US 12,293,521 B2
Apparatus and methods for image segmentation using machine learning processes
Chung-Chi Tsai, San Diego, CA (US); Shubhankar Mangesh Borse, San Diego, CA (US); Meng-Lin Wu, San Diego, CA (US); Venkata Ravi Kiran Dayana, San Diego, CA (US); Fatih Murat Porikli, San Diego, CA (US); and An Chen, San Diego, CA (US)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Sep. 1, 2022, as Appl. No. 17/901,429.
Prior Publication US 2024/0078679 A1, Mar. 7, 2024
Int. Cl. G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 30/19 (2022.01)
CPC G06T 7/11 (2017.01) [G06T 7/74 (2017.01); G06V 30/19153 (2022.01); G06V 30/19173 (2022.01); G06T 2207/20112 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus comprising:
a non-transitory, machine-readable storage medium storing instructions; and
at least one processor coupled to the non-transitory, machine-readable storage medium, the at least one processor being configured to:
apply a process to an input image to generate input image feature data characterizing features of the input image, and input image segmentation data characterizing an initial segmentation of the input image;
obtain, for a plurality of reference images, reference image feature data characterizing features of the plurality of reference images, and reference image classification data characterizing classifications of the plurality of reference images;
generate reference image segmentation data based on the reference image feature data, the reference image classification data, and the input image feature data; and
combine values of the input image segmentation data with values of the reference image segmentation data to generate blended image segmentation data, the blended image segmentation data characterizing a final segmentation of the input image.