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Tap ch´ Tin hoc v` Diˆu khiˆn hoc, T.23, S.2 (2007), 141–152<br />
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CHUAN BI DU LIEU TRONG VIEC XAY DU NG<br />
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CO SO DU LIEU VIDEO SO<br />
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LU O NG XUAN CU O NG1 , DO TRUNG TUAN2 , DO XUAN TIEN1<br />
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Hoc viˆn K˜ thuˆt Quˆn su., Email: lxcuong2002@yahoo.com; dxtienvxl@yahoo.com<br />
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2 Dai hoc Quˆ c gia H` Nˆi, Email tuandt@hep.edu.vn<br />
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Abstract. Preparing video data is an important step in the construction of digital video databases.<br />
This work demands segmenting a video sequence into shots, which are basic meaning units of video<br />
data. In this paper, a method to prepare video data is proposed consisting of a shot boundary<br />
detection technique on the basis of tracking camera motion through the background areas to the<br />
video frame (background tracking) and of some other steps to discard noise and to reduce false<br />
segmentation for increasing the accuracy of the video stream segmentation. Measures to be taken to<br />
overcome the problem of object’s and camera’s motion are proposed and an enhanced algorithm for<br />
segmenting video data is also reported.<br />
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sˆ biˆn ph´p giam nhiˆu v` c´c ph´t hiˆn sai nh˘ m t˘ng kha n˘ng phˆn chia mˆt c´ch ch´ x´c<br />
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Trong mˆi tru.`.ng da phu.o.ng tiˆn, d˜. liˆu video l` mˆt dang d˜. liˆu d˘c biˆt v´.i nh˜.ng<br />
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LU O NG XUAN CU O NG, DO TRUNG TUAN, DO XUAN TIEN<br />
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1.1. Mˆ h` h´a d˜. liˆu<br />
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Phˆn doan d˜. liˆu video theo th`.i gian nh˘ m muc d´ phˆn chia d`ng video liˆn tuc<br />
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.i gian. Trong khi canh lai du.o.c hiˆ u l` mˆt do.n vi logic (vˆ m˘t ng˜. ngh˜ cua d`ng<br />
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2. PHU O NG PHAP PHAT HIEN CAT LIA<br />
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DU A TREN DANH DAU VUNG N` N<br />
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gian f (x, y, t). C´c chuyˆ n lia thˆ hiˆn d˜ c´ mˆt su. thay dˆ i n`o d´ cua khˆng gian v`/ho˘c<br />
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th`.i gian gi˜.a c´c lia ([4]). C´ hai loai chuyˆ n lia l` c´c c˘t lia (chuyˆ n lia dˆt ngˆt) v` c´c<br />
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chuyˆ n lia t`. t`..<br />
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C´c thuˆt to´n ph´t hiˆn c˘t lia dˆu c´ chung muc d´ l` ph´t hiˆn t´ khˆng liˆn tuc<br />
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.i gian trong nˆi dung h` anh cua mˆt chuˆi video. Trong d´ vˆ n dˆ then chˆt l` chon<br />
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d˘c t´ (c´c d˘c t´<br />
a ınh a a ınh) dˆ biˆ u diˆn nˆi dung h` anh. D˘c t´ du.o.c chon cˆn biˆ u thi<br />
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CHUAN BI DU LIEU TRONG VIEC XAY DU NG<br />
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c´c thuˆc t´ giˆng nhau nˆu c´c anh n˘ m trong c`ng mˆt lia, nhu.ng s˜ thay dˆ i r˜ rˆt nˆu<br />
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ch´ng n˘ m trong c´c lia kh´c nhau.<br />
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Hiˆn nay d˜ c´ mˆt sˆ thuˆt to´n ph´t hiˆn c˘t lia ([2, 7, 11]), nhu. c´c thuˆt to´n du.a<br />
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.a trˆn d˘c t´ canh; c´c thuˆt to´n du.a trˆn chuyˆ n dˆng cua dˆi tu.o.ng; c´c thuˆt<br />
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to´n du.a trˆn c´c tham sˆ cua video n´n; ngo`i ra, c`n c´ mˆt sˆ phu.o.ng ph´p nh˘ m v`o<br />
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c´c d˘c t´ h` anh m´.c cao cua video...<br />
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C´c t´c gia d˜ dˆ xuˆ t mˆt phu.o.ng ph´p ph´t<br />
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video, c`ng v´.i c´c k˜ thuˆt nh˘ m giam nhiˆu dˆ<br />
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t˘ng kha n˘ng ph´t hiˆn ch´ x´c gianh gi´.i c´c<br />
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lia. K˜ thuˆt PRL n`y du.a trˆn hai co. so. sau:<br />
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1. Lu.a chon c´c v`ng d˘c biˆt trˆn c´c khung anh<br />
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nh˘ m t˘ng hiˆu qua cho thuˆt to´n so s´nh gi˜.a<br />
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2. Vˆn dung k˜ thuˆt n´n anh theo phu.o.ng ph´p<br />
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Th´p Gauss (Gaussian Pyramid) [6, 8] dˆ ’<br />
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k´ thu.´.c anh phuc vu cho PRL.<br />
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Khi mˆt lia du.o.c thu.c hiˆn t`. mˆt hoat dˆng<br />
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camera, theo vˆt di chuyˆ n cua camera l` mˆt c´ch<br />
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dˆ x´c dinh gianh gi´.i gi˜.a c´c lia. C´ thˆ l`m<br />
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du.o.c viˆc n`y b˘ ng c´ch d´nh dˆ u v`ng nˆn trong c´c khung video. V`ng nˆn (VNC) du.o.c<br />
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dinh ngh˜ nhu. H` 1. L´ do chon VNC trong c´c khung video c´ dang ch˜. π : (i) tru.´.c hˆt<br />
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cˆn canh, hay v`ng dˆi tu.o.ng (VDT); (ii) v`ng nˆn ch˜. nhˆt nho trˆn dınh phan ´nh chuyˆ n<br />
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dˆng ngang cua camera; (iii) hai cˆt tr´i/ phai phan ´nh chuyˆ n dˆng doc cua camera. Kˆt<br />
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.p gi˜.a v`ng dınh v` c´c cˆt c´ thˆ vach ra chuyˆ n dˆng bˆ t k` theo hu.´.ng du.`.ng ch´o.<br />
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Du.a trˆn c´ch x´c dinh v`ng nˆn, ta c´ thˆ thu.c hiˆn k˜ thuˆt PRL thˆng qua viˆc x´c<br />
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dinh m´.c dˆ phˆn biˆt VNC cua hai khung liˆn kˆ. M˘c d` dˆ ph´.c tap cua thuˆt to´n c´<br />
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t˘ng, nhu.ng b` lai phu.o.ng ph´p n`y lai to ra hiˆu qua trˆn c´c phu.o.ng diˆn sau:<br />
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1. Sˆ lu.o.ng ph´p so s´nh giam do k´ thu.´.c v`ng cˆn so s´nh khˆng phai l` to`n bˆ khung.<br />
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2. Giam du.o.c ph´t hiˆn sai d´ng kˆ so v´.i mˆt sˆ phu.o.ng ph´p kh´c do c´c biˆn ph´p loc<br />
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Dˆ tiˆn so s´nh c´c v`ng nˆn, nˆn su. dung c´c h` chuyˆ n dang do k´o th˘ng VNC.<br />
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` n k´o th˘ng cua VNC du.o.c goi l` v`ng nˆn chuyˆ n dˆ i (k´ hiˆu l` VNCD); v` n´ l`<br />
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mˆt mang c´c pixel hai chiˆu, nhu. trong H` 2.<br />
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LU O NG XUAN CU O NG, DO TRUNG TUAN, DO XUAN TIEN<br />
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Dˆ so s´nh nˆi dung hai v`ng nˆn, trong mˆt sˆ tru.`.ng ho.p cˆn du.a v`o viˆc so s´nh<br />
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.o.ng ph´p Th´p Gauss, quen thuˆc trong k˜<br />
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’n mˆt VNCD hai chiˆu th`nh mˆt d˜y c´c pixel (k´ hiˆu<br />
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l` dayPixel) v` cuˆi c`ng s˜ chuyˆ n th`nh mˆt pixel do.n (k´ hiˆu l` dPixel). Theo h` 2,<br />
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v`ng rˆng L*w s˜ du.o.c chia th`nh c´c cu.a sˆ ; qua mˆt sˆ lˆn ´p dung phu.o.ng ph´p n`y,<br />
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t´ du.o.c d˜y c´c pixel d˘c tru.ng cho trung b` m`u, dˆ t´ dPixel.<br />
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2.2. Thuˆt to´n<br />
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Thuˆt to´n su. dung dayPixel v` dPixel dˆ PRL thˆ hiˆn trˆn h` 3. Hai giai doan dˆu<br />
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.`.ng du.o.c su. dung dˆ kiˆ m tra nhanh cho nh˜.ng tru.`.ng ho.p r˜ r`ng. Chı khi n`o khˆng<br />
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ph´t hiˆn du.o.c m´.i su. dung dˆn giai doan 3. Thuˆt to´n du.o.c mˆ ta chi tiˆt nhu. sau:<br />
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Giai doan 1. So s´nh pixel: Mˆt pixel trong mˆi VNC du.o.c so v´.i pixel o. c`ng vi tr´ v` mˆt<br />
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sˆ pixel lˆn cˆn (Vungp) trong VNC cua khung liˆn kˆ n´. Nˆu tˆ ng sˆ pixel trong hai VNC<br />
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kh´c nhau Khacp nho ho.n mˆt gi´ tri ngu.˜.ng (Khacp < N guongp), hai khung tu.o.ng u.ng<br />
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v´.i hai VNC coi nhu. c`ng mˆt lia v` x´t t´.i khung tiˆp theo. Ngu.o.c lai, sang giai doan 2.<br />
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H` 3. Mˆ ta thuˆt to´n<br />
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2. Giai doan 2. So s´nh c´c trung b` m`u dPixel: Nˆu su. kh´c nhau cua dPixel cua hai<br />
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khung (goi l` Khacd) chu.a vu.o.t qu´ ngu.˜.ng (Khacd < N guongd), hai khung coi nhu. c`ng<br />
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.i khung tiˆp theo. Ngu.o.c lai, sang giai doan sau.<br />
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mˆt lia v` s˜ x´t t´<br />
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.˜.ng N guongp v` N guongd du.o.c chon theo kinh nghiˆm; t`y theo nˆi dung video.<br />
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Ch˘ng han khi xu. l´ d˜. liˆu vˆ thˆng tin quang c´o, N guongp = 0, 15, N guongd = 0, 20.<br />
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Giai doan 3. So s´nh dayP ixel : T´ to´n xem hai khung chia se bao nhiˆu phˆn nˆn chung.<br />
.<br />
.o.c so s´nh b˘ ng c´ch dich ch´ng di theo chiˆu ngu.o.c lai nhu. trˆn h` 4. Mˆi<br />
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Hai dayP ixel du .<br />
.<br />
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.´.c dich l` mˆt pixel v` s˜ t´ du.o.c sˆ diˆ m kh´.p nhau p tu.o.ng u.ng (sˆ c´c gi´ tri kh´.p<br />
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nhau liˆn tiˆp p cua dayP ixel cua khung i (dayP ixel i) v` cua khung i − 1 (dayP ixeli-1)).<br />
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