Skip to main content
SpringerLink
Log in

Dense Depth Maps from Low Resolution Time-of-Flight Depth and High Resolution Color Views

  • Conference paper
Advances in Visual Computing (ISVC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5876))

Included in the following conference series:

Abstract

In this paper a systematic approach to the processing and combination of high resolution color images and low resolution time-of-flight depth maps is described. The purpose is the calculation of a dense depth map for one of the high resolution color images. Special attention is payed to the different nature of the input data and their large difference in resolution. This way the low resolution time-of-flight measurements are exploited without sacrificing the high resolution observations in the color data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Buehler, C., Bosse, M., McMillan, L., Gortler, S., Cohen, M.: Unstructured lumigraph rendering. In: SIGGRAPH 2001: Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pp. 425–432. ACM, New York (2001)

    Chapter  Google Scholar 

  2. Shade, J., Gortler, S., He, L.w., Szeliski, R.: Layered depth images. In: SIGGRAPH 1998: Proceedings of the 25th annual conference on Computer graphics and interactive techniques, ACM, New York (1998)

    Google Scholar 

  3. Xu, Z., Schwarte, R., Heinol, H., Buxbaum, B., Ringbeck., T.: Smart pixel - photonic mixer device (pmd). In: M2VIP 1998 - International Conference on Mechatronics and Machine Vision in Practice, pp. 259–264 (1998)

    Google Scholar 

  4. Yang, Q., Yang, R., Davis, J., Nister, D.: Spatial-depth super resolution for range images. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR 2007, pp. 1–8 (2007)

    Google Scholar 

  5. Chan, D., Buisman, H., Theobalt, C., Thrun, S.: A noise-aware filter for real-time depth upsampling. In: Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications with ECCV (2008)

    Google Scholar 

  6. Scharstein, D., Szeliski, R., Zabih, R.: A Taxonomy and Evaluation of Dense Two-frame Stereo Correspondence Algorithms. In: Proceedings of IEEE Workshop on Stereo and Multi-BaselineVision, Kauai, HI (2001)

    Google Scholar 

  7. Beder, C., Bartczak, B., Koch, R.: A combined approach for estimating patchlets from PMD depth images and stereo intensity images. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 11–20. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  8. Gudmundsson, S., Aanaes, H., Larsen, R.: Fusion of stereo vision and time-of-flight imaging for improved 3d estimation. In: Proceedings of the DAGM Dyn3D Workshop, Heidelberg, Germany (2007)

    Google Scholar 

  9. Zhu, J., Wang, L., Yang, R., Davis, J.: Fusion of time-of-flight depth and stereo for high accuracy depth maps. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR 2008, pp. 1–8 (2008)

    Google Scholar 

  10. Yoon, K.-J., Kweon, I.S.: Adaptive support-weight approach for correspondence search. IEEE Transactions of Pattern Analysis and Machine Inteligence (PAMI) 28(4), 650–656 (2006)

    Article  Google Scholar 

  11. Egnal, G., Egnal, G., Wildes, R.: Detecting binocular half-occlusions: empirical comparisons of five approaches. IEEE Transactions of Pattern Analysis and Machine Inteligence (PAMI) 24, 1127–1133 (2002)

    Article  Google Scholar 

  12. Muhlmann, K., Maier, D., Hesser, R., Manner, R.: Calculating dense disparity maps from color stereo images, an efficient implementation. In: Proc. IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp. 30–36 (2001)

    Google Scholar 

  13. Goesele, M., Curless, B., Seitz, S.: Multi-view stereo revisited. In: Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2402–2409 (2006)

    Google Scholar 

  14. Furukawa, Y., Ponce, J.: Accurate, dense, and robust multi-view stereopsis. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition CVPR 2007, pp. 1–8 (2007)

    Google Scholar 

  15. Bartczak, B., Schiller, I., Beder, C., Koch, R.: Integration of a time-of-flight camera into a mixed reality system for handling dynamic scenes, moving viewpoints and occlusions in real-time. In: Proceedings of the 3DPVT Workshop, Atlanta, GA, USA (2008)

    Google Scholar 

  16. Pajarola, R., Sainz, M., Meng, Y.: Dmesh: Fast depth-image meshing and warping. Int. J. Image Graphics 4, 653–681 (2004)

    Article  Google Scholar 

  17. Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proc. Sixth International Conference on Computer Vision, pp. 839–846 (1998)

    Google Scholar 

  18. Schiller, I., Beder, C., Koch, R.: Calibration of a pmd camera using a planar calibration object together with a multi-camera setup. In: Proceedings of the ISPRS Congress, Bejing, China (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Kiel, Hermann-Rodewald-Str. 3, 24118, Kiel, Germany

    Bogumil Bartczak & Reinhard Koch

Authors
  1. Bogumil Bartczak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reinhard Koch
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, 338-8570, Japan

    Yoshinori Kuno

  6. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  7. Univ. of Zurich, Department of Informatics, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  8. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  9. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  10.  ,  

    Miguel L. Encarnação

  11. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  12. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bartczak, B., Koch, R. (2009). Dense Depth Maps from Low Resolution Time-of-Flight Depth and High Resolution Color Views. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-10520-3_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10519-7

  • Online ISBN: 978-3-642-10520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation