{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:41:45Z","timestamp":1772844105384,"version":"3.50.1"},"reference-count":86,"publisher":"Springer Science and Business Media LLC","issue":"19","license":[{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"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":["Appl Intell"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The use of virtual reality or augmented reality systems in billiards sports are useful tools for pure entertainment or improving the player\u2019s skills. Depending on the purpose of these systems, tracking algorithms based on computer vision must be used. These algorithms are especially useful in systems aiming to reconstruct the trajectories followed by the balls after a strike. However, depending on the billiard modality, the problem of tracking multiple small identical objects, such as balls, is a complex task. In addition, when an amateur or nontop professional player uses low-frame-rate and low-resolution devices, problems such as blurred balls, blurred contours, or fuzzy edges, among others, arise. These effects have a negative impact on ball-tracking accuracy and reconstruction quality. Thus, this work proposes two contributions. The first contribution is a new tracking algorithm called<jats:italic>\u201cmultiobject local tracking (MOLT)\u201d<\/jats:italic>. This algorithm can track balls with high precision and accuracy even with motion blur caused by low-resolution and low-frame-rate devices. Moreover, the proposed MOLT algorithm is compared with nine tracking methods and four different metrics, outperforming the rest of the methods in the majority of the cases and providing a robust solution. The second contribution is a whole system to track (using the MOLT algorithm) and reconstruct the movements of the balls on a billiard table in a 3D virtual world using computer vision. The proposed system covers all steps from image capture to 3D reconstruction. The 3D reconstruction results have been qualitatively evaluated by different users through a series of questionnaires, obtaining an overall score of 7.6 (out of 10), which indicates that the system is a promising and useful tool for training. Finally, both the MOLT algorithm and the reconstruction system are tested in three billiard modalities: blackball, carom billiards, and snooker.<\/jats:p>","DOI":"10.1007\/s10489-023-04542-3","type":"journal-article","created":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T16:45:27Z","timestamp":1686069927000},"page":"21543-21575","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["3D reconstruction system and multiobject local tracking algorithm designed for billiards"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3560-1407","authenticated-orcid":false,"given":"Francisco J.","family":"Rodriguez-Lozano","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan C.","family":"G\u00e1mez-Granados","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H\u00e9ctor","family":"Mart\u00ednez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose M.","family":"Palomares","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joaqu\u00edn","family":"Olivares","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,6]]},"reference":[{"key":"4542_CR1","doi-asserted-by":"crossref","unstructured":"Chen J, Zhenghao X, Ji J (2022) Multi-object tracking based on network flow model and orb feature. Appl Intell","DOI":"10.1007\/s10489-021-03042-6"},{"key":"4542_CR2","doi-asserted-by":"publisher","first-page":"103448","DOI":"10.1016\/j.artint.2020.103448","volume":"293","author":"W Luo","year":"2021","unstructured":"Luo W, Xing J, Milan A, Zhang X, Liu W, Kim T-K (2021) Multiple object tracking: a literature review. Artif Intell 293:103448","journal-title":"Artif Intell"},{"issue":"35","key":"4542_CR3","first-page":"5","volume":"181","author":"A Parihar","year":"2019","unstructured":"Parihar A, Nagarkar P, Bhosale V, Desale K (2019) Survey on multiple objects tracking in video analytics. Int J Comput Appl 181(35):5\u20139","journal-title":"Int J Comput Appl"},{"issue":"6","key":"4542_CR4","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s00530-018-0586-9","volume":"24","author":"W Kim","year":"2018","unstructured":"Kim W, Moon S-W, Lee J, Nam D-W, Jung C (2018) Multiple player tracking in soccer videos: an adaptive multiscale sampling approach. Multimedia Syst 24(6):611\u2013623","journal-title":"Multimedia Syst"},{"issue":"7","key":"4542_CR5","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1109\/TCSVT.2015.2455713","volume":"26","author":"S Baysal","year":"2016","unstructured":"Baysal S, Duygulu P (2016) Sentioscope: a soccer player tracking system using model field particles. IEEE Trans Circuits Syst Video Technol 26(7):1350\u20131362","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"3","key":"4542_CR6","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1007\/s10462-017-9582-2","volume":"52","author":"PR Kamble","year":"2017","unstructured":"Kamble PR, Keskar AG, Bhurchandi KM (2017) Ball tracking in sports: a survey. Artif Intell Rev 52(3):1655\u20131705","journal-title":"Artif Intell Rev"},{"key":"4542_CR7","doi-asserted-by":"publisher","first-page":"3117","DOI":"10.3233\/JIFS-189350","volume":"40","author":"Z Li","year":"2021","unstructured":"Li Z, Li X, Shi M, Song W, Zhao G, Yang R, Li S (2021) Tracking algorithm of snowboard target in intelligent system. J Intell Fuzzy Syst 40:3117\u20133125","journal-title":"J Intell Fuzzy Syst"},{"key":"4542_CR8","doi-asserted-by":"crossref","unstructured":"Moon S, Lee J, Nam D, Kim H, Kim W (2017) A comparative study on multi-object tracking methods for sports events. In: 2017 19Th international conference on advanced communication technology (ICACT), pp 883\u2013885","DOI":"10.23919\/ICACT.2017.7890221"},{"key":"4542_CR9","unstructured":"Dave Alciatore (2022) Glossary of pool and billiards terms and phrases. https:\/\/billiards.colostate.edu\/glossary\/"},{"key":"4542_CR10","doi-asserted-by":"crossref","unstructured":"Haar S, van Assel CM, Faisal AA (2020) Motor learning in real-world pool billiards. Sci Rep 10(1)","DOI":"10.1038\/s41598-020-76805-9"},{"issue":"07","key":"4542_CR11","doi-asserted-by":"publisher","first-page":"157","DOI":"10.36348\/JASPE.2019.v02i07.006","volume":"02","author":"MA Elmagd","year":"2019","unstructured":"Elmagd MA (2019) Is billiards considered a sport?. J Adv Sports Phys Educ 02(07):157\u2013161","journal-title":"J Adv Sports Phys Educ"},{"key":"4542_CR12","doi-asserted-by":"publisher","first-page":"012022","DOI":"10.1088\/1755-1315\/243\/1\/012022","volume":"243","author":"B Supriadi","year":"2019","unstructured":"Supriadi B, Lesmono AD, Prastowo SHB, Prihandono T, Subiki Ridlo ZR, Rosyadi FA (2019) Study of central and non-central collisions in billiard games. IOP Conf Ser: Earth Environ Sci 243:012022","journal-title":"IOP Conf Ser: Earth Environ Sci"},{"issue":"1","key":"4542_CR13","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1177\/1071181319631294","volume":"63","author":"E Thai","year":"2019","unstructured":"Thai E, Kumar AR (2019) How haptic feedback in a mixed reality pool game affects real-life pool performance. Proc Hum Factors Ergon Soc Annu Meet 63(1):2323\u20132327","journal-title":"Proc Hum Factors Ergon Soc Annu Meet"},{"key":"4542_CR14","unstructured":"World Confederation of Billiards Sports (2022) How to play Carom. https:\/\/wcbs.sport\/sports\/how-to-play-carom\/"},{"key":"4542_CR15","unstructured":"The World Professional Billiards and Snooker Association (2022) Official rules of the game of snooker and english billiards. The World Professional Billiards & Snooker Association Limited (WPBSA)"},{"key":"4542_CR16","unstructured":"World Pool-Billiard Association (2016) The Rules of Play - Version 15.03.2016. https:\/\/wpapool.com\/rules-of-play\/"},{"key":"4542_CR17","unstructured":"The World Pool-Billiard Association (WPA) (2018) Bring billiards as an additional sport to the Olympic Games Paris 2024. https:\/\/wpapool.com\/bring-billiards-as-an-additional-sport-to-the-olympic-games-paris-2024-2\/"},{"key":"4542_CR18","doi-asserted-by":"crossref","unstructured":"Ling Y, Li S, Xu P, Zhou B (2012) The detection of multi-objective billiards in snooker game video. In: 2012 Third international conference on intelligent control and information processing, pp 594\u2013596. IEEE","DOI":"10.1109\/ICICIP.2012.6391406"},{"issue":"1\u20132","key":"4542_CR19","first-page":"187","volume":"41","author":"JBTM Roerdink","year":"2000","unstructured":"Roerdink JBTM, Meijster A (2000) The watershed transform: Definitions, algorithms and parallelization strategies. Fundam Inf 41(1\u20132):187\u2013228","journal-title":"Fundam Inf"},{"key":"4542_CR20","doi-asserted-by":"crossref","unstructured":"Legg PA, Parry ML, Chung DHS, Jiang RM, Morris A, Griffiths IW, Marshall D, Chen M (2011) Intelligent filtering by semantic importance for single-view 3d reconstruction from snooker video. In: 2011 18th IEEE international conference on image processing, pp 2385\u20132388. IEEE, Belgium","DOI":"10.1109\/ICIP.2011.6116122"},{"issue":"12","key":"4542_CR21","doi-asserted-by":"publisher","first-page":"1747","DOI":"10.1109\/TVCG.2011.208","volume":"17","author":"ML Parry","year":"2011","unstructured":"Parry ML, Legg PA, Chung DHS, Griffiths IW, Chen M (2011) Hierarchical event selection for video storyboards with a case study on snooker video visualization. IEEE Trans Vis Comput Graphics 17(12):1747\u20131756","journal-title":"IEEE Trans Vis Comput Graphics"},{"key":"4542_CR22","unstructured":"Vachaspati P (2012) A computer vision system for 9-ball pool. Technical Report Massachusetts Institute of Technology"},{"key":"4542_CR23","unstructured":"Baekdahl BJ, Have S (2011) Detection and identification of pool balls using computer vision. PhD thesis, Vision, Graphics and Interactive Systems, Aalborg University"},{"key":"4542_CR24","unstructured":"Weatherford S (2013) Pool cue guide determination of guide vectors under adverse lighting, view aspect and scale. Technical Report, Department of Electrical Engineering, Stanford University, Stanford, United States"},{"key":"4542_CR25","doi-asserted-by":"crossref","unstructured":"Uchiyama H, Saito H (2007) AR Display of visual aids for supporting pool games by online markerless tracking","DOI":"10.1109\/ICAT.2007.35"},{"issue":"2\u20133","key":"4542_CR26","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.cviu.2003.06.005","volume":"92","author":"H Denman","year":"2003","unstructured":"Denman H, Rea N, Kokaram A (2003) Content-based analysis for video from snooker broadcasts. Comput Vis Image Underst 92(2\u20133):176\u2013195","journal-title":"Comput Vis Image Underst"},{"key":"4542_CR27","doi-asserted-by":"crossref","unstructured":"Hsu C-C, Tsai H-C, Chen H-T, Tsai W-J, Lee S-Y (2017) Computer-assisted billiard self-training using intelligent glasses. In: 2017 14Th international symposium on pervasive systems, algorithms and networks & 2017 11th international conference on frontier of computer science and technology & 2017 third international symposium of creative computing (ISPAN-FCST-ISCC). IEEE, Exeter, Devon, United Kingdom","DOI":"10.1109\/ISPAN-FCST-ISCC.2017.36"},{"key":"4542_CR28","doi-asserted-by":"crossref","unstructured":"Larsen LB, Jensen RB, Jensen KL, Larsen S (2005) Development of an automatic pool trainer. In: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, pp 83\u201387. ACM Press, Spain","DOI":"10.1145\/1178477.1178488"},{"issue":"2","key":"4542_CR29","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1007\/s41095-016-0047-3","volume":"2","author":"L Sousa","year":"2016","unstructured":"Sousa L, Alves R, Rodrigues JMF (2016) Augmented reality system to assist inexperienced pool players. Comput Vis Med 2(2):183\u2013193","journal-title":"Comput Vis Med"},{"key":"4542_CR30","doi-asserted-by":"crossref","unstructured":"Gao J, He Q, Zhan Z, Gao H (2016) Dynamic modeling based on fuzzy neural network for a billiard robot. In: 2016 IEEE 13Th international conference on networking, sensing, and control (ICNSC), pp 1\u20134","DOI":"10.1109\/ICNSC.2016.7478996"},{"key":"4542_CR31","doi-asserted-by":"crossref","unstructured":"Park J, Park J (2015) CAMshift algorithm based on geometric information for fast billiard ball tracking. In: 2015 12Th international conference on ubiquitous robots and ambient intelligence (URAI), pp 137\u2013138. IEEE, Korea","DOI":"10.1109\/URAI.2015.7358843"},{"issue":"2","key":"4542_CR32","doi-asserted-by":"publisher","first-page":"2145","DOI":"10.1007\/s11042-021-11673-7","volume":"81","author":"L Pei","year":"2021","unstructured":"Pei L, Zhang H, Yang B (2021) Improved camshift object tracking algorithm in occluded scenes based on AKAZE and kalman. Multimed Tools Appl 81(2):2145\u20132159","journal-title":"Multimed Tools Appl"},{"key":"4542_CR33","unstructured":"Gao J, He Q, Gao H, Zhan Z, Wu Z (2018) Design of an efficient multi-objective recognition approach for 8-ball billiards vision system. Kuwait journal of science 45"},{"key":"4542_CR34","doi-asserted-by":"crossref","unstructured":"Davies ER (2018) Chapter 11 - the generalized hough transform. In: Davies E.R. (ed) Computer vision (fifth edition), fifth edition edn., pp 299\u2013339. Academic press","DOI":"10.1016\/B978-0-12-809284-2.00011-3"},{"key":"4542_CR35","unstructured":"Alhajj R, Rokne J (eds) (2018) Convolutional neural network. Springer, NY"},{"issue":"6","key":"4542_CR36","doi-asserted-by":"publisher","first-page":"065002","DOI":"10.1088\/1361-6552\/aba207","volume":"55","author":"R Cross","year":"2020","unstructured":"Cross R (2020) Impact force between two colliding billiard balls. Phys Educ 55(6):065002","journal-title":"Phys Educ"},{"key":"4542_CR37","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/978-3-662-44415-3_23","volume":"8621","author":"A Gabdulkhakova","year":"2014","unstructured":"Gabdulkhakova A, Kropatsch WG (2014) Video analysis of a snooker footage based on a kinematic model. Structural, Syntactic, and Statistical Pattern Recognition 8621:223\u2013232","journal-title":"Structural, Syntactic, and Statistical Pattern Recognition"},{"issue":"9","key":"4542_CR38","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1119\/1.3157159","volume":"77","author":"S Mathavan","year":"2009","unstructured":"Mathavan S, Jackson MR, Parkin RM (2009) Application of high-speed imaging to determine the dynamics of billiards. Am J Phys 77(9):788","journal-title":"Am J Phys"},{"issue":"1","key":"4542_CR39","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1109\/TMECH.2015.2461547","volume":"21","author":"S Mathavan","year":"2016","unstructured":"Mathavan S, Jackson MR, Parkin RM (2016) Ball positioning in robotic billiards: a nonprehensile manipulation-based solution. IEEE\/ASME Trans Mechatronics 21(1):184\u2013195","journal-title":"IEEE\/ASME Trans Mechatronics"},{"key":"4542_CR40","doi-asserted-by":"crossref","unstructured":"Tung KG, Wen Wang S, Tai WK, Lor Way D, Chang CC (2019) Toward human-like billiard ai bot based on backward induction and machine learning. In: 2019 IEEE Symposium series on computational intelligence (SSCI), pp 924\u2013932","DOI":"10.1109\/SSCI44817.2019.9003085"},{"key":"4542_CR41","unstructured":"Bhagat KH (2018) Automatic Snooker-Playing Robot with Speech Recognition Using Deep Learning. PhD thesis, California State University, Long BeachProQuest Dissertations Publishing, Degree Year2018 10977867"},{"key":"4542_CR42","doi-asserted-by":"publisher","first-page":"061006","DOI":"10.1115\/1.4039876","volume":"13","author":"L Menini","year":"2018","unstructured":"Menini L, Possieri C, Tornamb\u00e8 A (2018) Tracking of a bouncing ball in a planar billiard through continuous-time approximations. J Comput Nonlinear Dyn 13:061006","journal-title":"J Comput Nonlinear Dyn"},{"issue":"2","key":"4542_CR43","doi-asserted-by":"publisher","first-page":"6195","DOI":"10.1016\/j.ifacol.2020.12.1712","volume":"53","author":"L Menini","year":"2020","unstructured":"Menini L, Possieri C, Tornamb\u00e8 A (2020) Trajectory tracking in rectangular billiards by unfolding the billiard table. IFAC-PapersOnLine 53(2):6195\u20136200. 21st IFAC World Congress","journal-title":"IFAC-PapersOnLine"},{"issue":"0","key":"4542_CR44","first-page":"1","volume":"0","author":"L Menini","year":"2021","unstructured":"Menini L, Possieri C, Tornamb\u00e8 A (2021) Trajectory tracking of a bouncing ball in a triangular billiard by unfolding and folding the billiard table. Int J Control 0(0):1\u201314","journal-title":"Int J Control"},{"key":"4542_CR45","doi-asserted-by":"crossref","unstructured":"Yu J, Huang Y, He Y (2018) Snooker video event detection using multimodal features. In: Proceedings of the 1st International Workshop on Multimedia Content Analysis in Sports. ACM, Seoul, Korea","DOI":"10.1145\/3265845.3265847"},{"key":"4542_CR46","doi-asserted-by":"crossref","unstructured":"Li S, Li B, Lu H, Xiao J (2021) Snooker match outcome prediction using ANN with inception structure. In: 2021 International conference on applications and techniques in cyber intelligence, pp 351\u2013359. Springer, Fuyang, China","DOI":"10.1007\/978-3-030-79200-8_51"},{"key":"4542_CR47","doi-asserted-by":"crossref","unstructured":"Sun Z, Chen J, Zhou H, Zhou D, Li L, Jiang M (2019) Graspsnooker: Automatic chinese commentary generation for snooker videos. In: Proceedings of the 28th International joint conference on artificial intelligence. International joint conferences on artificial intelligence organization, Macao, China","DOI":"10.24963\/ijcai.2019\/959"},{"issue":"5","key":"4542_CR48","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1260\/1747-9541.9.5.1083","volume":"9","author":"DHS Chung","year":"2014","unstructured":"Chung DHS, Griffiths IW, Legg PA, Parry ML, Morris A, Chen M, Griffiths W, Thomas A (2014) Systematic snooker skills test to analyze player performance. Int J Sports Sci Coaching 9(5):1083\u20131105","journal-title":"Int J Sports Sci Coaching"},{"issue":"3","key":"4542_CR49","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1016\/j.ejor.2021.04.056","volume":"296","author":"JAP Collingwood","year":"2022","unstructured":"Collingwood JAP, Wright M, Brooks RJ (2022) Evaluating the effectiveness of different player rating systems in predicting the results of professional snooker matches. Eur J Oper Res 296 (3):1025\u20131035","journal-title":"Eur J Oper Res"},{"key":"4542_CR50","doi-asserted-by":"crossref","unstructured":"Jebara T, Eyster C, Weaver J, Starner T, Pentland A (1997) Stochasticks: augmenting the billiards experience with probabilistic vision and wearable computers. In: Digest of papers. First international symposium on wearable computers, pp 138\u2013145. IEEE Comput. Soc, USA","DOI":"10.1109\/ISWC.1997.629930"},{"key":"4542_CR51","unstructured":"Medved S (2020) Augmented reality billiards assistant. Williams Honors College, Honors Research Projects. 1104. https:\/\/ideaexchange.uakron.edu\/honors_research_projects\/1104"},{"issue":"7","key":"4542_CR52","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1016\/j.knosys.2009.11.018","volume":"23","author":"C Shih","year":"2010","unstructured":"Shih C (2010) Aiming strategy error analysis and verification of a billiard training system. Knowl-Based Syst 23(7):732\u2013742","journal-title":"Knowl-Based Syst"},{"issue":"03","key":"4542_CR53","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1142\/S0219622014500278","volume":"13","author":"C Shih","year":"2014","unstructured":"Shih C (2014) Analyzing and comparing shot planning strategies and their effects on the performance of an augment reality based billiard training system. Int J Inf Technol Decis Making 13 (03):521\u2013565","journal-title":"Int J Inf Technol Decis Making"},{"key":"4542_CR54","doi-asserted-by":"crossref","unstructured":"Paolis LTD, Aloisio G, Pulimeno M (2009) A simulation of a billiards game based on marker detection. In: 2009 Second international conferences on advances in computer-human interactions. IEEE, Mexico","DOI":"10.1109\/ACHI.2009.19"},{"key":"4542_CR55","doi-asserted-by":"crossref","unstructured":"Mishima M, Suganuma A (2016) Development of stance correction system for billiard beginner player. In: 2016 International symposium on intelligent signal processing and communication systems (ISPACS), pp 1\u20135. IEEE, Thailand","DOI":"10.1109\/ISPACS.2016.7824701"},{"key":"4542_CR56","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.12988\/ces.2017.79116","volume":"10","author":"DMR Pinzon","year":"2017","unstructured":"Pinzon DMR, Gonzalez ECV, Gomez EJ (2017) Billiard game parameters calculation using a depth camera for augmented reality applications. Contemp Eng Sci 10:1171\u20131180","journal-title":"Contemp Eng Sci"},{"key":"4542_CR57","doi-asserted-by":"crossref","unstructured":"Wu F, Dellinger A (2017) Capturing reality for a billiards simulation. In: De paolis, LT, Bourdot, P, Mongelli, A (eds) Augmented Reality, Virtual Reality and Computer Graphics, pp 289\u2013298, Springer, Cham","DOI":"10.1007\/978-3-319-60922-5_23"},{"key":"4542_CR58","doi-asserted-by":"crossref","unstructured":"Kato J, Nakashima T, Takeoka H, Ogasawara K, Murao K, Shimokawa T, Sugimoto M (2013) Openpool: Community-based prototyping of digitally-augmented billiard table. In: 2013 IEEE 2nd global conference on consumer electronics (GCCE). IEEE, Japan","DOI":"10.1109\/GCCE.2013.6664790"},{"key":"4542_CR59","doi-asserted-by":"crossref","unstructured":"Dymora P, Mazurek M, Smalara K (2021) Modeling and fault tolerance analysis of zigbee protocol in iot networks. Energies 14(24)","DOI":"10.3390\/en14248264"},{"key":"4542_CR60","unstructured":"OpenCV team (2022) The OpenCV Reference Manual - 4.6.0. https:\/\/docs.opencv.org\/4.6.0\/"},{"key":"4542_CR61","doi-asserted-by":"crossref","unstructured":"Bugarinovi\u0107 Z, Pajewski L, Risti\u0107 A, Vrtunski M, Govedarica M, Borisov M (2020) On the introduction of canny operator in an advanced imaging algorithm for real-time detection of hyperbolas in ground-penetrating radar data. Electronics 9(3)","DOI":"10.3390\/electronics9030541"},{"key":"4542_CR62","doi-asserted-by":"crossref","unstructured":"Min Allah N, Jan F, Alrashed S (2021) Pupil detection schemes in human eye: a review. Multimed Syst 27","DOI":"10.1007\/s00530-021-00806-5"},{"key":"4542_CR63","unstructured":"Gonzalez RC, Woods RE (2018) Intensity transformations and spatial filtering. In: Digital Image Processing, 4nd edn., pp 119\u2013202. Addison-Wesley Longman Publishing Co., Inc. USA. Chap. 3"},{"issue":"5","key":"4542_CR64","doi-asserted-by":"publisher","first-page":"2001","DOI":"10.1007\/s10489-018-1372-2","volume":"49","author":"A Lopez-Martinez","year":"2019","unstructured":"Lopez-Martinez A, Cuevas FJ (2019) Automatic circle detection on images using the teaching learning based optimization algorithm and gradient analysis. Appl Intell 49(5):2001\u20132016","journal-title":"Appl Intell"},{"issue":"1","key":"4542_CR65","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1007\/s10489-020-01792-3","volume":"51","author":"C Li","year":"2021","unstructured":"Li C, Liu J, Wu Q, Bi L (2021) An adaptive enhancement method for low illumination color images. Appl Intell 51(1):202\u2013222","journal-title":"Appl Intell"},{"key":"4542_CR66","doi-asserted-by":"crossref","unstructured":"Xu H, Ding C, Li P, Ji Y (2022) An active learning algorithm based on the distribution principle of bhattacharyya distance Mathematics 10(11)","DOI":"10.3390\/math10111927"},{"key":"4542_CR67","volume-title":"Introduction to Algorithms, Fourth Edition","author":"HC Thomas","year":"2022","unstructured":"Thomas HC, Charles EL, Ronald LR, Stein C (2022) Introduction to Algorithms, Fourth Edition. The MIT Press, Cambridge"},{"key":"4542_CR68","unstructured":"ISO\/IEC 19775-1:2022 (2022) Information technology \u2014Computer graphics, image processing and environmental data representation - Extensible 3D (X3D) - Part 1: Architecture and base components. Standard, International Organization for Standardization"},{"key":"4542_CR69","unstructured":"NVIDIA Corporation (2021) Jetson Nano Developer Kit. https:\/\/developer.nvidia.com\/embedded\/jetson-nano-developer-kit"},{"key":"4542_CR70","unstructured":"Rodriguez-Lozano FJ (2022) Billiard-dataset. https:\/\/github.com\/FJ-Rodriguez-Lozano\/Billiard-dataset"},{"key":"4542_CR71","doi-asserted-by":"crossref","unstructured":"Rodriguez-Lozano FJ, Le\u00f3n-Garc\u00eda F, Ruiz de Adana M, Palomares JM, Olivares J (2019) Non-invasive forehead segmentation in thermographic imaging. Sensors 19(19)","DOI":"10.3390\/s19194096"},{"key":"4542_CR72","doi-asserted-by":"crossref","unstructured":"Zheng X, Lei Q, Yao R, Gong Y, Yin Q (2018) Image segmentation based on adaptive k-means algorithm. EURASIP Journal on Image and Video Processing 2018(1)","DOI":"10.1186\/s13640-018-0309-3"},{"key":"4542_CR73","doi-asserted-by":"publisher","first-page":"2294","DOI":"10.1109\/ACCESS.2020.3046763","volume":"9","author":"J Chen","year":"2021","unstructured":"Chen J, Xi Z, Wei C, Lu J, Niu Y, Li Z (2021) Multiple object tracking using edge multi-channel gradient model with orb feature. IEEE Access 9:2294\u20132309","journal-title":"IEEE Access"},{"key":"4542_CR74","doi-asserted-by":"crossref","unstructured":"Li J, Ding Y, Wei H-L, Zhang Y, Lin W (2022) Simpletrack: Rethinking and improving the jde approach for multi-object tracking. Sensors 22(15)","DOI":"10.3390\/s22155863"},{"issue":"19","key":"4542_CR75","doi-asserted-by":"publisher","first-page":"19060","DOI":"10.1109\/JSEN.2022.3196262","volume":"22","author":"B Rodrigues","year":"2022","unstructured":"Rodrigues B, Scheid EJ, Willems J, Tornow M, M\u00fcller KOE, Stiller B (2022) Fusion data tracking system (fits). IEEE Sensors J 22(19):19060\u201319072","journal-title":"IEEE Sensors J"},{"key":"4542_CR76","doi-asserted-by":"crossref","unstructured":"Dardagan N, Branin A, D\u017eigal D, Akagic A (2021) Multiple object trackers in opencv: A benchmark. In: 2021 IEEE 30th international symposium on industrial electronics (ISIE), pp 1\u20136","DOI":"10.1109\/ISIE45552.2021.9576367"},{"key":"4542_CR77","doi-asserted-by":"crossref","unstructured":"Boosting algorithm (2021). In: Ikeuchi, K. (ed.) Computer Vision, pp 110\u2013110. Springer","DOI":"10.1007\/978-3-030-63416-2_300341"},{"key":"4542_CR78","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1016\/j.ins.2018.12.080","volume":"481","author":"C Fu","year":"2019","unstructured":"Fu C, Duan R, Kayacan E (2019) Visual tracking with online structural similarity-based weighted multiple instance learning. Inf Sci 481:292\u2013310","journal-title":"Inf Sci"},{"key":"4542_CR79","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1016\/j.procs.2018.04.199","volume":"131","author":"Z NaNa","year":"2018","unstructured":"NaNa Z, Jin Z (2018) Optimization of face tracking based on KCF and camshift. Procedia Comput Sci 131:158\u2013166","journal-title":"Procedia Comput Sci"},{"issue":"1","key":"4542_CR80","first-page":"201","volume":"14","author":"Z Chen","year":"2020","unstructured":"Chen Z, Huang D, Luo L, Wen M (2020) And, C.Z.: Efficient parallel tld on cpu-gpu platform for real-time tracking. KSII Trans Int Inf Syst 14(1):201\u2013220","journal-title":"KSII Trans Int Inf Syst"},{"issue":"3","key":"4542_CR81","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1080\/03772063.2018.1492356","volume":"66","author":"CS Asha","year":"2018","unstructured":"Asha CS, Narasimhadhan AV (2018) Visual tracking using kernelized correlation filter with conditional switching to median flow tracker. IETE J Res 66(3):427\u2013438","journal-title":"IETE J Res"},{"key":"4542_CR82","doi-asserted-by":"crossref","unstructured":"Liu S, Liu D, Srivastava G, Po\u0142ap D, Wo\u017aniak M (2020) Overview and methods of correlation filter algorithms in object tracking. Complex & Intelligent Systems","DOI":"10.1007\/s40747-020-00161-4"},{"issue":"7","key":"4542_CR83","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1007\/s11263-017-1061-3","volume":"126","author":"A Luke\u017ei\u010d","year":"2018","unstructured":"Luke\u017ei\u010d A, Voj\u00ed\u0159 T, Zajc L\u010c, Matas J, Kristan M (2018) Discriminative correlation filter tracker with channel and spatial reliability. Int J Comput Vis 126 (7):671\u2013688","journal-title":"Int J Comput Vis"},{"key":"4542_CR84","unstructured":"ITU\u2013T (1996) Methods for subjective determination of transmissions quality. Recommendation P.800"},{"issue":"2","key":"4542_CR85","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/s00530-014-0446-1","volume":"22","author":"RC Streijl","year":"2016","unstructured":"Streijl RC, Winkler S, Hands DS (2016) Mean opinion score (MOS) revisited: methods and applications, limitations and alternatives. Multimed Syst 22(2):213\u2013227","journal-title":"Multimed Syst"},{"key":"4542_CR86","first-page":"7","volume":"12","author":"H Dadi","year":"2020","unstructured":"Dadi H (2020) Quantitative performance metrics for human tracking algorithms. Int J Anal Experi Modal Anal 12:7","journal-title":"Int J Anal Experi Modal Anal"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-04542-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-023-04542-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-04542-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T21:09:17Z","timestamp":1729544957000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-023-04542-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,6]]},"references-count":86,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["4542"],"URL":"https:\/\/doi.org\/10.1007\/s10489-023-04542-3","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,6]]},"assertion":[{"value":"23 February 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 June 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":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Ethics approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Consent to participate"}},{"value":"Participants were informed that the results of their opinions would be published in a way that their identity could not be revealed.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Consent for Publication"}},{"value":"The authors of this paper declare that they have no conflict of interest.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}