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arXiv Computer Vision

Comparing Commercial Depth Sensor Accuracy for Medical Applications

The study benchmarks four commercial depth sensors—Intel RealSense D405, PMD Flexx2, Stereolabs ZED 2i, and Zivid 2M+ 60—on porcine bone, porcine belly, and a silicone kidney phantom. Using stylus-sampled references, the sensors were evaluated at ~50 cm distance across challenging surfaces such as homogeneous, specular, and subsurface scattering. The Zivid 2M+ 60 achieved the best overall performance, while the ZED 2i ranked second for real tissue but last for the phantom.

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Wound3DAssist: A Practical Framework for 3D Wound Assessment

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RGBD-to-3D Object Mesh Refinement via Depth Matching and Symmetry Propagation

The paper introduces a lightweight RGBD-to-3D refinement technique that improves single-view 3D reconstructions by correcting visible surfaces through bipartite matching with back-projected depth points, mirroring corrections across detected symmetry planes, and propagating them via a smoothness solver. The method is closed-form, significantly faster than optimization-heavy refinements, and works plug-and-play with any RGB-to-3D reconstructor without retraining. Experiments on GSO and OmniObject3D with five backbones show consistent accuracy gains, especially on symmetric objects, and the approach also benefits RGB-D-to-mesh reconstructions and real noisy sensor data.

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