Abstract. We present a methodology and algorithm for the reconstruction of three dimensional geometric models of ancient Maltese water storage systems, i.e. cisterns, from sonar data. This project was conducted as a part of a four week expedition on the islands of Malta and Gozo. During this expedition, investigators used underwater robot systems capable of mapping ancient underwater cisterns and tunnels. The mapping included probabilistic algorithms for constructing the maps of the sonar data and computer graphics for surface reconstruction and visualization. This paper presents the general methodology for the data acquisition and the novel application of algorithms from computer graphics for surface reconstruction to this new data setting. In addition to reconstructing the geometry of the cisterns, the visualization system includes methods to enhance the understanding of the data by visualizing water level and texture detail either through the application of real image data via projective textures or by more standard texture mapping techniques. The resulting surface reconstructions and visualizations can be used by archaeologists for educational purposes and to help understand the shape and history of such water receptacles.
Abstract:This work presents a process pipeline that addresses the problem of reconstructing surfaces of underwater structures from stereo images and sonar scans collected with a micro-ROV on the islands of Malta and Gozo. Using a limited sensor load, sonar and small GoPro Hero2 cameras, the micro-ROV is able to explore water systems and gather data. As a preprocess to the reconstruction pipeline, a 3D evidence grid is created by mosaicing horizontal and vertical sonar scans. A volumetric representation is then constructed using a level set method. Fine-scale details from the scene are captured in stereo cameras, and are transformed into point clouds and projected into the volume. A raycasting technique is used to trim the volume in accordance with the projected point clouds, thus reintroducing fine details to the rough sonar-generated model. The resulting volume is surfaced, yielding a final mesh which can be viewed and interacted with for archaeological and educational purposes. Initial results from both steps of the reconstruction pipeline are presented and discussed.
Abstract:Geometric data acquired via a scanning process can suffer from holes due to errors in the acquisition process, noise, or challenges in merging multiple inputs together into a unified map. We present a straight forward algorithm to fill holes in incomplete evidence grids representing acquired geometric data. We also present our methods to apply learning in order to statistically evaluate the proposed hole filling algorithm. This analysis validates our proposed method for hole filling and additionally enables the construction of a probability distribution function to represent the accuracy of the filled data per model. During surface reconstruction, this function can be used to visualize the certainty of the filled geometry via transparency and coloring giving the user an understanding of the data's accuracy. This work is motivated by a multi-year project to construct educational visualizations of ancient water storage systems, i.e. cisterns and wells within churches, fortresses and homes on the islands of Malta, Gozo and Sicily.
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