{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T10:06:24Z","timestamp":1774605984911,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T00:00:00Z","timestamp":1574380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Most existing abandoned object detection algorithms use foreground information generated from background models. Detection using the background subtraction technique performs well under normal circumstances. However, it has a significant problem where the foreground information is gradually absorbed into the background as time passes and disappears, making it very vulnerable to sudden illumination changes that increase the false alarm rate. This paper presents an algorithm for detecting abandoned objects using a dual background model, which is robust even in illumination changes as well as other complex circumstances like occlusion, long-term abandonment, and owner re-attendance. The proposed algorithm can adapt quickly to various illumination changes. And also, it can precisely track the target objects to determine whether it is abandoned regardless of the existence of foreground information and the effect from the illumination changes, thanks to the largest-contour-based presence authentication mechanism proposed in this paper. For performance evaluation, we trialed the algorithm with the PETS2006, ABODA datasets as well as our dataset, especially to demonstrate its robustness in various illumination changes.<\/jats:p>","DOI":"10.3390\/s19235114","type":"journal-article","created":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T09:02:52Z","timestamp":1574413372000},"page":"5114","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Robust Detection of Abandoned Object for Smart Video Surveillance in Illumination Changes"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3564-2479","authenticated-orcid":false,"given":"Hyeseung","family":"Park","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeol-ro, Byeongcheon-myeon, Dongnam-gu, Cheonan-si, Chungcheongnam-do, Korea"}]},{"given":"Seungchul","family":"Park","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeol-ro, Byeongcheon-myeon, Dongnam-gu, Cheonan-si, Chungcheongnam-do, Korea"}]},{"given":"Youngbok","family":"Joo","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeol-ro, Byeongcheon-myeon, Dongnam-gu, Cheonan-si, Chungcheongnam-do, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Luna, E., Carlos, J., Miguel, S., Ortego, D., and Mart\u00ednez, J. (2018). Abandoned Object Detection in Video-Surveillance: Survey and Comparison. Sensors, 18.","DOI":"10.3390\/s18124290"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wahyono, and Jo, K.H (2017). Cumulative Dual Foreground Differences for Illegally Parked Vehicles Detection. IEEE Trans. Ind. Inform., 99, 1\u20139.","DOI":"10.1109\/TII.2017.2665584"},{"key":"ref_3","unstructured":"Bird, N., Atev, S., Caramelli, N., Martin, R., Masoud, O., and Papanikolopoulos, N. (2006, January 15\u201319). Real Time, Online Detection of Abandoned Objects in Public Areas. Proceedings of the 2006 IEEE International Conference on Robotics and Automation (ICRA 2006), Orlando, FL, USA."},{"key":"ref_4","first-page":"15595","article-title":"Survey on Abandoned Object Detection in Surveillance Video","volume":"7","author":"Mahale","year":"2017","journal-title":"Int. J. Eng. Sci. Comput."},{"key":"ref_5","unstructured":"(2018, December 01). PETS2006 Benchmark Data. Available online: http:\/\/www.cvg.reading.ac.uk\/PETS2006\/data.html."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1109\/TIFS.2015.2408263","article-title":"Abandoned Object Detection via Temporal Consistency Modeling and Back-Tracing Verification for Visual Surveillance","volume":"10","author":"Lin","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_7","unstructured":"Fan, Q., and Pankanti, S. (September, January 30). Modeling of temporarily y static objects for robust abandoned object detection in urban surveillance. Proceedings of the 8th IEEE International Conference AVSS, Klagenfurt, Austria."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1109\/TSMCC.2010.2065803","article-title":"Robust detection of abandoned and removed objects in complex surveillance videos","volume":"41","author":"Tian","year":"2011","journal-title":"IEEE Trans. Syst. Man Cybern. C"},{"key":"ref_9","unstructured":"Tian, Y., Feris, R., and Hampapur, A. (2008, January 17). Real-time Detection of Abandoned and Removed Objects in Complex Environments. Proceedings of the Eighth International Workshop on Visual Surveillance (VS2008), Marseille, France."},{"key":"ref_10","first-page":"30","article-title":"Robust abandoned object detection using dual foregrounds","volume":"2008","author":"Porikli","year":"2008","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Evangelio, R.H., Senst, T., and Sikora, T. (2011, January 5\u20137). Detection of static objects for the task of video surveillance. Proceedings of the IEEE WACV, Kona, HI, USA.","DOI":"10.1109\/WACV.2011.5711550"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lin, K., Chen, S.C., Chen, C.S., Lin, D.T., and Hung, Y.P. (2014, January 24\u201328). Left-Luggage Detection from Finite-State-Machine Analysis in Static-Camera Videos. Proceedings of the 22nd International Conference on Pattern Recognition, Stockholm, Sweden.","DOI":"10.1109\/ICPR.2014.787"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2247","DOI":"10.1109\/TII.2016.2605582","article-title":"Unattended object identification for intelligent surveillance system using sequence of dual background difference","volume":"12","author":"Wahyono","year":"2016","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_14","unstructured":"Filonenko, A., and Jo, K.H. (2015, January 25\u201327). Detecting abandoned objects in crowded scenes of surveillance videos using adaptive dual background model. Proceedings of the International Conference Human System Interactions, Warsaw, Poland."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Shyam, D., Kot, A., and Athalye, C. (2018, January 23\u201327). Abandoned Object Detection Using Pixel-Based Finite State Machine and Single Shot Multibox Detector. Proceedings of the IEEE International Conference on Multimedia and Expo, San Diego, CA, USA.","DOI":"10.1109\/ICME.2018.8486464"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xu, H., and Yu, F. (2013, January 26\u201328). Improved compressive tracking in surveillance scenes. Proceedings of the 7th International Conference on Image and Graphics (ICIG 2013), Qingdao, China.","DOI":"10.1109\/ICIG.2013.176"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1109\/TIP.2010.2101613","article-title":"ViBe: A universal background subtraction algorithm for video sequences","volume":"20","author":"Barnich","year":"2011","journal-title":"IEEE Trans. Image Process."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liao, S., Zhao, G., Kellokumpu, V., Pietikinen, M., and Li, S.Z. (2010, January 13\u201318). Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5539817"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1109\/TIP.2016.2642779","article-title":"Detection of stationary foreground objects using multiple nonparametric background-foreground models on a finite state machine","volume":"26","author":"Cuevas","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Smeureanu, S., and Ionescu, R.T. (2018, January 3\u20137). Real-time deep learning method for abandoned luggage detection in video. Proceedings of the 26th European Signal Processing Conference, Rome, Italy.","DOI":"10.23919\/EUSIPCO.2018.8553156"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Sidyakin, S.V., and Vishnyakov, B.V. (2017, January 26). Real-time detection of abandoned bags using CNN. Proceedings of the SPIE Optical Metrology, Munich, Germany.","DOI":"10.1117\/12.2270078"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/0004-3702(81)90024-2","article-title":"Determining optical flow","volume":"17","author":"Horn","year":"1981","journal-title":"Artif. Intell."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/TAES.1979.308710","article-title":"A Kalman Filter Based Tracking Scheme with Input Estimation","volume":"AES-15","author":"Chan","year":"1979","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_24","unstructured":"(2019, October 29). OpenCV. Available online: https:\/\/docs.opencv.org."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/0734-189X(85)90016-7","article-title":"Topological structural analysis of digitized binary images by border following","volume":"30","author":"Suzuki","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1016\/j.patrec.2005.11.005","article-title":"Efficient adaptive density estimation per image pixel for the task of background subtraction","volume":"27","author":"Zivkovic","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_27","unstructured":"Dalal, N., and Triggs, B. (, January Jun). Histograms of oriented gradients for human detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u201805), San Diego, CA, USA."},{"key":"ref_28","unstructured":"(2019, October 29). ABODA Dataset. Available online: https:\/\/github.com\/kevinlin311tw\/ABODA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.cviu.2017.01.008","article-title":"An edge-based method for effective abandoned luggage detection in complex surveillance videos","volume":"158","author":"Ilias","year":"2017","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Krusch, P., Bochinski, E., Eiselein, V., and Sikora, T. (2017, January 17\u201320). A consistent two-level metric for evaluation of automated abandoned object detection methods. Proceedings of the IEEE International Conference on Image Processing (ICIP), Beijing, China.","DOI":"10.1109\/ICIP.2017.8297104"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"19","DOI":"10.5194\/isprs-annals-IV-1-W1-19-2017","article-title":"Security Event Recognition for Visual Surveillance","volume":"4","author":"Liao","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5114\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:36:42Z","timestamp":1760189802000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5114"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,22]]},"references-count":31,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235114"],"URL":"https:\/\/doi.org\/10.3390\/s19235114","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,22]]}}}