We introduce an innovative 3D depth sensing scheme that seamlessly integrates various depth sensing modalities and technologies into a single compact device. Our approach dynamically switches between depth sensing modes, including iTOF and structured light, enabling real-time data fusion of depth images. We successfully demonstrated iToF depth imaging without multipath interference (MPI), simultaneously achieving high image resolution (VGA) and high depth accuracy at a frame rate of 30 fps.
How we visually perceive non-emissive objects in our surrounding depends on the interaction of light with the optical characteristics of the materials that comprise them. The macroscopic surface roughness can also influence the appearance through shadowing and interreflections. In this work, we use a structured light scanner to estimate the surface structure of near-planar surfaces, namely of printing textiles. We compare our scans, both qualitatively and quantitatively, to those from a commercial highgrade profilometer based on the confocal principle. We achieve comparable results to the profilometer on samples with moderately complex surfaces. We discuss the possible reasons for errors in the scans of complex surfaces, thus providing guidelines for robust depth estimation. This comparison can help other researchers build more robust acquisition setups by understanding and minimizing the errors inherent to the reconstruction methods.