Aligning input image data with model input data to generate image annotations

Abstract

An image data annotation system automatically annotates a physical object within individual images frames of an image sequence with relevant object annotations based on a three-dimensional (3D) model of the physical object. Annotating the individual image frames with object annotations includes updating individual image frames within image input data to generate annotated image data that is suitable for reliably training a DNN object detection architecture. Exemplary object annotations that the image data annotation system can automatically apply to individual image frames include, inter alia, object pose, image pose, object masks, 3D bounding boxes composited over the physical object, 2D bounding boxes composited over the physical object, and/or depth map information. Annotating the individual image frames may be accomplished by aligning the 3D model of the physical object with a multi-view reconstruction of the physical object that is generated by inputting an image sequence into a Structure-from-Motion and/or Multi-view Stereo pipeline.