Computer Science > Computer Vision and Pattern Recognition
[Submitted on 13 Nov 2022 (v1), last revised 10 Sep 2023 (this version, v2)]
Title:Batch-based Model Registration for Fast 3D Sherd Reconstruction
View PDFAbstract:3D reconstruction techniques have widely been used for digital documentation of archaeological fragments. However, efficient digital capture of fragments remains as a challenge. In this work, we aim to develop a portable, high-throughput, and accurate reconstruction system for efficient digitization of fragments excavated in archaeological sites. To realize high-throughput digitization of large numbers of objects, an effective strategy is to perform scanning and reconstruction in batches. However, effective batch-based scanning and reconstruction face two key challenges: 1) how to correlate partial scans of the same object from multiple batch scans, and 2) how to register and reconstruct complete models from partial scans that exhibit only small overlaps. To tackle these two challenges, we develop a new batch-based matching algorithm that pairs the front and back sides of the fragments, and a new Bilateral Boundary ICP algorithm that can register partial scans sharing very narrow overlapping regions. Extensive validation in labs and testing in excavation sites demonstrate that these designs enable efficient batch-based scanning for fragments. We show that such a batch-based scanning and reconstruction pipeline can have immediate applications on digitizing sherds in archaeological excavations. Our project page: this https URL.
Submission history
From: Jiepeng Wang [view email][v1] Sun, 13 Nov 2022 13:08:59 UTC (23,145 KB)
[v2] Sun, 10 Sep 2023 07:12:27 UTC (4,206 KB)
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