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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
¿µ»óÀÇ ±íÀÌÁ¤º¸ ÃßÃâÀ» À§ÇÑ weighted cost aggregation ±â¹ÝÀÇ ½ºÅ×·¹¿À Á¤ÇÕ ±â¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Weighted cost aggregation approach for depth extraction of stereo images |
ÀúÀÚ(Author) |
À±ÈñÁÖ
Â÷ÀÇ¿µ
Hee-Joo Yoon
Eui-Young Cha
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¿ø¹®¼ö·Ïó(Citation) |
VOL 13 NO. 01 PP. 0396 ~ 0399 (2009. 05) |
Çѱ۳»¿ë (Korean Abstract) |
½ºÅ×·¹¿À ºñÀü ½Ã½ºÅÛ(stereo vision system)Àº 2Â÷¿ø ¿µ»óÁ¤º¸¸¦ ÀÌ¿ëÇÏ¿© 3Â÷¿ø ±íÀÌ Á¤º¸¸¦ ȹµæÇÏ´Â µ¥ À¯¿ëÇÑ ¹æ¹ýÀ¸·Î, ±×µ¿¾È ¸¹Àº ¿¬±¸°¡ ÁøÇàµÇ¾ú´Ù. 3Â÷¿ø ±íÀÌ Á¤º¸¸¦ ȹµæÇϱâ À§Çؼ´Â ¿µ»óÀÇ ´ëÀÀÁ¡À» ã¾Æ¾ß Çϴµ¥, ¼Óµµ¿Í Á¤È®¼ºÀ» µ¿½Ã¿¡ ¸¸Á·½ÃÅ°±â°¡ ¾î·Æ´Ù. ÀÌ·¯ÇÑ ¹®Á¦¸¦ ÇØ°áÇϱâ À§ÇØ, º» ³í¹®¿¡¼´Â ÀûÀÀÀû °¡ÁßÄ¡(weight)¸¦ Àû¿ëÇÑ cost aggregation ±â¹ÝÀÇ ½ºÅ×·¹¿À Á¤ÇÕ ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. ÀÌ ¹æ¹ýÀº ½ºÅ×·¹¿À ¿µ»óÀÇ Æ¯Â¡À» ÀÌ¿ëÇÏ¿© °¡ÁßÄ¡¸¦ ȹµæÇÏ°í, »ö»óÁ¤º¸, ¹à±âÁ¤º¸, °Å¸®Á¤º¸¿¡ °¡ÁßÄ¡¸¦ Àû¿ëÇÑ ÈÄ, À̸¦ ÀÌ¿ëÇÏ¿© ´ëÀÀÁ¡À» ã¾Æ ±íÀÌ Á¤º¸¸¦ ÃßÃâÇÑ´Ù. Á¦¾ÈµÈ ¹æ¹ýÀÇ ¼º´ÉÀ» Æò°¡Çϱâ À§ÇÏ¿© ground truth°¡ Á¸ÀçÇÏ´Â ´Ù¾çÇÑ ½ºÅ×·¹¿À ¿µ»óÀ» ÀÌ¿ëÇÏ¿© ½ÇÇèÇÏ¿´À¸¸ç, ½ÇÇè °á°ú ´Ù¾çÇÑ ¿µ»ó¿¡¼µµ Çâ»óµÈ °á°ú¸¦ º¸¿´´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color, brightness and distance information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.
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Å°¿öµå(Keyword) |
Disparity map
depth extraction
stereo matching
weighted matching
cost aggregation
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