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Boosting event-based structured light via cyclic spatial coding.

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    This study introduces a cyclic spatial coding strategy for event-based structured light (SL) systems. The novel method enhances depth sensing accuracy and efficiency, enabling high-speed 3D reconstruction.

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    Area of Science:

    • Robotics and Computer Vision
    • Neuromorphic Engineering

    Background:

    • Event-based structured light (SL) systems offer high-speed, high dynamic range, and low-power depth sensing using event cameras.
    • Current spatial coding methods in event-based SL present a trade-off between scanning speed and reconstruction quality.

    Purpose of the Study:

    • To develop a novel cyclic spatial coding strategy for event-based SL systems.
    • To improve depth reconstruction accuracy while maintaining high efficiency in event-based SL.

    Main Methods:

    • A cyclic spatial coding strategy embedding geometric constraints through frame-to-frame speckle displacement was designed.
    • A geometric prior-guided stereo matching algorithm was developed to leverage these constraints.
    • A multi-frame enhancing strategy was proposed to improve event frame quality.

    Main Results:

    • The proposed cyclic spatial coding strategy effectively enhances the performance of event-based SL systems.
    • High-accuracy depth reconstruction was achieved by exploiting embedded geometric constraints.
    • The system demonstrated robust 3D sensing capabilities at a high frame rate of 1000 FPS.

    Conclusions:

    • The novel cyclic spatial coding strategy and associated algorithms significantly advance event-based structured light systems.
    • This approach offers a promising solution for high-accuracy, high-speed 3D sensing applications.
    • The method provides a robust basis for stereo matching and depth reconstruction in challenging dynamic scenarios.