Abstract: The present invention estimates parameters for 3D models. Parameters may include, without limitation, surface topology, edge geometry, luminous or reflective characteristics, visual properties, characterization of noise in the signal, or other. A metric is estimated by quantifying a relationship between a received signal and a reference signal. The metric is then utilized to determine a parameter for a 3D model. The metric may include a measurement such as the cross-correlation of the received signal and the reference signal, or standard deviation of the difference of the received signal and the reference signal, for example. The parameter obtained may then be used to create a reference signal for determination of another parameter.

Abstract: The present invention estimates parameters for 3D models. Parameters may include, without limitation, surface topology, edge geometry, luminous or reflective characteristics, visual properties, characterization of noise in the signal, or other. A metric is estimated by quantifying a relationship between a received signal and a reference signal. The metric is then utilized to determine a parameter for a 3D model. The metric may include a measurement such as the cross-correlation of the received signal and the reference signal, or standard deviation of the difference of the received signal and the reference signal, for example. The parameter obtained may then be used to create a reference signal for determination of another parameter.

Abstract: In one example, a method of generating a 3D electronic model of one or more physical objects includes obtaining reflectance data associated with a physical object, obtaining key features from within the reflectance data, utilizing the key features to obtain a model parameter or plurality of model parameters, and estimating the value of a model parameter or plurality of model parameters that characterize a 3D electronic model of the physical object.