Lefloch, Damien

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Lefloch, Damien

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    PublicationAccess status: Open Access ,
    Real-time processing of range data focusing on environment reconstruction
    (2017)
    Lefloch, Damien
    With the availability of affordable range imaging sensors, providing real-time three-dimensional information of the captured scene, new types of Computer Vision applications arise. Such applications range from designing new Human-Computer interfaces (known as Natural User Interfaces) to the generation of highly detailed reconstructions of complex scenes (for example to keep track of cultural heritage or crime scenes), to autonomous driving and augmented reality. These depth sensors are mostly based on two efficient technologies: the structured-light principle (such as the Xbox 360 version of the Kinect camera) and the time-of-flight (ToF) principle (as cameras implemented by pmdtechonologies). When ToF cameras measure the time until the light emitted by their illumination unit is backscattered to their smart detectors, the structured-light cameras project a known light pattern onto the scene and measure the amount of distortion between the emitted light pattern and its image. Both technologies have their own advantages and weak points. This dissertation is composed of 4 contributions. First, an efficient approach is proposed to compensate motion artifact of ToF raw images. Thereafter, a work on online three-dimensional reconstruction application has been investigated to improve the robustness of the camera tracker by segmenting moving objects. The second major contribution lies on a robust handling of noise on raw data, during the full reconstruction pipeline, proposing a new type of information fusion which considered the anisotropic nature of noise present on depth data, leading to faster convergence of high-quality reconstructions. Finally, a new method has been designed which uses surface curvature information to robustly reconstruct fine structures of small objects, as well as limiting the total error of camera drift.
    Source Type:Doctoral Thesis
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