Model acquisition by registration of multiple acoustic range views

This paper deals with the three-dimensional reconstruction of an underwater environment from multiple acoustic range views acquired by a remotely operated vehicle. The problem is made challenging by the very noisy nature of the data, the low resolution and the narrow field of view of the sensor. Our contribution is twofold: first, we introduce a statistically sound thresholding (the X84 rejection rule) to improve ICP robustness against noise and non-overlapping data. Second, we propose a new global registration technique to distribute registration errors evenly across all views. Our approach does not use data points after the first pairwise registration, for it works only on the transformations. Therefore, it is fast and occupies only a small memory. Experimental results suggest that ICP with X84 performs better than Zhang's ICP, and that the global registration technique is effective in reducing and equalizing the error.