1. A method of modeling a three-dimensional object from plural image data sources, the method comprising: providing a first point cloud including a first plurality of points defined in space, the first plurality of points being derived using a multiview stereo (MVS) process from a first one or more images of the object, the first one or more images being of a first image type, each point in the first plurality representing a location on a surface of the three-dimensional object, and each point in the first plurality having a first confidence value on a first confidence scale, the first confidence value being based upon an average texturedness value of the first one or more images; providing a second point cloud including a second plurality of points defined in space, the second plurality of points being derived from a second one or more images of the object, the second one or more images being of a second image type, each point in the second plurality representing a location on the surface of the three-dimensional object, and each point in the second plurality having a second confidence value on a second confidence scale; merging the first plurality and the second plurality of points into a third merged point cloud, each point in the third merged point cloud representing a location on the surface of the object, including: normalizing one of the first or second confidence scales with the respective second or first confidence scale; and for each location of the object for which a corresponding point exists in both the first point cloud and the second point cloud, selecting the point for inclusion in the merged point cloud from either the first point cloud or the second point cloud having a greater first or second normalized confidence value.