Building 3D models from multiple 2D images captured from a variety of viewing positions is nothing new, but doing so for highly detailed or cluttered environments at high resolution has proved difficult because of the large amounts of data involved.
The Disney Research, Zürich team, however, developed an algorithm that can effectively leverage these amounts of data, and process them efficiently without the need to keep all of the input data in memory at one time.
The research is published in a paper called Scene Reconstruction from High Spatio-Angular Resolution Light Fields.
Many 3D models now are obtained using laser scanning. In complex, cluttered environments, however, a single laser scan misses a lot of detail because objects in the foreground can block the laser’s view. Photography makes it easier to capture the scene from multiple viewpoints, but combining photographs to build a 3D model is burdensome at high resolutions.
Disney Research’s algorithm first computes reliable depth estimates specifically around object boundaries instead of interior regions, by operating on individual light rays instead of image patches. More homogeneous interior regions are then processed in a fine-to-coarse procedure rather than the standard coarse-to-fine approaches. “This allows our algorithm to retain precise object contours while still ensuring smooth reconstructions in less detailed areas.” ..
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