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arXiv · 2008.07861

Depth Completion with RGB Prior

Yuri Feldman·Yoel Shapiro·Dotan Di Castro
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Abstract

Depth cameras are a prominent perception system for robotics, especially when operating in natural unstructured environments. Industrial applications, however, typically involve reflective objects under harsh lighting conditions, a challenging scenario for depth cameras, as it induces numerous reflections and deflections, leading to loss of robustness and deteriorated accuracy. Here, we developed a deep model to correct the depth channel in RGBD images, aiming to restore the depth information to the required accuracy. To train the model, we created a novel industrial dataset that we now present to the public. The data was collected with low-end depth cameras and the ground truth depth was generated by multi-view fusion.

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Yuri Feldman, Yoel Shapiro, Dotan Di Castro. 2020-08-18. Depth Completion with RGB Prior. https://arxiv.org/abs/2008.07861

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