Direct Linear Transformation & Computer Vision Models
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1 Diet inea ansfomation & Comute Vision Models Chate -A4 CE : Digital Photogammeti Sstems Aman F. Habib
2 Photogammet Vs. Comute Vision Conventional Photogammet is foug on eise geometi infomation etation fom image. oogahi maing fom sae bone and aibone image Metologial infomation etation though lose-ange hotogammet teestial hotogammet bjet-to-amea distane is less than mete Comute Vision CV is mainl onened with automated image undestanding: bjet eognition, Navigation and obstale avoidane, and bjet modeling CE : Digital Photogammeti Sstems Aman F. Habib
3 Aibone Photogammeti Maing CE : Digital Photogammeti Sstems Aman F. Habib
4 Aibone Photogammeti Maing CE : Digital Photogammeti Sstems 4 Aman F. Habib
5 Close-Range Photogammeti Maing CE : Digital Photogammeti Sstems Aman F. Habib
6 CV: bjet Reognition CE : Digital Photogammeti Sstems Aman F. Habib
7 CV: Navigation & bstale Avoidane CE : Digital Photogammeti Sstems Aman F. Habib
8 Photogammet Vs. Comute Vision Photogammet is alwas onened with eise geometi infomation etation. Photogammeti maing onsides otential deviations fom the assumed esetive ojetion. Fo Comute Vision CV: Fous is alwas on automation. bjet eognition and navigation aliations do not equie eise deivation of geometi infomation. Deending on the aliation, objet modeling might equie eise geometi infomation etation. CV usuall assumes that the ollineait of the objet oint, esetive ente, and oesonding image oint is maintained, even fo un-alibated ameas. CE : Digital Photogammeti Sstems 8 Aman F. Habib
9 bjet-to-image Coodinate ansfomation in Photogammet Collineait Equations CE : Digital Photogammeti Sstems Aman F. Habib
10 Collineait Equations a oa = oa o hese vetos should be defined w..t. the same oodinate sstem. A CE : Digital Photogammeti Sstems Aman F. Habib
11 Collineait Equations Pesetive Cente G R,, z G i + a + a, a A A A A G G CE : Digital Photogammeti Sstems Aman F. Habib
12 CE : Digital Photogammeti Sstems Aman F. Habib Collineait Equations he veto onneting the esetive ente to the image oint w..t. the image oodinate sstem o a dist dist dist dist v a a a a oa i
13 CE : Digital Photogammeti Sstems Aman F. Habib Collineait Equations he veto onneting the esetive ente to the objet oint w..t. the gound oodinate sstem o A o A o A o A o o o A A A m oa o V
14 Collineait Equations oa oa v M,, V R m i oa m oa a dist m m m A o dist m m m a A o m m m A o Whee: is a sale fato +ve. CE : Digital Photogammeti Sstems 4 Aman F. Habib
15 CE : Digital Photogammeti Sstems Aman F. Habib Collineait Equations M R m o A o A o A o A o A o A a o A o A o A o A o A o A a dist m m m m m m dist m m m m m m m R R o A o A o A o A o A o A a o A o A o A o A o A o A a dist dist
16 bjet-to-image Coodinate ansfomation Diet inea ansfomation Comute Vision Model CE : Digital Photogammeti Sstems Aman F. Habib
17 D & Comute Vision Models he D and omute vision models enomass: Collineait Equations, Non-othogonalit between the aes of the image/amea oodinate sstem, and wo sale fatos S, S along the aes of the image oodinate sstem. D & CV models an dietl deal with iel oodinates. We will stat with modifing the otation mati to onside the imat of the non-othogonalit. Pima the -ais of the gound ood. sstem Seonda the -ais etia otation the -ais CE : Digital Photogammeti Sstems Aman F. Habib
18 Pima Rotation & CE : Digital Photogammeti Sstems 8 Aman F. Habib
19 CE : Digital Photogammeti Sstems Aman F. Habib Pima Rotation z R z z z os os
20 Seonda Rotation & CE : Digital Photogammeti Sstems Aman F. Habib
21 CE : Digital Photogammeti Sstems Aman F. Habib Seonda Rotation z R z z z os os
22 etia Rotation & CE : Digital Photogammeti Sstems Aman F. Habib
23 CE : Digital Photogammeti Sstems Aman F. Habib etia Rotation z R z z z os os
24 CE : Digital Photogammeti Sstems Aman F. Habib 4 Rotation in Sae z R R R z // to the gound oodinate sstem // to the image oodinate sstem
25 CE : Digital Photogammeti Sstems Aman F. Habib Rotation in Sae os os os os os os os os os os os os os os : whee R R R R
26 Consideation of the Non-thogonalit os os & CE : Digital Photogammeti Sstems Aman F. Habib
27 CE : Digital Photogammeti Sstems Aman F. Habib os os os os os Consideation of the Non-thogonalit os os os os os os os Assuming small non-othogonalit angle
28 CE : Digital Photogammeti Sstems Aman F. Habib 8 Consideation of the Non-thogonalit os os os os os R R R R
29 CE : Digital Photogammeti Sstems Aman F. Habib Consideation of the Non-thogonalit R z // to the image oodinate sstem // to the gound oodinate sstem R Note:
30 CE : Digital Photogammeti Sstems Aman F. Habib Consideation of the Non-thogonalit Collineait Equations while onsideing the nonothogonalit between the aes of the image oodinate sstem. R
31 CE : Digital Photogammeti Sstems Aman F. Habib R s s / / R s s / / / Divide both sides b -. Consideation of the Sale Fatos Collineait Equations while onsideing the nonothogonalit between the aes of the image oodinate sstem & diffeent sale fatos.
32 CE : Digital Photogammeti Sstems Aman F. Habib Consideation of the Sale Fatos R / / R / / R s, s & -/ `.
33 CE : Digital Photogammeti Sstems Aman F. Habib D & Comute Vision Models R &
34 D & Comute Vision Models CE : Digital Photogammeti Sstems 4 Aman F. Habib
35 D & Comute Vision Models Whee: CE : Digital Photogammeti Sstems Aman F. Habib
36 D & Comute Vision Models ' K R I K { Calibation Mati} R I { Eteio ientation Mati} CE : Digital Photogammeti Sstems Aman F. Habib
37 D & Comute Vision Models he Diet inea ansfomation D, whih has been develoed b the hotogammeti ommunit, is an altenative to the ollineait equations that allows fo diet tansfomation between mahine/iel oodinates and oesonding gound oodinates. & he D an be also eesented b the following fom: CE : Digital Photogammeti Sstems Aman F. Habib
38 D & Comute Vision Models D: Diet inea ansfomation D ' R 4 8 ' R CE : Digital Photogammeti Sstems 8 Aman F. Habib
39 D & CV Models: Piel Coodinates he D & CV models an also onside the diet tansfomation fom iel to gound oodinates. u v CE : Digital Photogammeti Sstems Aman F. Habib
40 D & CV Models: Piel Coodinates CE : Digital Photogammeti Sstems 4 Aman F. Habib
41 D & CV Models: Piel Coodinates CE : Digital Photogammeti Sstems 4 Aman F. Habib
42 D & CV Models: Piel Coodinates Modified Calibation Mati: CE : Digital Photogammeti Sstems 4 Aman F. Habib
43 D & CV Models: Piel Coodinates Fo D when woking with iel oodinates, we have the following model. CE : Digital Photogammeti Sstems 4 Aman F. Habib
44 Moden Photogammet & Comute Vision Moden Photogammet and Comute Vision ae onveging fields. At and siene of tool develoment fo automati geneation of satial and desitive infomation fom multi-senso data and/o sstems CE : Digital Photogammeti Sstems 44 Aman F. Habib
45 D IPs & EPs Aoah # CE : Digital Photogammeti Sstems 4 Aman F. Habib
46 D IP & EP D R 4 8 R CE : Digital Photogammeti Sstems 4 Aman F. Habib
47 CE : Digital Photogammeti Sstems Aman F. Habib 4 D IP & EP No Sign Ambiguit 8 4 Given: hen: 8 4
48 CE : Digital Photogammeti Sstems Aman F. Habib 48 D IP & EP D D KK K R K R D D D D } { Ambiguit Sign hen:
49 CE : Digital Photogammeti Sstems Aman F. Habib 4 D IP & EP D D No Sign Ambiguit hen: KK K R K R D D
50 CE : Digital Photogammeti Sstems Aman F. Habib D D D IP & EP No Sign Ambiguit hen: KK K R K R D D
51 CE : Digital Photogammeti Sstems Aman F. Habib D D D IP & EP KK K R K R D D. No Sign Ambiguit hen:
52 CE : Digital Photogammeti Sstems Aman F. Habib D IP & EP D D KK K R K R D D / No Sign Ambiguit hen:
53 CE : Digital Photogammeti Sstems Aman F. Habib D D D IP & EP KK K R K R D D. No Sign Ambiguit hen:
54 D IP & EP Given: hen: Sign Ambiguit CE : Digital Photogammeti Sstems 4 Aman F. Habib
55 CE : Digital Photogammeti Sstems Aman F. Habib Collineait Equations bjetive: Resolve the sign ambiguit in Sine the sale fato is alwas +ve Assuming that the oigin,, is visible in the image ve ve S
56 D IP & EP B hoog =. 4 8 is Negative R CE : Digital Photogammeti Sstems Aman F. Habib
57 D IP & EP No sign Ambiguit CE : Digital Photogammeti Sstems Aman F. Habib
58 D IP & EP os os os tan No Sign Ambiguit CE : Digital Photogammeti Sstems 8 Aman F. Habib
59 CE : Digital Photogammeti Sstems Aman F. Habib D IP & EP Retieve Note: hee is an ambiguit in detemination annot be distinguished. os os
60 D IP & EP Aoah # : Mati Fatoization CE : Digital Photogammeti Sstems Aman F. Habib
61 CE : Digital Photogammeti Sstems Aman F. Habib D IP Fatoization # Conetual basis: Diet deivation of the alibation mati Cholesk Deomosition of DD K Calibation Mati? Wong D D KK K R K R D D
62 D IP Fatoization # N D D K K CH N M M N M M M N M N M M M K K K K K [ CH{ DD } ] CE : Digital Photogammeti Sstems Aman F. Habib
63 CE : Digital Photogammeti Sstems Aman F. Habib Ug the otation mati R, one an deive the individual otation angles, and. D Rotation Angles
64 Analsis CE : Digital Photogammeti Sstems 4 Aman F. Habib
65 CE : Digital Photogammeti Sstems Aman F. Habib Pesetive Cente ,, is the intesetion oint of thee diffeent lanes whose sufae nomals ae,,,,, and,,, esetivel.
66 CE : Digital Photogammeti Sstems Aman F. Habib Pesetive Cente Assuming:. and. -. he thee sufaes ae othogonal to eah othe. his would lead to bette intesetion.
67 CE : Digital Photogammeti Sstems Aman F. Habib Assuming:. and. -. As and inease, the sufae nomals beome almost aallel. his would lead to weak intesetion. Pesetive Cente
68 CE : Digital Photogammeti Sstems Aman F. Habib 8 he ows of D ae not oelated: he ae othogonal to eah othe. - is well defined. Assuming:. and. -. Rotation Angles
69 CE : Digital Photogammeti Sstems Aman F. Habib Assuming:. and. -. he ows of D tend to be highl oelated. - is not well defined. Rotation Angles
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