Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
´Ù¼öÀÇ º¸ÇàÀÚ ÃßÀû°úÁ¤¿¡¼ Ư¡Á¤º¸¸¦ ÀÌ¿ëÇÑ º¸ÇàÀÚ °ËÃâ ¾Ë°í¸®Áò ¼³°è |
¿µ¹®Á¦¸ñ(English Title) |
Design of Pedestrian Detection Algorithm Using Feature Data in Multiple Pedestrian Tracking Process |
ÀúÀÚ(Author) |
ÇѸíÈ£
·ùâÁÖ
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ÇѽÂÁ¶
Myung-ho Han
Chang-ju Ryu
Sang-duck Lee
Seung-jo Han
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¿ø¹®¼ö·Ïó(Citation) |
VOL 22 NO. 04 PP. 0641 ~ 0647 (2018. 04) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù ¿©·¯ ¸ñÀûÀ¸·Î ¿µ»ó Á¤º¸¸¦ Á¦°øÇÏ´Â CCTV´Â Áö´ÉÇüÀ¸·Î º¯ÈÇÏ°í ÀÖÀ¸¸ç, ÄÄÇ»ÅÍ ºñÀüÀ» ÀÌ¿ëÇÑ ÀÚµ¿È ÀÀ¿ë ¹üÀ§°¡ Áõ°¡ÇÏ°í ÀÖ´Ù. º¸ÇàÀÚ ¹× Â÷·® µîÀÇ Á¤È®ÇÑ ÀνÄÀ» À§ÇØ ½Å·Ú¼ºÀÌ ³ôÀº °ËÃâ¹æ¹ýÀ» ¼öÇàÇÏ¿©¾ß Çϸç À̸¦ À§ÇØ ´Ù¾çÇÑ ¹æ¹ýµéÀÌ ¿¬±¸µÇ°í ÀÖ´Ù. º» ³í¹®¿¡¼´Â ´Ù¼öÀÇ º¸ÇàÀÚ°¡ ¿òÁ÷ÀÌ´Â »óȲ¿¡¼ º¸ÇàÀÚÀÇ ¼¼ °¡Áö Ư¡Á¤º¸¸¦ ȹµæÇÏ¿© ´Ù¼öÀÇ º¸ÇàÀÚµéÀ» °ËÃâÇÏ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ¹ýÀº º¸ÇàÀÚ °ËÃâ ¹× ÃßÀû¿¡ ½ÇÆÐÇϰųª È¥µ¿µÇ´Â »óȲÀ» ÃÖ¼ÒÈ ÇÏ¸é¼ °¢°¢ÀÇ º¸ÇàÀÚ¸¦ ±¸º°ÇÑ´Ù. º¸ÇàÀڵ鳢¸® ±ÙÁ¢Çϰųª °ãÄ¡´Â °æ¿ì ¹Ì¸® ÀúÀåµÈ ÇÁ·¹ÀÓ Æ¯Â¡ Á¤º¸¸¦ ÀÌ¿ëÇÏ¿© º¸ÇàÀÚ¸¦ ±¸º° ¹× °ËÃâÇÑ´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.
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Å°¿öµå(Keyword) |
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pedestrian
tracking
feature data
detection
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