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We propose a novel approach to determining the Next Best View (NBV) for the task of efficiently building highly accurate 3D models from images. Our proposed method deploys a hierarchical uncertainty driven model refinement process designed to select vantage viewpoints based on the model’s covariance structure and appearance, as well as the camera characteristics. The developed NBV planning system incrementally builds a sensing strategy by sequentially finding the single camera placement, which best reduces an existing model’s 3D uncertainty. The generic nature of our system’s design and internal data representation makes it well suited to be applied to a wide variety of 3D modeling algorithms. It can be used within active computer vision systems as well as for optimized view selection from the set of available views. Experimental results are presented to illustrate the effectiveness and versatility of our approach.
Dunn et al. (Thu,) studied this question.
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