Abstract

Depth estimation is a fundamental issue in computational stereo. To obtain accurate stereo depth estimation, all mechanical parameters with a high precision need to be measured in order to achieve subpixel accuracy and to match features between two different images. This paper investigates accurate depth estimation with different mechanical parameter errors, such as camera calibration and alignment errors, which mainly result from camera lens distortion, camera translation, rotation, pitch, and yaw. For each source of the errors, a model for the error description is presented, and the accurate depth estimation due to this error is quantitatively analyzed. Depth estimation algorithms under an individual error, and with all the errors, are given. Experimental results show that the proposed models can rectify the errors and calculate the accurate depths effectively.

© 2011 Optical Society of America

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References

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  1. M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
    [CrossRef]
  2. U. R. Dhond and J. K. Aggarwal, “Structure from stereo: a review,” IEEE Trans. Syst. Man Cybern. 19, 1489–1510 (1989).
    [CrossRef]
  3. S. Barnerd and M. A. Fischler, “Computational stereo,” ACM Comput. Surv. 14, 553–572 (1982).
    [CrossRef]
  4. W. Y. Zhao and N. Nandhakumar, “Effects of camera alignment errors on stereoscopic depth estimation,” Pattern Recogn. 29, 2115–2126 (1996).
    [CrossRef]
  5. S. D. Blostein and T. S. Huang, “Error analysis in stereo determination of 3-D point,” IEEE Trans. Pattern Anal. Machine Intell. 9, 752–765 (1987).
    [CrossRef]
  6. J. J. Rodriguez and J. K. Aggarwal, “Stochastic analysis of stereo quantization error,” IEEE Trans. Pattern Anal. Machine Intell. 12, 467–470 (1990).
    [CrossRef]
  7. R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
    [CrossRef]
  8. Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
    [CrossRef]
  9. N. D. Kehtarnavaz and W. Sohn, “Error analysis of camera movements in stereo vehicle tracking systems,” Computer Vision and Image Understanding 62, 347–359 (1995).
    [CrossRef]
  10. A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
    [CrossRef]
  11. J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
    [CrossRef]
  12. A. S. Malik and T.-S. Choi, “Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery,” Pattern Recogn. 40, 154–170 (2007).
    [CrossRef]
  13. W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
    [CrossRef] [PubMed]
  14. A. Verri and V. Torre, “Absolute depth estimates in stereopsis,” J. Opt. Soc. Am. A 3, 297–299 (1986).
    [CrossRef]
  15. J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
    [CrossRef]
  16. S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
    [CrossRef]
  17. Z. Zhang, “Camera calibration with one dimensional objects,” IEEE Trans. Pattern Anal. Machine Intell. 26, 892–899(2004).
    [CrossRef]
  18. T. Clarke and J. Fryer, “The development of camera calibration methods and models,” Photogramm. Rec. 16, 51–66(1998).
    [CrossRef]
  19. M. Ahmed and A. Farag, “Nonmetric calibration of camera lens distortion: differential methods and robust estimation,” IEEE Trans. Image Process. 14, 1215–1230 (2005).
    [CrossRef] [PubMed]
  20. K. Takaya, “Feature point correspondence of stereo images by monogenic phase,” in Proceedings of IEEE Pacific Rim Conference on Communications, Computers and Signal (IEEE, 2007), pp. 272–275.
    [CrossRef]
  21. R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
    [CrossRef]
  22. D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 1988), pp. 742–746.
  23. Y. Xiong and F. Quek, “Automatic aerial image registration without correspondence,” in Proceedings of IEEE International Conference on Computer Vision Systems (IEEE, 2006), pp. 25–32.

2009 (2)

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
[CrossRef] [PubMed]

2008 (1)

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

2007 (2)

J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
[CrossRef]

A. S. Malik and T.-S. Choi, “Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery,” Pattern Recogn. 40, 154–170 (2007).
[CrossRef]

2006 (1)

R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
[CrossRef]

2005 (1)

M. Ahmed and A. Farag, “Nonmetric calibration of camera lens distortion: differential methods and robust estimation,” IEEE Trans. Image Process. 14, 1215–1230 (2005).
[CrossRef] [PubMed]

2004 (2)

A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
[CrossRef]

Z. Zhang, “Camera calibration with one dimensional objects,” IEEE Trans. Pattern Anal. Machine Intell. 26, 892–899(2004).
[CrossRef]

2003 (1)

M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
[CrossRef]

1998 (1)

T. Clarke and J. Fryer, “The development of camera calibration methods and models,” Photogramm. Rec. 16, 51–66(1998).
[CrossRef]

1996 (1)

W. Y. Zhao and N. Nandhakumar, “Effects of camera alignment errors on stereoscopic depth estimation,” Pattern Recogn. 29, 2115–2126 (1996).
[CrossRef]

1995 (1)

N. D. Kehtarnavaz and W. Sohn, “Error analysis of camera movements in stereo vehicle tracking systems,” Computer Vision and Image Understanding 62, 347–359 (1995).
[CrossRef]

1993 (1)

S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
[CrossRef]

1990 (1)

J. J. Rodriguez and J. K. Aggarwal, “Stochastic analysis of stereo quantization error,” IEEE Trans. Pattern Anal. Machine Intell. 12, 467–470 (1990).
[CrossRef]

1989 (1)

U. R. Dhond and J. K. Aggarwal, “Structure from stereo: a review,” IEEE Trans. Syst. Man Cybern. 19, 1489–1510 (1989).
[CrossRef]

1987 (1)

S. D. Blostein and T. S. Huang, “Error analysis in stereo determination of 3-D point,” IEEE Trans. Pattern Anal. Machine Intell. 9, 752–765 (1987).
[CrossRef]

1986 (1)

1982 (1)

S. Barnerd and M. A. Fischler, “Computational stereo,” ACM Comput. Surv. 14, 553–572 (1982).
[CrossRef]

Aggarwal, J. K.

J. J. Rodriguez and J. K. Aggarwal, “Stochastic analysis of stereo quantization error,” IEEE Trans. Pattern Anal. Machine Intell. 12, 467–470 (1990).
[CrossRef]

U. R. Dhond and J. K. Aggarwal, “Structure from stereo: a review,” IEEE Trans. Syst. Man Cybern. 19, 1489–1510 (1989).
[CrossRef]

Ahmed, M.

M. Ahmed and A. Farag, “Nonmetric calibration of camera lens distortion: differential methods and robust estimation,” IEEE Trans. Image Process. 14, 1215–1230 (2005).
[CrossRef] [PubMed]

Barnerd, S.

S. Barnerd and M. A. Fischler, “Computational stereo,” ACM Comput. Surv. 14, 553–572 (1982).
[CrossRef]

Blostein, S. D.

S. D. Blostein and T. S. Huang, “Error analysis in stereo determination of 3-D point,” IEEE Trans. Pattern Anal. Machine Intell. 9, 752–765 (1987).
[CrossRef]

Brada, R.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 1988), pp. 742–746.

Brown, M. Z.

M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
[CrossRef]

Burschka, D.

M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
[CrossRef]

Chaudhuri, S.

A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
[CrossRef]

Choi, T.-S.

A. S. Malik and T.-S. Choi, “Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery,” Pattern Recogn. 40, 154–170 (2007).
[CrossRef]

Clarke, T.

T. Clarke and J. Fryer, “The development of camera calibration methods and models,” Photogramm. Rec. 16, 51–66(1998).
[CrossRef]

Dhond, U. R.

U. R. Dhond and J. K. Aggarwal, “Structure from stereo: a review,” IEEE Trans. Syst. Man Cybern. 19, 1489–1510 (1989).
[CrossRef]

Farag, A.

M. Ahmed and A. Farag, “Nonmetric calibration of camera lens distortion: differential methods and robust estimation,” IEEE Trans. Image Process. 14, 1215–1230 (2005).
[CrossRef] [PubMed]

Fernádez, M. A.

J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
[CrossRef]

Fernádez-Caballero, A.

J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
[CrossRef]

Fischler, M. A.

S. Barnerd and M. A. Fischler, “Computational stereo,” ACM Comput. Surv. 14, 553–572 (1982).
[CrossRef]

Fryer, J.

T. Clarke and J. Fryer, “The development of camera calibration methods and models,” Photogramm. Rec. 16, 51–66(1998).
[CrossRef]

Hager, G. D.

M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
[CrossRef]

Hartley, R. I.

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
[CrossRef]

Huang, T. S.

S. D. Blostein and T. S. Huang, “Error analysis in stereo determination of 3-D point,” IEEE Trans. Pattern Anal. Machine Intell. 9, 752–765 (1987).
[CrossRef]

Hung, Y. P.

S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
[CrossRef]

Kehtarnavaz, N. D.

N. D. Kehtarnavaz and W. Sohn, “Error analysis of camera movements in stereo vehicle tracking systems,” Computer Vision and Image Understanding 62, 347–359 (1995).
[CrossRef]

Keren, D.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 1988), pp. 742–746.

Lera, G.

R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
[CrossRef]

Lin, W. S.

S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
[CrossRef]

Liu, Y.

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

Lóez-Valles, J. M.

J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
[CrossRef]

Malik, A. S.

A. S. Malik and T.-S. Choi, “Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery,” Pattern Recogn. 40, 154–170 (2007).
[CrossRef]

Mayoral, R.

R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
[CrossRef]

Miled, W.

W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
[CrossRef] [PubMed]

Nandhakumar, N.

W. Y. Zhao and N. Nandhakumar, “Effects of camera alignment errors on stereoscopic depth estimation,” Pattern Recogn. 29, 2115–2126 (1996).
[CrossRef]

Nistér, D.

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

Parent, M.

W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
[CrossRef] [PubMed]

Peleg, S.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 1988), pp. 742–746.

Pérez-Ilzarbe, M. J.

R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
[CrossRef]

Pesquet, J. C.

W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
[CrossRef] [PubMed]

Quek, F.

Y. Xiong and F. Quek, “Automatic aerial image registration without correspondence,” in Proceedings of IEEE International Conference on Computer Vision Systems (IEEE, 2006), pp. 25–32.

Rajagopalan, A. N.

A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
[CrossRef]

Rodriguez, J. J.

J. J. Rodriguez and J. K. Aggarwal, “Stochastic analysis of stereo quantization error,” IEEE Trans. Pattern Anal. Machine Intell. 12, 467–470 (1990).
[CrossRef]

Shi, F.

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

Shih, S. W.

S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
[CrossRef]

Sohn, W.

N. D. Kehtarnavaz and W. Sohn, “Error analysis of camera movements in stereo vehicle tracking systems,” Computer Vision and Image Understanding 62, 347–359 (1995).
[CrossRef]

Stewénius, H.

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

Takaya, K.

K. Takaya, “Feature point correspondence of stereo images by monogenic phase,” in Proceedings of IEEE Pacific Rim Conference on Communications, Computers and Signal (IEEE, 2007), pp. 272–275.
[CrossRef]

Torre, V.

Uma, M.

A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
[CrossRef]

Verri, A.

Wang, J.

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

Wang, L.

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

Xiong, Y.

Y. Xiong and F. Quek, “Automatic aerial image registration without correspondence,” in Proceedings of IEEE International Conference on Computer Vision Systems (IEEE, 2006), pp. 25–32.

Yang, Q.

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

Yang, R.

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

Zhang, J.

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

Zhang, Z.

Z. Zhang, “Camera calibration with one dimensional objects,” IEEE Trans. Pattern Anal. Machine Intell. 26, 892–899(2004).
[CrossRef]

Zhao, W. Y.

W. Y. Zhao and N. Nandhakumar, “Effects of camera alignment errors on stereoscopic depth estimation,” Pattern Recogn. 29, 2115–2126 (1996).
[CrossRef]

Zisserman, A.

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
[CrossRef]

ACM Comput. Surv. (1)

S. Barnerd and M. A. Fischler, “Computational stereo,” ACM Comput. Surv. 14, 553–572 (1982).
[CrossRef]

Computer Vision and Image Understanding (1)

N. D. Kehtarnavaz and W. Sohn, “Error analysis of camera movements in stereo vehicle tracking systems,” Computer Vision and Image Understanding 62, 347–359 (1995).
[CrossRef]

IEEE Trans. Image Process. (2)

W. Miled, J. C. Pesquet, and M. Parent, “A convex optimization approach for depth estimation under illumination variation,” IEEE Trans. Image Process. 18, 813–830 (2009).
[CrossRef] [PubMed]

M. Ahmed and A. Farag, “Nonmetric calibration of camera lens distortion: differential methods and robust estimation,” IEEE Trans. Image Process. 14, 1215–1230 (2005).
[CrossRef] [PubMed]

IEEE Trans. Pattern Anal. Machine Intell. (6)

Q. Yang, L. Wang, R. Yang, H. Stewénius, and D. Nistér, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Machine Intell. 31, 492–504 (2009).
[CrossRef]

A. N. Rajagopalan, S. Chaudhuri, and M. Uma, “Depth estimation and image restoration using defocused stereo pairs,” IEEE Trans. Pattern Anal. Machine Intell. 26, 1521–1525 (2004).
[CrossRef]

S. D. Blostein and T. S. Huang, “Error analysis in stereo determination of 3-D point,” IEEE Trans. Pattern Anal. Machine Intell. 9, 752–765 (1987).
[CrossRef]

J. J. Rodriguez and J. K. Aggarwal, “Stochastic analysis of stereo quantization error,” IEEE Trans. Pattern Anal. Machine Intell. 12, 467–470 (1990).
[CrossRef]

M. Z. Brown, D. Burschka, and G. D. Hager, “Advances in computational stereo,” IEEE Trans. Pattern Anal. Machine Intell. 25, 993–1008 (2003).
[CrossRef]

Z. Zhang, “Camera calibration with one dimensional objects,” IEEE Trans. Pattern Anal. Machine Intell. 26, 892–899(2004).
[CrossRef]

IEEE Trans. Syst. Man Cybern. (1)

U. R. Dhond and J. K. Aggarwal, “Structure from stereo: a review,” IEEE Trans. Syst. Man Cybern. 19, 1489–1510 (1989).
[CrossRef]

Image Vis. Comput. (1)

R. Mayoral, G. Lera, and M. J. Pérez-Ilzarbe, “Evaluation of correspondence errors for stereo,” Image Vis. Comput. 24, 1288–1300 (2006).
[CrossRef]

J. Opt. Soc. Am. A (1)

Opt. Eng. (1)

S. W. Shih, Y. P. Hung, and W. S. Lin, “Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem,” Opt. Eng. 32, 138–149(1993).
[CrossRef]

Pattern Recogn. (3)

J. Wang, F. Shi, J. Zhang, and Y. Liu, “A new calibration model of camera lens distortion,” Pattern Recogn. 41, 607–615 (2008).
[CrossRef]

A. S. Malik and T.-S. Choi, “Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery,” Pattern Recogn. 40, 154–170 (2007).
[CrossRef]

W. Y. Zhao and N. Nandhakumar, “Effects of camera alignment errors on stereoscopic depth estimation,” Pattern Recogn. 29, 2115–2126 (1996).
[CrossRef]

Pattern Recogn. Lett. (1)

J. M. Lóez-Valles, M. A. Fernádez, and A. Fernádez-Caballero, “Stereovision depth analysis by two-dimensional motion charge memories,” Pattern Recogn. Lett. 28, 20–30 (2007).
[CrossRef]

Photogramm. Rec. (1)

T. Clarke and J. Fryer, “The development of camera calibration methods and models,” Photogramm. Rec. 16, 51–66(1998).
[CrossRef]

Other (4)

K. Takaya, “Feature point correspondence of stereo images by monogenic phase,” in Proceedings of IEEE Pacific Rim Conference on Communications, Computers and Signal (IEEE, 2007), pp. 272–275.
[CrossRef]

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
[CrossRef]

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 1988), pp. 742–746.

Y. Xiong and F. Quek, “Automatic aerial image registration without correspondence,” in Proceedings of IEEE International Conference on Computer Vision Systems (IEEE, 2006), pp. 25–32.

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Figures (11)

Fig. 1
Fig. 1

Sketch map of the stereo vision system with two cameras.

Fig. 2
Fig. 2

Stereo vision model.

Fig. 3
Fig. 3

Relationship between the image pixel coordinate and the physical coordinate.

Fig. 4
Fig. 4

Stereo vision model with camera lens distortion. O X 2 Y 2 , the ideal image plane coordinate; OUV, the real sensor array plane coordinate; θ and φ, the rotation angles around the x axis and the y axis, separately; P 2 and P 2 , the projects of P in the real sensor array plane and the ideal image plane.

Fig. 5
Fig. 5

Planform of the noncoplanar CCD array stereo vision model. (a) Forward translation. (b) Backward translation.

Fig. 6
Fig. 6

Front view of the stereo vision model with camera rotation. P 1 and P 2 , the projects of P in the image planes A O 1 C and E O 2 F .

Fig. 7
Fig. 7

Stereo vision model with camera pitch. (a) The side elevation of camera 2 with camera pitch; (b) The planform of camera 2 with camera pitch E i F i , ( i = 1 , ... , 5 ) , the sample line on the real image sensor.

Fig. 8
Fig. 8

Planform of the stereo vision model with camera yaw. P 1 and P 2 , the projections of P in image planes AC and EF. EF intersects O O 2 at G. P , the projection of P in the ideal image plane E O F . (a) Camera left yaw; (b) Camera right yaw.

Fig. 9
Fig. 9

Steps of image registration with parameters α, β, and γ.

Fig. 10
Fig. 10

Original images captured from the two cameras under the ideal configuration. (a) Left camera; (b) right camera.

Fig. 11
Fig. 11

Images obtained for the composite errors with obvious differences. (a)  d = 2 mm , α = β = γ = 0 ° ; (b)  d = 0 mm , α = β = 0 ° , γ = 3 ° ; (c)  d = 0 mm , α = β = 0 ° , γ = 6 ° ; (d)  d = 0 mm , α = γ = 0 ° , β = 3 ° ; (e)  d = 0 mm , α = γ = 0 ° , β = 3 ° ; (f)  d = 0 mm , α = β = γ = 5 ° .

Tables (2)

Tables Icon

Table 1 Lens Distortion Effects on the Depth Estimation

Tables Icon

Table 2 Effects on the Depth Estimation by Eq. (14)

Equations (40)

Equations on this page are rendered with MathJax. Learn more.

D = B · f x 2 x 1 f ,
{ u = x d x + u 0 v = y d y + v 0 ,
D = B f ( u 2 u 1 ) · d x f .
[ x r y r ] = f · δ ( x , y ) θ · δ ( x , y ) · y φ · δ ( x , y ) · x + f [ x y ] ,
[ x y ] = f · δ ( x r , y r ) θ · δ ( x r , y r ) · y r φ · δ ( x r , y r ) · x r + f [ x r y r ] .
D = B · f f · δ ( x 2 , y 2 ) θ · δ ( x 2 , y 2 ) · y 2 φ · δ ( x 2 , y 2 ) · x 2 + f · x 2 x 1 f ,
D = B f + x 2 d x 2 x 1 f ,
D = B f x 2 cos γ + y 2 sin γ x 1 f ,
( y 2 f tan α 2 ) sin α + f x 2 = f x ;
D = B f f x 2 ( y 2 f tan α 2 ) sin α + f x 1 f ,
D = B f f x 2 f 2 tan β f + x 2 tan β x 1 f ,
D = B f + ( x 2 cos γ + y 2 sin γ ) d x 2 cos γ + y 2 sin γ x 1 f .
D = B f f ( x 2 cos γ + y 2 sin γ ) f 2 tan β f + ( x 2 cos γ + y 2 sin γ ) tan β x 1 f .
D = B f f X 2 ( Y 2 f tan α 2 ) sin α + f f tan β 1 + X 2 ( Y 2 f tan α 2 ) sin α + f tan β x 1 f ,
D = B f + f X 2 ( Y 2 f tan α 2 ) sin α + f tan β 1 + X 2 ( Y 2 f tan α 2 ) sin α + f tan β d f X 2 ( Y 2 f tan α 2 ) sin α + f f tan β 1 + X 2 ( Y 2 f tan α 2 ) sin α + f tan β x 1 f ,
g 2 ( θ 2 , φ 2 , δ 2 ) = f · δ 2 ( x 2 , y 2 ) θ 2 · δ 2 ( x 2 , y 2 ) · y 2 φ 2 · δ 2 ( x 2 , y 2 ) · x 2 + f ;
g 1 ( θ 1 , φ 1 , δ 1 ) = f · δ 1 ( x 1 , y 1 ) θ 1 · δ 1 ( x 1 , y 1 ) · y 1 φ 1 · δ 1 ( x 1 , y 1 ) · x 1 + f ;
x = K [ I | 0 ] X ,
x = K [ R | 0 ] X = K R K 1 K [ I | 0 ] X = K R K 1 X ,
g ( x , y ) = f ( x cos ( γ ) + y sin ( γ ) + a , y cos ( γ ) x sin ( γ ) + b ) .
g ( x , y ) f ( x + a + y γ x γ 2 2 , y γ 2 2 y x γ + b ) .
E ( a , b , γ ) = [ f ( x , y ) + ( a + y γ γ 2 2 x ) f x + ( b x γ γ 2 2 y ) f y g ( x , y ) ] 2 ,
[ ( f x ) 2 ] a + [ f x f y ] b + [ R f x ] γ = f x ( f g ) ,
[ f x f y ] a + [ ( f y ) 2 ] b + [ R f y ] γ = f y ( f g ) ,
[ R f x ] a + [ R f y ] b + [ R 2 ] γ = R ( f g ) ,
tan V = tan ( β + τ ) = tan β + tan τ 1 tan β · tan τ .
x f = tan β + x 2 f 1 tan β · x 2 f
x = f 2 tan β + f x 2 f x 2 tan β .
D = B · f f x 2 + f 2 tan β f x 2 tan β x 1 f .
tan β = tan ( V + τ ) = tan V + tan τ 1 tan V · tan τ .
tan β = x f + x 2 f 1 + x x 2 f 2
x = f 2 tan β + f x 2 f x 2 tan β .
D = B · f f x 2 + f 2 tan β f x 2 tan β x 1 f .
tan V = tan ( β + τ ) = tan β + tan τ 1 tan β · tan τ .
x 2 f = tan β + x f 1 + x f tan β
x = f 2 tan β + f x 2 f x 2 tan β .
D = B · f f x 2 + f 2 tan β f x 2 tan β x 1 f .
D = B · f f x 2 + f 2 tan β f x 2 tan β x 1 f .
x = f x 2 f 2 tan β f + x 2 tan β ,
D = B f f x 2 f 2 tan β f + x 2 tan β x 1 f .

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