Depth from Dual Differential Defocus and Stereo Consensus 文章

ArXiv CS.CV2026-06-03NEWSen作者: Junjie Luo, Wei Xu, Dylan Chu, Emma Alexander, Qi Guo

摘要

arXiv:2606.02906v1 Announce Type: cross Abstract: We introduce D^3S Consensus, a physics-based, closed-form algorithm that unifies depth-from-defocus (DfD) and stereo to achieve highly accurate depth estimation throughout an extended working range beyond the depth-of-field (DoF) of cameras. Given a pair of dual-defocus stereo images, the method estimates an overdetermined set of depth using a novel DfD theory, Dual Differential Defocus (D^3), and (S)tereo in a coupled fashion. It then picks the most confident depth prediction from the set by enforcing consensus between these physically independent cues to reject unreliable estimates. Analysis shows that D^3S achieves a comparable working range under the same error tolerance with 10x smaller baseline than previous triangulation-based depth estimation systems. This enables compact passive binocular rangefinders with substantially smaller form factors than conventional stereo and DfD designs.

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Depth from Dual Differential Defocus and Stereo Consensus
2026-06-03PRODUCT_LAUNCH影响: MEDIUM

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