Pointcloud processing Sample Clauses

Pointcloud processing. In order to have reliable information about the diver’s pose; the point cloud should not include many points outside the diver’s body. For this reason, a series of image processing techniques are used in the generated disparity map. First a median filter is applied to eliminate random noise caused by feature mis-matching. Then, erosion and dilation processes are done sequentially to eliminate holes within the point cloud and small sets of isolated points; usually these sets are not nearly as big as the set that encompasses the diver’s body. The resultant image (the rightmost in Figure 3.7) is used as a mask to only use the points on those coordinates as point cloud generators; in this way, PCA will provide more information about the diver and not the surrounding environment. Otherwise, a lot of points from the background, bubbles, reflections, etc, would have formed part of the point cloud. And all of this unnecessary information would have made the PCA computation less accurate. This is shown in the disparity map below.
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Related to Pointcloud processing

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