Computer implemented method and system for retrieval of multi spectral BRDF parameters

A system for retrieval of multi lispectral bidirectional reflectance distribution function (BRDF) parameters by using red-green-blue-depth (RGB-D) data, the system comprising:

• an RGB-D camera configured to capture at least one image of one or more objects in a scene, wherein the captured at least one image of the one or more objects comprises RGB-D data including color and geometry information of the one or more objects;
• and
• a computer comprising:
• memory configured to store a deep neural network comprising an input layer, an output layer, and at least one hidden layer between the input layer and the output layer;
• and
• at least one processor configured to store program instructions that, when executed on the at least one processor, cause the system to:
• reconstruct the captured at least one image of the one or more objects to one or more three-dimensional (3D) reconstructions by using the RGB-D data;
• classify the BRDF of a surface of the one or more objects based on the one or more 3D reconstructions, using the deep neural network;
• and
• retrieve the multi lispectral BRDF parameters by approximation of the classified BRDF using an iterative optimization.

A handheld comprising:

• an RGB-D camera configured to capture at least one image of one or more objects in a scene, wherein the captured at least one image of the one or more objects comprises RGB-D data including color and geometry information of the one or more objects;
• and
• a computer comprising:
• memory configured to store a deep neural network comprising an input layer, an output layer, and at least one hidden layer between the input layer and the output layer;
• and
• at least one processor configured to store program instructions that, when executed on the at least one processor, cause the handheld to:
• reconstruct the captured at least one image of the one or more objects to one or more three-dimensional (3D) reconstructions by using the RGB-D data;
• classify the BRDF of a surface of the one or more objects based on the one or more 3D reconstructions, using the deep neural network;
• and
• retrieve the multi spectral BRDF parameters by approximation of the classified BRDF using an iterative optimization.

A non-transitory computer-readable storage medium that stores instructions executable by one or more processors to retrieve multispectral bidirectional reflectance distribution function (BRDF) parameters by using red-green-blue-depth (RGB-D) data, the instructions comprising:

• capturing at least one image of one or more objects in a scene, wherein the captured at least one image of the one or more objects comprises RGB-D data including color and geometry information of the one or more objects;
• reconstructing the captured at least one image of the one or more objects to one or more three-dimensional (3D) reconstructions by using the RGB-D data;
• classifying, by a deep neural network, the BRDF of a surface of the one or more objects based on the one or more 3D reconstructions, wherein the deep neural network comprises an input layer, an output layer, and at least one hidden layer between the input layer and the output layer;
• and
• retrieving the multi spectral BRDF parameters by approximating the classified BRDF mousing an iterative optimization method.