| CPC G06T 7/55 (2017.01) [G06T 7/0012 (2013.01); G06T 2200/28 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30088 (2013.01); G06T 2207/30096 (2013.01)] | 30 Claims |

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1. A method, comprising:
storing input data of an object in a storage engine of a system, the input data comprising first-order primitives and second-order primitives;
determining, by operation of an analytics engine of the system, a plurality of features of the object based on the first-order primitives and the second-order primitives;
generating, by operation of the analytics engine of the system, a tensor field, the tensor field comprising an attribute set, the attribute set comprising one or more attributes selected from the first-order primitives, the second-order primitives, and the plurality of features, the tensor field being organized based on attributes of a single pixel, a single voxel, a super pixel, a super frame, or a cluster of the same, the tensor field comprising subgroups defined based on types of attributes contained in the attribute set, the subgroups comprising:
a first subgroup containing one or more scalar attributes;
a second subgroup containing one or more vector attributes; and
a third subgroup containing one or more attributes containing 3D information; and
processing, by operation of the analytics engine of the system, the tensor field according to an artificial intelligence algorithm to generate output data representing the object, wherein the output data comprises surface normal and curvature data.
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