[36] Ji, Q., S. Costa, M. Haralick, and L. Shapiro. 2000. A robust linear least squaresestimation of camera exterior orientation using multiple geometric features. IS-PRS Journal of Phtogrammetry and Remote Sensing 55,75–93.[37] Kubik, K. 1992. Photogrammetric restitution based on linear features. InternationalArchives of Photogrammetry and Remote Sensing 29(B3),687–690.[38] Lee, C., and J.S. Bethel. 2004. Extraction, modelling, and use of linear featuresfor restituion of airborne hyperspectral imagery. ISPRS Photogrammetry& Remote Sensing 58,289–300.[39] Lee, Y. 2002. Pose estimation of line cameras using linear features. Ph.D.dissertation, Department of Civil and Environmental Engineering and GeodeticScience, The Ohio State University, Columbus, OH.[40] Lin, H.T. 2002. Autonomous recovery of exterior orientaion of imagery usingfree-form linear features. Ph.D. dissertation, Department of Civil and EnvironmentalEngineering and Geodetic Science, The Ohio State University, Columbus,OH.[41] Marr, D. 1982. Vision. New York, NY, Freeman Publishers.[42] Masry, S.E. 1981. Digital mapping using entities:a new concept. PhotogrammetricEngineering and Remote Sensing 48(11),1561–1565.[43] Mikhail, E.M. 1993. Linear features for photogrammetric restitution and objectcompletion. SPIE proceedings- Integrating photogrammetric techniques <strong>with</strong> sceneanalysis and machine vision, Orlando, FL Vol. 1944.[44] Mikhail, E.M., and K. Weerawong. 1994. Feature-based photogrammetric objectconstruction. Proceedings of ASPRS/ACSM Annual Convention 1,403–407.[45] Moravec, H. 1977. Towards automatic visual obstacle avoidance. Proceedings ofthe international joint conference on artificial intelligence 584.[46] Mulawa, D.C. 1989. Estimation and photogrammetric treatment of linear features.Ph.D. dissertation, Department of Civil Engineering, Purdue University,West Lafayette, IN.[47] Mulawa, D.C., and E.M. Mikhail. 1988. Photogrammetric treatment of linearfeatures. International Archives of Photogrammetry and Remote Sensing, Kyoto,Japan 27(B10),383–393.[48] Nasri, A.H., C.W.A.M. van Overveld, and B. Wyvill. 2001. A recursive subdivisionalgorithm for piecewise circular spline. Computer Graphics forum 20(1),35–45.116
[49] Parian, J.A., and A. Gruen. 2005. Panoramic camera calibration using 3Dstraight lines. International Archives of Photogrammetry, Remote Sensing andSpatial Information Sciences, ISPRS Panoramic Photogrammetry Workshop,Berlin, Germany XXXVI(5/W8).[50] Petsa, E., and P. Patias. 1994. Formulation and assessment of straight line basedalgorithms for digital photogrammetry. International Archives of Photogrammetryand Remote Sensing, Melbourne, Australia 30(5),310–317.[51] Prewitt, J. 1970. Object enhancement and extraction in picture processing andpsychopictorics. New York, NY, Academic Press.[52] Rabbani, T., Dijkman S., Heuvel F., and Vosselman G. 2007. An integratedapproach for modelling and global registration of point clouds. ISPRS Photogrammetry& Remote Sensing 61,355–370.[53] Roth, G., and M.D. Levine. 1994. Geometric primitive extraction using a geneticalgorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence16(9),901–905.[54] Sarkar, S., and K.L. Boyer. 1993. Integration, inference, and management ofspatial information using bayesian networks: perceptual organization. IEEETransactions on Pattern Analysis and Machine Intelligence 15(3),256–274.[55] Sarkar, S., and K.L. Boyer. 1994. Computing perceptual organization in computervision. River Edge, NJ, World Scientific.[56] Schenk, T. 1998. Determining transformation parameters between surfaces <strong>with</strong>outidentical points. Tech. Rep. No. 15, Department of Civil and EnvironmentEngineering and Geodetic Science, The Ohio State University.[57] Schenk, T. 1999. Digital photogrammetry Vol.I. Laurelville, OH, TerraScience.[58] Schenk, T. 2002. Towards a feature-based photogrammetry. Bildteknik/ImageScience, 2002(1), Swedish Society for Photogrammetry and Remote Sensing,Stockholm 143–150.[59] Schenk, T. 2004. From point-based to feature-based aerial triangulation. ISPRSPhotogrammetry & Remote Sensing 48,315–329.[60] Schenk, T., and C. Toth. 1993. Towards a fully automated aero-triangulationsystem. ACSM/ASPRS, Annual Convention Technical Papers 3,340–347.[61] Schenk, T., C. Toth, and J. Li. 1991. Towards an autonomous system for orientingdigital stereopaires. Photogrammetric Engineering and Remote Sensing57(8),1057–1064.117
- Page 2:
c○ Copyright byWon Hee Lee2008
- Page 7 and 8:
ACKNOWLEDGMENTSThanks be to God, my
- Page 10 and 11:
3. BUNDLE BLOCK ADJUSTMENTWITH 3D N
- Page 13 and 14:
CHAPTER 1INTRODUCTION1.1 OverviewOn
- Page 15 and 16:
y an intersection employing more th
- Page 17 and 18:
similarity of geometric properties
- Page 19 and 20:
straight linear features or formula
- Page 21 and 22:
• Bundle block adjustment by the
- Page 23 and 24:
Hessian. Interest point operators w
- Page 25 and 26:
[60], Ebner and Ohlhof(1994) [16],
- Page 27 and 28:
a complicated problem. The developm
- Page 29 and 30:
⎡⎢⎣x i − x py i − y p−f
- Page 31 and 32:
x p = −f (X A + t · a − X C )r
- Page 33 and 34:
surfaces and terrain models in 2D a
- Page 35 and 36:
f(u) − e(u) = g(u)f(u) − e(u) =
- Page 37 and 38:
Tankovich[69] used linear features
- Page 39 and 40:
(a) 0th order continuity (b) 1st or
- Page 41 and 42:
Cardinal splineA Cardinal spline is
- Page 43 and 44:
2.3.2 Fourier transformFourier seri
- Page 45 and 46:
For other polyline expressions, Aya
- Page 47 and 48:
Each segment of a natural cubic spl
- Page 49 and 50:
⎡⎢⎣2 11 4 11 4 1· · ·1 4 1
- Page 51 and 52:
3.2 Extended collinearity equation
- Page 53 and 54:
R −1 = R T . The matrix R T (= R
- Page 55 and 56:
dx p = M 1 dX C + M 2 dY C + M 3 dZ
- Page 57 and 58:
In this research, the arc-length pa
- Page 59 and 60:
=√∫ √√√ ()ti+1−f u′ (
- Page 61 and 62:
This equation can be replaced with
- Page 63 and 64:
order polynomial using Newton’s d
- Page 65 and 66:
y collinearity equations, tangents
- Page 67 and 68:
d tan(θ t ) = w′ (v ′ w − w
- Page 69 and 70:
y each two points, which are four e
- Page 71 and 72:
+M 14 db i3 + M 15 dc i0 + M 16 dc
- Page 73 and 74:
collinearity model are described in
- Page 75 and 76:
[ ] [ ] [ ]N11 N 12 ˆξ1 c1N12T =N
- Page 77 and 78: systematic errors in the image spac
- Page 79 and 80: interval based on the normal distri
- Page 81 and 82: 1 ∂Φ2 ∂l= (X C + d 1 l − a i
- Page 83 and 84: about splines, their relationships,
- Page 85 and 86: cubic spline in the image and the o
- Page 87 and 88: The redundancy budget of a tie poin
- Page 89 and 90: of bundle block adjustment is requi
- Page 91 and 92: ξ kiSP = [ da i0 da i1 da i2 da i3
- Page 93 and 94: Spline location parametersImage 1 I
- Page 95 and 96: Spline location parametersImage 1 I
- Page 97 and 98: 5.3 Recovery of EOPs and spline par
- Page 99 and 100: Table 5.7 expressed the convergence
- Page 101 and 102: Iteration with an incorrect spline
- Page 103 and 104: Vertical aerial photographData 9 Ju
- Page 105 and 106: All locations are assumed as on the
- Page 107 and 108: of the Gauss-Markov model correspon
- Page 109 and 110: estimation is obstacled by the corr
- Page 111 and 112: Interior orientation defines a tran
- Page 113 and 114: + fu ( w2 31 (X i (t) − X C ) + s
- Page 115 and 116: A.2 Derivation of arc-length parame
- Page 117 and 118: +2f( t [1 + t 2) − 1 22s 12 (Y i
- Page 119 and 120: +Du ′ ( t 1 + t 22)2r 11 t + Dv
- Page 121 and 122: A 17 = t [2 − t 1 16 2 f(t 1) −
- Page 123 and 124: 1−u ′ w − w ′ u {w′ [s 21
- Page 125 and 126: BIBLIOGRAPHY[1] Ackerman, F., and V
- Page 127: [24] Haala, N., and G. Vosselman. 1
- Page 131: [73] Vosselman, G., and H. Veldhuis