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Computing Stereo-Vision in Video Real-Time with Low-Cost SIMD-Hardware

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3708))

Abstract

The XETAL chip by Philips Electronics is a low-cost hardware-solution for image processing on pixel level. The architecture of XETAL focuses on a low-energy environment and it is therefore highly suited for integration into mobile vision and intelligent cameras. While hardware support for 2D-vision has reached the level of affordable state-of-the-art technology by thorough research, also real-time 3D-vision by stereo, based on the support by a low-cost and low-energy hardware, appears to be able to reach this level soon.

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References

  1. Abbo, A.A., Kleihorst, R.P., Sevat, L., Wielage, P., van Veen, R., Op de Beeck, M.J.R., van der Avoird, A.: A low-power parallel processor IC for digital video cameras. In: ESSCIRC 2001: Proc. European Solid-State Circuits Conference (2001)

    Google Scholar 

  2. Kraft, G., Jonker, P.P.: Real-time stereo with dense output by a SIMD-computed Dynamic Programming algorithm. In: Arabnia, H.R. (ed.) PDPTA 2002: Proc. Int. Conf. on Parallel and Distributed Processing Techniques and Applications, June 2002, vol. III, pp. 1031–1036. CSREA Press, Las Vegas (2002)

    Google Scholar 

  3. Smit, J., Kleihorst, R., Abbo, A., Meuleman, J., van Willigenburg, G.: Real time depth mapping performed on an autonomous stereo vision module. In: ProRISC Program for Research on Integrated Systems and Circuits, pp. 306–310 (2000)

    Google Scholar 

  4. Sunyoto, H., van der Mark, W., Gavrila, D.M.: A comparative study of fast dense stereo vision algorithms. In: IEEE Intelligent Vehicles Symposium, pp. 319–324 (2004)

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© 2005 Springer-Verlag Berlin Heidelberg

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Kraft, G., Kleihorst, R. (2005). Computing Stereo-Vision in Video Real-Time with Low-Cost SIMD-Hardware. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_88

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  • DOI: https://doi.org/10.1007/11558484_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29032-2

  • Online ISBN: 978-3-540-32046-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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