Abstract
Scene depth estimation is gaining importance as more and more AR/VR and robot vision applications are developed. Conventional depth-from-defocus techniques can passively provide depth maps from a single image. This is especially advantageous for moving scenes. However, they suffer a depth ambiguity problem where two distinct depth planes can have the same amount of defocus blur in the captured image. We solve the ambiguity problem and, as a consequence, introduce a passive technique that provides a one-to-one mapping between depth and defocus blur. Our method relies on the fact that the relationship between defocus blur and depth is also wavelength dependent. The depth ambiguity is thus solved by leveraging (multi-) spectral information. Specifically, we analyze the difference in defocus blur of two channels to obtain different scene depth regions. This paper provides the derivation of our solution, a robustness analysis, and validation on consumer lenses.
Highlights
Optical depth estimation, in which depth is estimated using radiation properties, is receiving increased attention due to the proliferation of augmented/virtual reality applications [1,2,3] and robot vision systems [4, 5]
The objective of this section is to show that the relationships derived between defocus blur, depth and wavelength can extend to a typical lens, and demonstrate the generalization of our proposed metric ∆
Knowing the sign of the metric, a one-to-one mapping between defocus blur and depth can be obtained, irrespective of where the camera is focused during capture
Summary
In which depth is estimated using radiation properties, is receiving increased attention due to the proliferation of augmented/virtual reality applications [1,2,3] and robot vision systems [4, 5] These applications require depth maps to be generated continuously in real time. Time-of-flight and structured-light approaches can eliminate the need for multiple captures, but require synthetic illumination that can be problematic in bright or outdoor locations [8] For these reasons, passive methods requiring only a single capture can prove to be very advantageous. Our closed-form solution, which does not require calibration or aperture modifications, makes it possible to obtain an unambiguous, injective mapping between depth and defocus blur. To the best of our knowledge, the first solution that can be used to correct previous depth-from-defocus methods, as it requires no hardware modifications (in contrast with coded apertures or chromatic-aberration-exaggerated lenses) and no calibration or knowledge of camera settings
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