A., Dyer, A. G., & Dorin, A. (2023). Spatial monitoring and insect behavioural analysis using computer vision for precision pollination. International Journal of Computer Vision, 131(3), 591\u2013606.","journal-title":"International Journal of Computer Vision"},{"issue":"2","key":"2803_CR39","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0239504","volume":"16","author":"MN Ratnayake","year":"2021","unstructured":"Ratnayake, M. N., Dyer, A. G., & Dorin, A. (2021). Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring. Plos one, 16(2), Article e0239504.","journal-title":"Plos one"},{"issue":"4","key":"2803_CR40","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1111\/aje.12913","volume":"59","author":"SJ Reece","year":"2021","unstructured":"Reece, S. J., Radloff, F. G., Leslie, A. J., Amin, R., & Tambling, C. J. (2021). A camera trap appraisal of species richness and community composition of medium and large mammals in a miombo woodland reserve. African Journal of Ecology, 59(4), 898\u2013911.","journal-title":"African Journal of Ecology"},{"key":"2803_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2021.101215","volume":"61","author":"F Schindler","year":"2021","unstructured":"Schindler, F., & Steinhage, V. (2021). Identification of animals and recognition of their actions in wildlife videos using deep learning techniques. Ecological Informatics, 61, Article 101215.","journal-title":"Ecological Informatics"},{"issue":"1904","key":"2803_CR42","doi-asserted-by":"publisher","first-page":"20230106","DOI":"10.1098\/rstb.2023.0106","volume":"379","author":"JK Sheard","year":"2024","unstructured":"Sheard, J. K., Adriaens, T., Bowler, D. E., B\u00fcermann, A., Callaghan, C. T., Camprasse, E. C., et al. (2024). Emerging technologies in citizen science and potential for insect monitoring. Philosophical Transactions of the Royal Society B, 379(1904), 20230106.","journal-title":"Philosophical Transactions of the Royal Society B"},{"issue":"9","key":"2803_CR43","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1068\/p281059","volume":"28","author":"DJ Simons","year":"1999","unstructured":"Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: Sustained inattentional blindness for dynamic events. Perception, 28(9), 1059\u20131074.","journal-title":"Perception"},{"key":"2803_CR44","doi-asserted-by":"crossref","unstructured":"Sittinger, M., Uhler, J., Pink, M., & Herz, A. (2023). Insect detect: An open-source diy camera trap for automated insect monitoring. bioRxiv, 2023\u201312","DOI":"10.1101\/2023.12.05.570242"},{"issue":"4","key":"2803_CR45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0295474","volume":"19","author":"M Sittinger","year":"2024","unstructured":"Sittinger, M., Uhler, J., Pink, M., & Herz, A. (2024). Insect detect: An open-source diy camera trap for automated insect monitoring. Plos one, 19(4), Article e0295474.","journal-title":"Plos one"},{"issue":"12","key":"2803_CR46","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1109\/TCSVT.2012.2221191","volume":"22","author":"GJ Sullivan","year":"2012","unstructured":"Sullivan, G. J., Ohm, J.-R., Han, W.-J., & Wiegand, T. (2012). Overview of the high efficiency video coding (hevc) standard. IEEE Transactions on circuits and systems for video technology, 22(12), 1649\u20131668.","journal-title":"IEEE Transactions on circuits and systems for video technology"},{"issue":"6","key":"2803_CR47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0098881","volume":"9","author":"KR Swinnen","year":"2014","unstructured":"Swinnen, K. R., Reijniers, J., Breno, M., & Leirs, H. (2014). A novel method to reduce time investment when processing videos from camera trap studies. PloS one, 9(6), Article e98881.","journal-title":"PloS one"},{"issue":"15","key":"2803_CR48","doi-asserted-by":"publisher","first-page":"1976","DOI":"10.3390\/ani12151976","volume":"12","author":"M Tan","year":"2022","unstructured":"Tan, M., Chao, W., Cheng, J.-K., Zhou, M., Ma, Y., Jiang, X., & Feng, L. (2022). Animal detection and classification from camera trap images using different mainstream object detection architectures. Animals, 12(15), 1976.","journal-title":"Animals"},{"issue":"3","key":"2803_CR49","doi-asserted-by":"publisher","first-page":"791","DOI":"10.3390\/s24030791","volume":"24","author":"V-I Ungureanu","year":"2024","unstructured":"Ungureanu, V.-I., Negirla, P., & Korodi, A. (2024). Image-compression techniques: Classical and \u201cregion-of-interest-based\u2019\u2019 approaches presented in recent papers. Sensors, 24(3), 791.","journal-title":"Sensors"},{"key":"2803_CR50","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.13191","volume":"10","author":"GE van der Voort","year":"2022","unstructured":"van der Voort, G. E., Gilmore, S. R., Gorrell, J. C., & Janes, J. K. (2022). Continuous video capture, and pollinia tracking, in platanthera (orchidaceae) reveal new insect visitors and potential pollinators. PeerJ, 10, Article e13191.","journal-title":"PeerJ"},{"key":"2803_CR51","doi-asserted-by":"crossref","unstructured":"van Klink, R., August, T., Bas, Y., Bodesheim, P., Bonn, A., Foss\u00f8y, F., H\u00f8ye, T. T., Jongejans, E., Menz, Myles H. M., Miraldo, A., et al. (2022). Emerging technologies revolutionise insect ecology and monitoring. Trends in ecology & evolution.","DOI":"10.1016\/j.tree.2022.06.001"},{"key":"2803_CR52","doi-asserted-by":"crossref","unstructured":"Van\u00a0Klink, R., Sheard, J. K., H\u00f8ye, T. T., Roslin, T., Do\u00a0Nascimento, L. A., & Bauer, S. (2024). Towards a toolkit for global insect biodiversity monitoring (Vol.\u00a0379) (No. 1904). The Royal Society.","DOI":"10.1098\/rstb.2023.0101"},{"issue":"7","key":"2803_CR53","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1109\/TCSVT.2003.815165","volume":"13","author":"T Wiegand","year":"2003","unstructured":"Wiegand, T., Sullivan, G. J., Bjontegaard, G., & Luthra, A. (2003). Overview of the h. 264\/avc video coding standard. IEEE Transactions on circuits and systems for video technology, 13(7), 560\u2013576.","journal-title":"IEEE Transactions on circuits and systems for video technology"},{"issue":"5","key":"2803_CR54","doi-asserted-by":"publisher","first-page":"836","DOI":"10.1111\/2041-210X.14322","volume":"15","author":"K Wittmann","year":"2024","unstructured":"Wittmann, K., Gamal Ibrahim, M., Straw, A. D., Klein, A.-M., & Staab, M. (2024). Monitoring fast-moving animals\u2013building a customized camera system and evaluation toolset. Methods in Ecology and Evolution, 15(5), 836\u2013842.","journal-title":"Methods in Ecology and Evolution"},{"key":"2803_CR55","doi-asserted-by":"crossref","unstructured":"Wong, W.-M., & Kachel, S. (2024). Camera trapping\u2014advancing the technology. Snow leopards (pp. 415\u2013428). Elsevier.","DOI":"10.1016\/B978-0-323-85775-8.00018-2"},{"key":"2803_CR56","doi-asserted-by":"crossref","unstructured":"Zett, T., Stratford, K. J., & Weise, F. J. (2022). Inter-observer variance and agreement of wildlife information extracted from camera trap images. Biodiversity and Conservation,31(12), 3019\u20133037.","DOI":"10.1007\/s10531-022-02472-z"},{"key":"2803_CR57","doi-asserted-by":"crossref","unstructured":"Zualkernan, I., Dhou, S., Judas, J., Sajun, A. R., Gomez, B. R., & Hussain, L. A. (2022). An iot system using deep learning to classify camera trap images on the edge. Computers,11(1), 13.","DOI":"10.3390\/computers11010013"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-026-02803-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-026-02803-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-026-02803-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T23:07:44Z","timestamp":1781824064000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-026-02803-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,7]]},"references-count":57,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["2803"],"URL":"https:\/\/doi.org\/10.1007\/s11263-026-02803-5","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,7]]},"assertion":[{"value":"29 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 April 2026","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The original version is revised due to update Table 1 in PDF version","order":7,"name":"change_details","label":"Change Details","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":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"220"}}