Abstract
This chapter provides an outline of the concept of the point spread function of an optical system, of the depth from defocus approach, where variations of the point spread function across the set of images are exploited to estimate the depth of scene points, and of the depth from focus method, which aims for determining depth by acquiring several images at different known focus settings.
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References
Barrois, B., Wöhler, C., 2007. 3D pose estimation based on multiple monocular cues. ISPRS Workshop Towards Benchmarking Automated Calibration, Orientation and Surface Reconstruction from Images (BenCOS), held in conjunction with CVPR 2007, Minneapolis, USA.
Bouguet, J.-Y., 2007. Camera Calibration Toolbox for Matlab. http://www.vision.caltech.edu/bouguetj/calib_doc/ (accessed September 04, 2007).
Chaudhuri, S., Rajagopalan, A. N., 1999. Depth from Defocus: A Real Aperture Imaging Approach. Springer, New York.
d’Angelo, P., Wöhler, C., 2005c. 3D surface reconstruction by combination of photopolarimetry and depth from defocus. In: Kropatsch, W., Sablatnig, R., Hanbury, A. (eds.). Pattern Recognition, Proc. 27th DAGM Symposium, Vienna, Austria. Lecture Notes in Computer Science 3663, pp. 176–183, Springer, Berlin.
d’Angelo, P., Wöhler, C., 2008. Image-based 3D surface reconstruction by combination of photometric, geometric, and real-aperture methods. ISPRS J. Photogramm. Remote Sens. 63(3), pp. 297–321.
Harris, C., Stephens, M., 1988. A combined corner and edge detector. Proc. 4th Alvey Vision Conf., pp. 189–192.
Krauß, M., 2006. Integration von Depth-from-Defocus und Shape-from-Polarisation in einen Pose-Estimation-Algorithmus. Diplom Thesis, Faculty of Computer Science and Automation, Technical University of Ilmenau.
Krüger, L., Wöhler, C., Würz-Wessel, A., Stein, F., 2004. In-factory calibration of multiocular camera systems. Proc. SPIE Photonics Europe (Optical Metrology in Production Engineering), Strasbourg, pp. 126–137.
Krüger, L., Wöhler, C., 2011. Accurate chequerboard corner localisation for camera calibration. Pattern Recognit. Lett. 32, pp. 1428–1435.
Kuhl, A., Wöhler, C., Krüger, L., Groß, H.-M., 2006. Monocular 3D scene reconstruction at absolute scales by combination of geometric and real-aperture methods. In: Franke, K., Müller, K.-R., Nickolay, B., Schäfer, R. (eds.), Pattern Recognition, Proc. 28th DAGM Symposium, Heidelberg, Germany. Lecture Notes in Computer Science 4174, pp. 607–616, Springer, Berlin.
Lucas, B. D., Kanade, T., 1981. An iterative image registration technique with an application to stereo vision. Proc. Int. Joint Conf. on Artificial Intelligence, Vancouver, pp. 674–679.
McCloskey, S., Langer, M., Siddiqi, K., 2007. Evolving measurement regions for depth from defocus. Proc. Asian Conf. on Computer Vision. Lecture Notes on Computer Science 4844, pp. 858–868, Springer, Berlin.
Namboodiri, V. P., Chaudhuri, S., Hadap, S., 2008. Regularized depth from defocus. Proc. IEEE Int. Conf. on Image Processing, pp. 1520–1523.
Nayar, S., 1989. Shape from Focus. Carnegie Mellon University, Technical Report CMU-RI-TR-89-27.
Nourbakhsh, I. R., Andre, D., Tomasi, C., Genesereth, M. R., 1997. Mobile robot obstacle avoidance via depth from focus. Robot. Auton. Syst. 22, pp. 151–158.
Pedrotti, F. L., 1993. Introduction to Optics. 2nd Edition, Prentice Hall, New York.
Pentland, A., 1987. A new sense for depth of field. IEEE Trans. Pattern Anal. Mach. Intell. 9, pp. 523–531.
Schaper, D., 2002. Automated quality control for micro-technology components using a depth from focus approach. Proc. 5th IEEE Southwest Symp. on Image Analysis and Interpretation, pp. 50–54.
Shi, J., Tomasi, C., 1994. Good features to track. IEEE Conf. on Computer Vision and Pattern Recognition, Seattle, USA, pp. 593–600.
Subbarao, M., 1988. Parallel depth recovery by changing camera parameters. Proc. Int. Conf. on Computer Vision, pp. 149–155.
Subbarao, M., Surya, G., 1994. Depth from defocus: a spatial domain approach. Int. J. Comput. Vis. 13(3), pp. 271–294.
Subbarao, M., Wei, T.-C., 1992. Depth from defocus and rapid autofocusing: a practical approach. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 773–776.
Watanabe, M., Nayar, S. K., Noguchi, M., 1996. Real-time computation of depth from defocus. Proc. SPIE Three-Dimensional and Unconventional Imaging for Industrial Inspection and Metrology, SPIE 2599, pp. 14–25.
Wöhler, C., d’Angelo, P., Krüger, L., Kuhl, A., Groß, H.-M., 2009. Monocular 3D scene reconstruction at absolute scale. ISPRS J. Photogramm. Remote Sens. 64, pp. 529–540.
Xiong, Y., Shafer, S., 1993. Depth from focusing and defocusing. DARPA Image Understanding Workshop, Palo Alto, California, USA, pp. 967–976.
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Wöhler, C. (2013). Point Spread Function-Based Approaches to Three-Dimensional Scene Reconstruction. In: 3D Computer Vision. X.media.publishing. Springer, London. https://doi.org/10.1007/978-1-4471-4150-1_4
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DOI: https://doi.org/10.1007/978-1-4471-4150-1_4
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