Systems and methods for automatically generating training image sets for an object

• Main Authors: Muir, Eric Raymond, Evans, Nick Shadbeh, Staudinger, Tyler C
• Format: Patent
• Language: English
• Published: 05.01.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

A computer-implemented method for generating a training image set includes retrieving, from at least one memory device, model data corresponding to a three-dimensional (3-D) model of a target object, and creating a plurality of two-dimensional (2-D) synthetic images from the model data. The 2-D synthetic images include a plurality of views of the 3-D model. The method also includes creating a plurality of semantic segmentation images by identifying a plurality of pixels that define the target object in the 2-D synthetic image, and assigning a semantic segmentation label to the identified pixels of the target object. The method further includes generating linking data associating each of the semantic segmentation labels with a corresponding one of the 2-D synthetic images, and storing the training image set including the 2-D synthetic images, the semantic segmentation labels, and the linking data.