US 11,704,917 B2
Multi-sensor analysis of food
Cynthia Kuo, Mountain View, CA (US); Maher Matta, Sunnyvale, CA (US); and Avik Santra, Munich (DE)
Assigned to Infineon Technologies AG, Neubiberg (DE)
Filed by Infineon Technologies AG, Neubiberg (DE)
Filed on Jul. 6, 2021, as Appl. No. 17/368,570.
Claims priority of provisional application 63/049,823, filed on Jul. 9, 2020.
Prior Publication US 2022/0012467 A1, Jan. 13, 2022
Int. Cl. G01S 13/86 (2006.01); G06V 20/64 (2022.01); G06T 7/00 (2017.01); G06V 10/82 (2022.01); G16H 20/60 (2018.01); G06V 20/68 (2022.01)
CPC G06V 20/647 (2022.01) [G01S 13/867 (2013.01); G06T 7/0004 (2013.01); G06V 10/82 (2022.01); G06T 2207/30128 (2013.01); G06V 20/68 (2022.01); G16H 20/60 (2018.01)] 31 Claims
OG exemplary drawing
 
1. A method for estimating a composition of food, the method comprising:
receiving a first 3D image;
identifying food in the first 3D image;
determining a volume of the identified food based on the first 3D image; and
estimating a composition of the identified food using a millimeter-wave radar, wherein estimating the composition of food comprises:
receiving radar data from an ADC of the millimeter-wave radar,
preprocessing the received radar data to generate a radar image, and
using a deep convolutional neural network (DCNN) to estimate the composition of the food based on the radar image.