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We conclude with a few remarks concerning practical and theoretical aspects of the manifold lifting framework.
Finally, another open question in the manifold lifting framework is what could be said about the uniqueness of ℳ x) given samples of Φℳ x).
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We have presented a geometric framework in which many multi-view imaging problems may be cast and explained how this framework can inform the design of effective manifold lifting algorithms for joint reconstruction.
Multirate control design in the lifting framework consists of lifting the system and subsequently designing a controller for the single-rate lifted system.
The GLCI is described in the general lifting framework and several variants are introduced.
Figure 7 Reconstruction results in manifold lifting demonstration.
Figure 8 Comparative reconstructions for manifold lifting demonstration.
c Joint reconstruction using our manifold lifting algorithm with unknown camera positions, PSNR 23.6 dB.
Figure 6c shows the final estimated camera positions after all iterations of our manifold lifting algorithm.
As a proof of concept, we now present a comprehensive multi-view reconstruction algorithm inspired by the manifold lifting viewpoint.
The goal of a manifold lifting algorithm is to recover an ensemble of images from their low-dimensional measurements.
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