Issue No. 04 - April (1989 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.19036
A method for identifying unoccluded three-dimensional objects from arbitrary viewing angles is presented. The technique uses synthetically generated range data in a model-based feature vector classification scheme. Fourier descriptors and moments are used for feature vector generation from, respectively, contour imagery, and silhouette or range imagery. A method is developed for generating an exhaustive set of library views and worst-case test views that is based on a polyhedral approximation to a sphere. Analysis of the success of this approach is made with experiments on a six-airplane data set. A model of range data noise is developed, and results are presented for both ideal and noisy lower-resolution image-classification tests. The use of multiple views for object identification is discussed, and results for one-, two-, and three-view tests are presented.<
computerised picture processing, computerised pattern recognition, polyhedral approximation, 3D objects identification, pattern recognition, computerised picture processing, range data, model-based feature vector classification, Fourier descriptors, contour imagery, silhouette, range imagery, Testing, Object recognition, Libraries, Image sampling, Airplanes, Spatial resolution, Image resolution, Image classification, Noise reduction, Noise level
"Identification of three-dimensional objects using range information," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 11, no. , pp. 403,404,405,406,407,408,409,410, 1989.