{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/comparative-study-of-motion-detection-methods","title":"Comparative study of motion detection methods for video surveillance systems","arxiv_id":"1804.05459","date":"2018-04-16","proceeding":null,"authors":["Kamal Sehairi","Chouireb Fatima","Jean Meunier"],"abstract":"The objective of this study is to compare several change detection methods\nfor a mono static camera and identify the best method for different complex\nenvironments and backgrounds in indoor and outdoor scenes. To this end, we used\nthe CDnet video dataset as a benchmark that consists of many challenging\nproblems, ranging from basic simple scenes to complex scenes affected by bad\nweather and dynamic backgrounds. Twelve change detection methods, ranging from\nsimple temporal differencing to more sophisticated methods, were tested and\nseveral performance metrics were used to precisely evaluate the results.\nBecause most of the considered methods have not previously been evaluated on\nthis recent large scale dataset, this work compares these methods to fill a\nlack in the literature, and thus this evaluation joins as complementary\ncompared with the previous comparative evaluations. Our experimental results\nshow that there is no perfect method for all challenging cases, each method\nperforms well in certain cases and fails in others. However, this study enables\nthe user to identify the most suitable method for his or her needs.","url_abs":"http://arxiv.org/abs/1804.05459v1","url_pdf":"http://arxiv.org/pdf/1804.05459v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"comparative-study-of-motion-detection-methods","repo_url":"https://github.com/SEHAIRIKamal/A-Matlab-Background-Subtraction-Library","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"change-detection","task_name":"Change Detection"},{"task_slug":"motion-detection","task_name":"Motion Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}