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Integrated video motion estimator with Retinex-like pre-processing for robust motion analysis in automotive scenarios: algorithmic and real-time architecture design

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Abstract

The paper presents a novel technique for robust motion analysis in real automotive scenarios based on integrated Retinex-like pre-processing algorithm with block matching video motion estimator. Both algorithmic and real-time hardware design issues are discussed. The benefits of the proposed technique are manifold: the entire system is more robust; the estimated motion vectors are more reliable and less dependent on critical ambient conditions like shadows or flashes; the proposed algorithm may allow to perform motion estimation using very few bits and running as a 2- or 1-bit transform, still maintaining good performances. Real-time hardware implementation is achieved by design and synthesis in 65 nm CMOS standard-cells technology of an Application Specific Instruction-set Processor. Design optimizations for both the processing core and the memory organization are presented. With respect to the state of the art the proposed hardware implementation ensures bounded circuit complexity, low power consumption and reprogrammability of the technique.

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Acknowledgments

This research was partially supported by grants of the University of Trieste and of the Regione Friuli-Venezia Giulia within the “Eladin 2” project.

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Authors and Affiliations

  1. DEEI, University of Trieste, via Valerio 10, 34127, Trieste, Italy

    Stefano Marsi

  2. Department of Information Engineering, University of Pisa, via G. Caruso 16, 56122, Pisa, Italy

    Sergio Saponara

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  1. Stefano Marsi
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  2. Sergio Saponara
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Correspondence to Sergio Saponara.

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Marsi, S., Saponara, S. Integrated video motion estimator with Retinex-like pre-processing for robust motion analysis in automotive scenarios: algorithmic and real-time architecture design. J Real-Time Image Proc 5, 275–289 (2010). https://doi.org/10.1007/s11554-009-0148-7

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  • DOI: https://doi.org/10.1007/s11554-009-0148-7

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