公开(公告)号：US20240296662A1

公开(公告)日：2024-09-05

申请号：US18578471

申请日：2021-08-06

申请人： Siemens Corporation

发明人： Eugen Solowjow ,  Ines Ugalde Diaz ,  Yash Shahapurkar ,  Juan L. Aparicio Ojea ,  Heiko Claussen

IPC分类号： G06V10/774 ,  G06T15/20 ,  G06V10/764 ,  G06V10/776 ,  G06V20/70

CPC分类号： G06V10/774 ,  G06T15/20 ,  G06V10/764 ,  G06V10/776 ,  G06V20/70

摘要： A computer-implemented method for building an object detection module uses mesh representations of objects belonging to specified object classes of interest to render images by a physics-based simulator. Each rendered image captures a simulated environment containing objects belonging to multiple object classes of interest placed in a bin or on a table. The rendered images are generated by randomizing a set of parameters by the simulator to render a range of simulated environments. The randomized parameters include environmental and sensor-based parameters. A label is generated for each rendered image, which includes a two-dimensional representation indicative of location and object classes of objects in that rendered image frame. Each rendered image and the respective label constitute a data sample of a synthetic training dataset. A deep learning model is trained using the synthetic training dataset to output object classes from an input image of a real-world physical environment.