Electronic device and method for assisting with driving of vehicle
AssigneeSamsung Electronics Co., Ltd.
InventorYosub Park
Life of this patent
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Abstract
An electronic device may include a processor configured to: obtain a plurality of images, the plurality of images including a first image captured by a first camera or image sensor, and a second image captured by a second camera or image sensor. The processor may further be configured to: determine whether a first object and a second object respectively included in the first image and the second image are a same object, and based on determining that the first object and the second object are the same object, train a neural network data recognition model to recognize the first object and the second object as the same object in both the first image and the second image by using the first image and the second image as training data of the neural network data recognition model.
Claims18
An electronic device comprising:
- a communication interface;
- a memory storing one or more instructions;
- and
- a processor configured to execute the one or more instructions stored in the memory to:
- obtain a plurality of images of a real world scene, through the communication interface, the plurality of images including a first image captured by a first camera or image sensor, and a second image captured by a second camera or image sensor;
- determine whether a first object included in the first image and a second object included in the second image are a same object, wherein the first object and the second object are determined to be the same object based on a similarity between the first object and the second object and based on a first piece of capturing time and location information and a second piece of capturing time and location information respectively corresponding to the first image and the second image corresponding to a same location at a same time point, and wherein the first piece of capturing time and location information and the second piece of capturing time and location information include information about a time point and information about a location at which the first image and the second image is captured, respectively;
- and
- based on determining that the first object and the second object are the same object, modify and refine a neural network data recognition model to recognize the first object and the second object as the same object in both the first image and the second image by using the first image and the second image as training data of the neural network data recognition model.
A method comprising:
- obtaining a plurality of images of a real world scene, through a communication interface, the plurality of images including a first image captured by a first camera or image sensor, and a second image captured by a second camera or image sensor;
- determining whether or not a first object and a second object respectively included in the first image and the second image are a same object, wherein the first object and the second object are determined to be the same object based on a similarity between the first object and the second object and based on a first piece of capturing time and location information and a second piece of capturing time and location information respectively corresponding to the first image and the second image corresponding to a same location at a same time point, wherein the first piece of capturing time and location information and the second piece of capturing time and location information include information about a time point and information about a location at which the first image and the second image is captured, respectively;
- and
- based on determining that the first object and the second object are the same object, modifying and refining a neural network data recognition model to recognize the first object and the second object as the same object in both the first image and the second image by using the first image and the second image as training data of the neural network data recognition model.
A computer-implemented method of training a neural network for object detection comprising:
- collecting a set of digital sample images from a database;
- inputting the collected set of digital sample images into a neural network recognition model;
- and
- modifying and refining the neural network recognition model to recognize a first object in a first digital image as a specific object based on the first object being similar to a second object in a second digital image that is co-located with the first object at a same time point.
Dependencies are inferred from the claim text.