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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ³í¹®Áö B : ¼ÒÇÁÆ®¿þ¾î ¹× ÀÀ¿ë

Á¤º¸°úÇÐȸ ³í¹®Áö B : ¼ÒÇÁÆ®¿þ¾î ¹× ÀÀ¿ë

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) °¨½Ã ½Ã½ºÅÛ¿¡¼­ÀÇ ºñÁ¤»ó ¼Ò¸® ŽÁö ¹× ½Äº°
¿µ¹®Á¦¸ñ(English Title) Abnormal Sound Detection and Identification in Surveillance System
ÀúÀÚ(Author) ¿À½Â±Ù   ÀÌÁ¾¿í   ÀÌÇѼº   Á¤¿ëÈ­   ¹Ú´ëÈñ   Seunggeun Oh   Jonguk Lee   Hansung Lee   Yongwha Chung   Daihee Park  
¿ø¹®¼ö·Ïó(Citation) VOL 39 NO. 02 PP. 0144 ~ 0152 (2012. 02)
Çѱ۳»¿ë
(Korean Abstract)
º» ³í¹®¿¡¼­´Â CCTV µî°ú °°Àº °¨½Ã Ä«¸Þ¶ó ȯ°æ¿¡¼­ ½Ç½Ã°£À¸·Î À¯ÀԵǴ ¼Ò¸® Á¤º¸¸¦ ÀÌ¿ëÇÏ¿©, ºñÁ¤»ó »óȲÀ» ŽÁö ¹× ½Äº°ÇÏ´Â ÇÁ·ÎÅäŸÀÔ ½Ã½ºÅÛÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈµÈ ½Ã½ºÅÛÀÇ Ã¹ ¹ø° °èÃþ¿¡¼­´Â ´ÜÀÏ Å¬·¡½º SVMÀÎ SVDD·Î ºñÁ¤»ó ¼Ò¸®¸¦ ½Å¼ÓÇÏ°Ô Å½ÁöÇÏ¿© °ü¸®ÀÚ¿¡°Ô ¾Ë¶÷ °æ°íÇÏ°í, µÎ ¹ø° °èÃþÀÇ SRC´Â ŽÁöµÈ ºñÁ¤»ó ¼Ò¸®¸¦ ¡®gun', 'scream', 'siren', 'crash', 'bomb' µîÀ¸·Î ¼¼ºÐÈ­ ½Äº°ÇÏ¿© °ü¸®ÀÚ¿¡°Ô º¸°íÇÔÀ¸·Î½á °ü¸®ÀÚÀÇ À§±â »óȲ ´ëó ´É·ÂÀ» µ½´Â´Ù. º» ³í¹®¿¡¼­ Á¦¾ÈÇÏ´Â SVDD¿Í SRC¸¦ È¥ÇÕÇÑ °èÃþÀû ±¸Á¶´Â ´ÙÀ½°ú °°Àº Ư¼ºÀ» °®´Â´Ù. ù°, Á¤»ó ¼Ò¸® µ¥ÀÌÅ͸¸À¸·Î ÇнÀÇÑ SVDD¸¦ ÀÌ¿ëÇÏ¿© ºñÁ¤»ó ¼Ò¸®¸¦ ºü¸£°Ô ŽÁöÇÔÀ¸·Î½á, Á¤»ó ¼Ò¸®¿¡ ´ëÇÑ ºÒÇÊ¿äÇÑ ºñÁ¤»ó ¼Ò¸® ½Äº° ¿¬»êÀ» ¼öÇàÇÏÁö ¾Ê´Â´Ù. µÑ°, ÃÖ±Ù ¾ó±¼ ÀÎ½Ä ºÐ¾ß¿¡¼­ ¼º°øÀûÀÎ ¾÷ÀûÀ» º¸¿©ÁÖ°í ÀÖ´Â °­ÀÎÇÑ SRC¸¦ ÀÌ¿ëÇÏ¿© ºñÁ¤»ó ¼Ò¸®¸¦ ½Äº°ÇÔÀ¸·Î½á, ¾ÈÁ¤ÀûÀÎ º¸¾È °¨½Ã ½Ã½ºÅÛ ¿î¿ëÀ» º¸ÀåÇÑ´Ù. ¼Â°, SRC °íÀ¯ÀÇ Æ¯¼º»ó »õ·Î¿î ºñÁ¤»ó ¼Ò¸®°¡ Ãß°¡µÇ´õ¶óµµ Àüü ½Ã½ºÅÛÀ» ÀçÇнÀ½Ãų ÇÊ¿ä°¡ ¾ø´Â ½Ã½ºÅÛÀÇ Á¡ÁõÀû °»½ÅÀÌ °¡´ÉÇÏ´Ù. Á¤¼ºÀû ºÐ¼®À» Æ÷ÇÔÇÑ ½ÇÇè °á°ú·Î Á¦¾ÈµÈ ½Ã½ºÅÛÀÇ È¿´ÉÀ» ¹àÈù´Ù.
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(English Abstract)
In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as "gun", "scream", "siren", "crash", "bomb" via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.
Å°¿öµå(Keyword) ºñÁ¤»ó ¼Ò¸® ŽÁö ¹× ½Äº°   ¼­º£ÀÏ·±½º ½Ã½ºÅÛ   SVDD   SRC   Abnormal audio detection and identification   Surveillance system  
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