8 March 2002 Automatic landmark extraction from three-dimensional head scan data
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Automatic extraction of anatomic landmarks from three-dimensional (3-D) head scan data is a typical, also challenging application of 3-D image analysis. This paper explored approaches to automatically identify landmarks based on their geometric appearance in a 3-D data set. We investigated the geometric features of most important landmarks of the head/face, especially invariant surface characteristics such as mean and Gaussian curvature, and other external characteristics as well. Based on the analysis of these features, we define a number of methods and operators to locate each extractable landmark from 3-D scan data. Starting from nose, the process to locate face landmarks can be conducted in a structural way and we reduced the image analysis of each landmark to a local area. Ideally, the characteristic map derived from a 3-D digital image should deliver a meaningful image for analysis. However, due to noise and void in the data set, it is not unusual the characteristic map has to be post-processed or re-computed. A number of experiments is conducted to find the suitable computational technique and additional steps are taken to obtain a satisfied characteristic map.
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Peng Li, Peng Li, Brian D. Corner, Brian D. Corner, Steven Paquette, Steven Paquette, "Automatic landmark extraction from three-dimensional head scan data", Proc. SPIE 4661, Three-Dimensional Image Capture and Applications V, (8 March 2002); doi: 10.1117/12.460170; https://doi.org/10.1117/12.460170

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