{"department":[{"_id":"ChLa"}],"date_updated":"2022-05-24T08:05:40Z","doi":"10.1007/s11554-010-0168-3","day":"01","quality_controlled":"1","citation":{"ama":"Lampert C, Peters J. Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. Journal of Real-Time Image Processing. 2012;7(1):31-41. doi:10.1007/s11554-010-0168-3","ieee":"C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1. Springer, pp. 31–41, 2012.","apa":"Lampert, C., & Peters, J. (2012). Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. Journal of Real-Time Image Processing. Springer. https://doi.org/10.1007/s11554-010-0168-3","short":"C. Lampert, J. Peters, Journal of Real-Time Image Processing 7 (2012) 31–41.","mla":"Lampert, Christoph, and Jan Peters. “Real-Time Detection of Colored Objects in Multiple Camera Streams with off-the-Shelf Hardware Components.” Journal of Real-Time Image Processing, vol. 7, no. 1, Springer, 2012, pp. 31–41, doi:10.1007/s11554-010-0168-3.","ista":"Lampert C, Peters J. 2012. Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. Journal of Real-Time Image Processing. 7(1), 31–41.","chicago":"Lampert, Christoph, and Jan Peters. “Real-Time Detection of Colored Objects in Multiple Camera Streams with off-the-Shelf Hardware Components.” Journal of Real-Time Image Processing. Springer, 2012. https://doi.org/10.1007/s11554-010-0168-3."},"oa":1,"ddc":["000"],"volume":7,"scopus_import":"1","_id":"3248","year":"2012","publist_id":"3417","publication_identifier":{"issn":["1861-8200"],"eissn":["1861-8219"]},"article_type":"original","has_accepted_license":"1","file":[{"creator":"kschuh","date_updated":"2020-07-14T12:46:04Z","access_level":"open_access","file_size":2933187,"content_type":"application/pdf","file_name":"2012_Springer_Lampert.pdf","checksum":"241be47ea50e81a283bcf4c45b07e8cc","relation":"main_file","file_id":"5958","date_created":"2019-02-12T10:52:25Z"}],"author":[{"first_name":"Christoph","full_name":"Lampert, Christoph","last_name":"Lampert","orcid":"0000-0001-8622-7887","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Peters","full_name":"Peters, Jan","first_name":"Jan"}],"title":"Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components","issue":"1","month":"03","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Journal of Real-Time Image Processing","language":[{"iso":"eng"}],"date_created":"2018-12-11T12:02:15Z","oa_version":"Submitted Version","page":"31 - 41","publication_status":"published","publisher":"Springer","date_published":"2012-03-01T00:00:00Z","type":"journal_article","intvolume":" 7","abstract":[{"text":"We describe RTblob, a high speed vision system that detects objects in cluttered scenes based on their color and shape at a speed of over 800 frames/s. Because the system is available as open-source software and relies only on off-the-shelf PC hardware components, it can provide the basis for multiple application scenarios. As an illustrative example, we show how RTblob can be used in a robotic table tennis scenario to estimate ball trajectories through 3D space simultaneously from four cameras images at a speed of 200 Hz.","lang":"eng"}],"article_processing_charge":"No","file_date_updated":"2020-07-14T12:46:04Z","status":"public"}