Patent ID: 9489768
Filing Date: 2016-11-08
CPC Classification: G06T

Claim Text:
1. A method to reconstruct 3D model of an object with a structure-from-motion (SFM) processor, the method comprising: receiving with the processor a set of training data including images of the object captured by a camera from various viewpoints; learning a prior comprised of a mean shape describing a commonality of shapes across a category and a set of weighted anchor points encoding similarities between instances in appearance and spatial consistency; matching anchor points across instances to enable learning a mean shape for the category; applying the structure-from-motion (SFM) processor to images of an unseen instance with a shape different from training objects to generate a point cloud; collating bounding boxes from object detection in individual images using the SFM camera poses and localizing and orienting one or more objects in the point cloud; modeling the shape of an object instance as a warped version of a category mean, along with instance-specific details; recovering each object not in a shape prior with a set of displacements and reconstructing an object instance by estimating the warping parameters and modeling semantic similarity as the shape prior with a set of automatically learned anchor points across several instances and a learned mean shape that captures shared commonality between semantic similarities and shape variation across instances; and determining a set of displacement Δ Where i and j are points, parameter μ is empirically determined for the training set, ε