Trich chon c trng t video phc v nhn dng ch nm
Trich chon c trng t video phc v nhn dng ch nmSinh vin: Nguyn Vn
TonTng quanYu cu bi ton.Hng gii quyt.Tch cc frame.To nh panorama.Yu
cu bi tonTch c cc frame.Phc v vic nhn dng.Hng gii quytTh nht: Trch
chn cc frame c trng.Th hai: to nh panorama t cc frame.Tch cc
frameXc nh v tr ca frame.Lu frame li di dng bitmap.panoramaChiu ln
v Ha trn nhTm kim c trngTnh ton Homography bng RANSACTm kim c
trngCc im c trng gi l Interest point.Harris corner detectSIFTSURFTm
kim gc Harris
C s thay i theo mt hngC s thay i theo mi hngTm kim gc Harris
S(x, y) l tng bnh phng lchw(u, v) l ca s khung hnh ti v tr (u,
v)I(u, v) v I(u+x, v+y) l cng sng ca pixel ti cc v tr (u, v) v
(u+x, v+y)Tm kim gc Harris
I(u+x, v+y) c th khai trin Taylor nh sau:Ix, Iy l cc o hm ca I
theo cc thnh phn x, y
Tm kim gc Harris
A l mt cu trc TensorTm kim gc Harris
1 v 2 l cc gi tr ring ca Ak l mt ngng cho trc
(HarrisThreshold)SIFTXy dng khng gian Scale.Xc nh v tr im c
trng.Thm hng cho im c trng.M t im c trng.SURFGm hai phn chnh l:Pht
hin im c trng.M t im c trng.SURFvi mi im X(x, y) ca nh I, ma trn
Hessian ca X trong khng gian scale l:
SURFHm Gaussian l ti u trong phn tch khng gian scale.Xp x cho o
hm bc hai ca hm Gaussian.
SURF
Dxx, Dyy, Dxy ln lt l cc xp x theo x, y, v xy ca o hm bc hai hm
Gaussian.
SURF|x|F l tiu chun Frobenius ca ma trn xSURFHomographynh trong
khng gian 3 chiu => nh 2 chiu.m bo v t l ca vt.Khng m bo gc v
kch thc vt th.X ~ HXX: l nh trong khng gian camera.X: l nh trong
khng gian thc.H: l ma trn Homography.Homography
X = HX
Vi x2 = x2/z2 v y2 = y2/z2, ta c:Tng ng vi cng
thc:Homography
Vi z = 1Homography
Vi:HomographyRANSACRANdom SAmple Consensusc cng b bi Fischler v
Bolles nm 1981.Gii thut kh nhiu.RANSAC tng c bn:D liu gm inlier, v
outlier va mt ngng.Chn n im ngu nhin xy dng m hnh.T n im suy ra cc
m hnh c th.Tin hnh b phiu.Tin hnh kim phiu.RANSAC
RANSAC
RANSACInput:data: mt tp d liu ban u.model:mt m hnh ph hp vi
data.n:s lng d liu nh nht thit lp nn m hnh.k:s ln lp li ca thut
ton.t:mt gi tr ngng xc nh mc tnh ton cho m hnhd:D liu kim
chngRANSACOutput:best_model:cc tham s m hnh to nn m hnh ph hp nht
vi databest_consensus_set:Tp cc im khp vi best_modelbest_error:Tp
cc im outlierRANSACiterations := 0best_model :=
nilbest_consensus_set := nilbest_error := infinitywhile(iterations
< k){maybe_inliers := n chn ngu nhin n im t data ban
u.maybe_model l m hnh c tnh ton t tp maybe_inliers
chn.consensus_set := maybe_inliers
for(d){nu im c gi tr nh hn ngng t th thm im vo tp
consensus_set}
Nu s lng phn t ca consensus_set > d (c ngha l y l m hnh
tt)Thc hin vic test model.This_model := l m hnh ph hp vi tt c cc im
trong consensus_set.This_error := If(This_error < best_error){Ta
tm c m hnh tt nht k t khi lp. Gi cho n khi tm c m hnh tt
hn.best_model := this_modelbest_consensus_set :=
consensus_setbest_error := this_error}Interations++;}return
best_model, best_consensus_set, best_errorRANSAC
