Abstract:Modeling is a severe bottleneck for computer graphics applications. Manual modeling is time consuming and fails to capture the complexity of real world scenes. Automated modeling based on acquiring color and depth data is a promising alternative. However, the usual approach of densely sampling the scene from a few viewpoints suffers from long acquisition times, high data redundancy, and lack of robustness, leading to incomplete models.We propose automated modeling based on sampling the scene sparsely from a de… Show more
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