US 12,755,524 B2Granted

Method of training machine learning model for detecting target object in infrared image, method executed by processor therefor, onboard vehicle computer unit therefor, non-transitory computer readable storage medium comprising program codes therefor, vehicle

AssigneeSubaru Corporation

InventorEvan Millison

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Abstract

A method classifies an IR image to be used for training a machine learning model. The method comprises: (i) providing a set of machine learning models in function of temperature; (ii) acquiring an infrared image; (iii) identifying a target object to be detected and a comparison object in the infrared image; (iv) calculating a first characteristic of the target object in the infrared image and a second characteristic of the comparison object in the infrared image; and (v) based on the first characteristic of the target object and the second characteristic of the comparison object, selecting a machine learning model among the set of machine learning models in function of temperature for the IR image.

Claims12

Dependent claims

A method of classifying an infrared image into training data to be used for training a machine learning model for detecting a target object in infrared images, the method comprising:

(i) providing a set of machine learning models, each machine learning model being associated with a respective range of a difference obtained by subtracting an average pixel value of pixels corresponding to a target object from an average pixel value of pixels corresponding to a comparison object;
(ii) acquiring an infrared image;
(iii) identifying, in the infrared image, pixels corresponding to the target object and pixels corresponding to the comparison object;
(iv) calculating a first average pixel value of the pixels corresponding to the target object and a second average pixel value of the pixels corresponding to the comparison object;
(v) calculating the difference by subtracting the first average pixel value from the second average pixel value;
and
(vi) selecting, from the set of machine learning models, one machine learning model associated with the respective range including the difference, and classifying the infrared image into training data to be used to train the selected machine learning model.

4 more elements

A method executed by a processor for detecting a target object in an infrared image for image recognition,

(a) providing a set of machine-learned models trained using training data classified by a method, the method comprising:
(a1) providing a set of machine learning models in function of temperature;
(a2) acquiring a training infrared image;
(a3) identifying a target object to be detected and a comparison object in the training infrared image;
(a4) calculating a first characteristic of the target object in the training infrared image and a second characteristic of the comparison object in the training infrared image;
and
(a5) based on the first characteristic of the target object and the second characteristic of the comparison object, selecting a machine learning model among the set of machine learning models in function of temperature for the training infrared image;
and
(b) acquiring an infrared image;
(c) acquiring an outside temperature related to the infrared image;
(d) based on the outside temperature, selecting a machine-learned model among the set of machine-learned models;
(e) using the selected model to identify whether the infrared image includes a target object and a comparison object;
(f) if either one or both of a target object and a comparison object is not identified in the infrared image, repeating the steps (b) to (e);
(g) if a target object and a comparison object are both identified in the infrared image, calculating the first characteristic of the target object in the infrared image and the second characteristic of the comparison object in the infrared image;
(h) based on the first characteristic of the target object and the second characteristic of the comparison object, selecting a machine learning model among the set of machine learning models in function of temperature;
(i) if the acquired outside temperature is within the temperature range of the selected machine learning model, determining the selected machine learning model as the model to be used;
(j) if the acquired outside temperature is not within a temperature range of the selected machine learning model, selecting another machine learning model that corresponds to the acquired outside temperature, and determining the selected another machine learning model as the model to be used;
and
(k) using the determined model to be used for the image recognition of the target object.

16 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/737,338Filed 7 Jun 2024
Published: US 2025/0378685 A111 Dec 2025
Granted: 6 Oct 2026
Term ends: Not estimatedThe source records don’t support an estimate.

Classification5 codes

G06V 10/87
Using pattern recognition or machine learning: using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system
G06V 10/26
Image preprocessing: segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g.…
G06V 10/764
Using pattern recognition or machine learning: using classification, e.g. of video objects
G06V 20/58
Exterior to a vehicle by using sensors mounted on the vehicle: recognition of moving objects or obstacles, e.g. vehicles or pedestrians;…