A methodology for 3D surface modeling from a single image is proposed. The principal novelty is concave and specular surface modeling without any externally imposed prior. The main idea of the method is to use BRDFs and generated rendered surfaces, to transfer the normal field, computed for the generated samples, to the unknown surface. The transferred information is adequate to blow and sculpt the segmented image mask in to a bas-relief of the object. The object surface is further refined basing on a photo-consistency formulation that relates for error minimization the original image and the modeled object.
Dettaglio pubblicazione
2016, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Pages 4414-4423
Single image object modeling based on BRDF and r-surfaces learning (04b Atto di convegno in volume)
Natola Fabrizio, Ntouskos Valsamis, Pirri Ardizzone Maria Fiora, Sanzari Marta
ISBN: 9781467388511; 9781467388511
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