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Robust Pose Estimation for Arbitrary Objects in Complex Scenes

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Pattern Recognition (DAGM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3175))

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Abstract

Viewer-centered estimation of the pose of a three dimensional object has two main advantages: No explicit models are needed and error-prone corner detection is not necessary. Eigenspace methods have been successful in pose estimation especially for faces. However, most eigenspace-based algorithms fail if the images are corrupted, e. g. if the object is occluded, the background differs from the training images or the image is geometrically transformed. EigenTracking by Black and Jepson uses robust estimation to find the correct pose. We show that performance degrades for objects whose silhouette changes greatly with 3D rotation. To solve this problem we introduce masks that adapt to the estimated object pose. To this end we used hierarchical eigenspaces containing both the appearance and mask descriptions. We illustrate the improvement in pose estimation precision for some typical objects.

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References

  1. Pentland, A., Moghaddam, B., Starner, T.: View-based and modular eigenspaces for face recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 1994), Seattle, USA, vol. 1, pp. 84–91 (1994)

    Google Scholar 

  2. Yoshimura, S., Kanade, T.: Fast template matching based on the normalized correlation by using multiresolution eigenimages. In: IEEE/RSJ/GI International Conference on Intelligent Robots and Systems, Advanced Robotic Systems and the Real World, New York, USA, vol. 3, pp. 2086–2093 (1994)

    Google Scholar 

  3. Chang, C.Y., Maciejewski, A.A., Balakrishnan, V., Roberts, R.G.: Eigendecomposition- based pose detection in the presence of occlusion. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Maui, HI, pp. 569–576 (2001)

    Google Scholar 

  4. Ohba, K., Ikeuchi, K.: Detectability, uniqueness and reliability of eigen windows for stable verifikation of partially occluded objects. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 1043–1048 (1997)

    Article  Google Scholar 

  5. Leonardis, A., Bischof, H.: Robust recognition using eigenimages. Computer Vision and Image Understanding: CVIU 78, 99–118 (2000)

    Article  Google Scholar 

  6. Wildenauer, H., Bischof, H., Leonardis, A.: Eigenspace pyramids for robust and efficient recognition of scaled eigenimages. In: Proc. Computer Vision WinterWorkshop (CVWW), Valtice, Czech Republic, pp. 115–120 (2003)

    Google Scholar 

  7. Black, M.J., Jepson, A.D.: EigenTracking: Robust matching and tracking of articulated objects using a view-based representation. International Journal of Computer Vision 26, 63–84 (1998)

    Article  Google Scholar 

  8. Nene, S.A., Nayar, S.K., Murase, H.: Columbia object image library (COIL-100). Technical Report CUCS-006-96, Columbia University (1996)

    Google Scholar 

  9. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: Burkhardt, H., Neumann, B. (eds.) Proc. European Conference on Computer Vision, vol. 2, pp. 484–498. Springer, Heidelberg (1998)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Dörfler, P., Schnurr, C. (2004). Robust Pose Estimation for Arbitrary Objects in Complex Scenes. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_56

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  • DOI: https://doi.org/10.1007/978-3-540-28649-3_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22945-2

  • Online ISBN: 978-3-540-28649-3

  • eBook Packages: Springer Book Archive

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