Abstract
In this paper we investigate the quality of 3D-2D pose estimates using hand labeled line and point correspondences. We select point correspondences from junctions in the image, allowing to construct a meaningful interpretation about how the junction is formed, as proposed in e.g. [1], [2], [3]. We make us of this information referred as the semantic interpretation, to identify the different types of junctions (i.e. L-junctions and T-junctions). T-junctions often denote occluding contour, and thus do not designate a point in space. We show that the semantic interpretations is useful for the removal of these T-junction from correspondence sets, since they have a negative effect on motion estimates. Furthermore, we demonstrate the possibility to derive additional line correspondences from junctions using the semantic interpretation, providing more constraints and thereby more robust estimates.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Parida, L., Geiger, D., Hummel, R.: Junctions: detection, classification and reconstruction. In: CVPR 1998. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 20, pp. 687–698 (1998)
Rohr, K.: Recognizing corners by fitting parametric models. International Journal of Computer Vision 9, 213–230 (1992)
Kalkan, S., Yan, S., Pilz, F., Krüger, N.: Improving junction detection by semantic interpretation. In: VISAPP 2007. International Conference on Computer Vision Theory and Applications (2007)
Ball, R.: The theory of screws. Cambridge University Press, Cambridge (1900)
Steinbach, E.: Data driven 3-D Rigid Body Motion and Structure Estimation. Shaker Verlag (2000)
Phong, T., Horaud, R., Yassine, A., Tao, P.: Object pose from 2-D to 3-D point and line correspondences. International Journal of Computer Vision 15, 225–243 (1995)
Krüger, N., Jäger, T., Perwass, C.: Extraction of object representations from stereo imagesequences utilizing statistical and deterministic regularities in visual data. In: DAGM Workshop on Cognitive Vision, pp. 92–100 (2002)
Grimson, W. (ed.): Object Recognition by Computer. MIT Press, Cambridge (1990)
Rosenhahn, B., Sommer, G.: Adaptive pose estimation for different corresponding entities. In: Van Gool, L. (ed.) Pattern Recognition. LNCS, vol. 2449, pp. 265–273. Springer, Heidelberg (2002)
Araujo, H., Carceroni, R., Brown, C.: A fully projective formulation to improve the accuracy of lowe’s pose–estimation algorithm. Computer Vision and Image Understanding 70, 227–238 (1998)
Rosenhahn, B., Perwass, C., Sommer, G.: Cvonline: Foundations about 2d-3d pose estimation. In: Fisher, R. (ed.) CVonline: On-Line Compendium of Computer Vision [Online] (2004), http://homepages.inf.ed.ac.uk/rbf/CVonline/
Krüger, N., Wörgötter, F.: Statistical and deterministic regularities: Utilisation of motion and grouping in biological and artificial visual systems. Advances in Imaging and Electron Physics 131, 82–147 (2004)
Wettegren, B., Christensen, L., Rosenhahn, B., Granert, O., Krüger, N.: Image uncertainty and pose estimation in 3d euclidian space. In: DSAGM 2005. Proceedings DSAGM 13th Danish Conference on Pattern Recognition and Image Analysis, pp. 76–84 (2005)
J.M., S.: Some remarks on the statistics of pose estimation. Technical Report SBU-CISM-00-25, South Bank University, London (2000)
Liu, Y., Huang, T., Faugeras, O.: Determination of camera location from 2-d to 3-d line and point correspondence. In: CVPR 1989. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 12, pp. 28–37 (1989)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pilz, F., Shi, Y., Grest, D., Pugeault, N., Kalkan, S., Krüger, N. (2007). Utilizing Semantic Interpretation of Junctions for 3D-2D Pose Estimation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76858-6_67
Download citation
DOI: https://doi.org/10.1007/978-3-540-76858-6_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76857-9
Online ISBN: 978-3-540-76858-6
eBook Packages: Computer ScienceComputer Science (R0)