I am working on a face recognition using 3D data from a special 3D imaging system. For those interested the data comes from the FRGC 2004 dataset. The problem I am having is that for some pixels the scanner fails to capture depth information. The result is that the image has missing values. There are small regions on the face such as eyebrows and eyes that are missing the depth information. I would like to fill in these region by interpolating from nearby pixels but I am not sure of the best way to do that.
I currently have two arrays: * floating point array with depth information (missing data is encoded as a large negative number -999999.0) * boolean array that is a missing data mask I have some ideas on how to solve this problem but I am hoping that someone on this list may have more experience with this type of missing data problem. * Are there any utilities in scipy/numpy designed for this type of missing data problem? * If not does any one have suggestions on how I should proceed? _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
