{"id":152061,"date":"2005-11-01T00:00:00","date_gmt":"2005-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/accurate-repeat-finding-and-object-skipping-using-fingerprints\/"},"modified":"2018-10-16T20:01:54","modified_gmt":"2018-10-17T03:01:54","slug":"accurate-repeat-finding-and-object-skipping-using-fingerprints","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/accurate-repeat-finding-and-object-skipping-using-fingerprints\/","title":{"rendered":"Accurate Repeat Finding and Object Skipping Using Fingerprints"},"content":{"rendered":"<div data-canvas-width=\"351.8234171496\">This paper introduces a novel and very accurate segmentation algorithm. It is very efficient and consumes less than 10% of CPU on a simple desktop PC to segment a stream in real-time. It operates on an audio stream, or on the audio portion of a audio-visual stream. It is very accurate: it accurately detects the positions and durations of objects on an over-the-air broadcast television signal, and songs on both FM and internet radio stations (as checked against labeled ground truth streams). The algorithm does not require any prior information or training. We detail the system design and present results of segmenting broadcast stream.<\/div>\n","protected":false},"excerpt":{"rendered":"<p>This paper introduces a novel and very accurate segmentation algorithm. It is very efficient and consumes less than 10% of CPU on a simple desktop PC to segment a stream in real-time. It operates on an audio stream, or on the audio portion of a audio-visual stream. It is very accurate: it accurately detects the [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"user_nicename","value":"cormac"}],"msr_publishername":"Association for Computing Machinery, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2004 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and\/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. The definitive version of this paper can be found at ACM's Digital Library 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