Samsung Electronics Co., Ltd.

Junho Rim

Jaewook Shin

Aeran Lim

Hyunsoo Choi

Sungjin Kim

Myungjin Eom

Inhak Na

Jaedeok Kim

Jungwook Kim

Haedong Yeo

Juyong Song

Hyungdong Lee

Yoonsik Tak

A device and method for providing a recipe video are provided, the method including obtaining text feature information corresponding to each step of a cooking recipe, the cooking recipe comprising a plurality of steps corresponding to a plurality of coking actions; obtaining image feature information corresponding to each frame of a plurality of frames constituting a cooking video; matching each step of the cooking recipe with a respective section of the cooking video based on a correlation between the obtained text feature information and the obtained image feature information obtained using a machine learned matching model, wherein the respective section of the cooking video corresponds to a respective step among the plurality of steps; and generating the recipe video by using the respective section of the cooking video matched with each step of the cooking recipe.

Method and device for providing recipe video

An electronic device recognizing an object is provided. The electronic device includes a plurality of computing units, a memory, and a processor configured to control at least one of the plurality of computing units such that object information about objects obtained by recognizing the objects existing in a space by using a first recognition model, divide the space into a plurality of subset spaces, based on the object information, determine at least one recognition model, based on characteristic information of each of the subset spaces, assign the determined recognition model to one computing unit, based on characteristic information of each of a plurality of computing units and characteristic information of the determined recognition model, and control the plurality of computing units to perform object recognition by using the determined recognition model and the one computing unit in each of the subset spaces.

Electronic device assigning recognition model to computing unit and operating method thereof

A method of generating a time-lapse video includes: identifying an image storage mode; obtaining a first image; based on identifying that the image storage mode is an emphasis mode for emphasizing one or more images, obtaining a first time difference between the first image and a stored image, and a first feature value indicating a first amount of change between the first image and the stored image; for each respective image of a first plurality of images of a first image group stored in a memory, identifying a second image from among the first plurality of images, based on a second time difference and a second feature value; generating a second image group by removing the second image from the first image group and adding the first image to the first image group; and generating the time-lapse video by using a second plurality of images of the second image group.

Method and home appliance device for generating time-lapse video

The electronic device includes a camera, a non-volatile memory storing at least one instruction and a plurality of object recognition models, a volatile memory, and a processor, connected to the non-volatile memory, the volatile memory, and the camera, and configured to control the electronic device. The processor, by executing the at least one instruction, is configured to, based on an operation mode of the electronic device, load, to the volatile memory, a hierarchical object recognition model having a hierarchical structure corresponding to the operation mode, the hierarchical object recognition model including objection recognition models among the plurality of object recognition models, obtain information on an object by inputting an object image obtained through the camera to the hierarchical object recognition model, and determine an operation of the electronic device based on the information on the object.

Electronic device and method for controlling the electronic device

A robot cleaner includes an intake port, a shock detection sensor, a camera, a memory, and a processor. The memory may include an artificial intelligence model trained to identify an object, and the processor may, based on the object being ingested by the intake port, identify an image obtained within a preset time before the object is ingested, among a plurality of images obtained through the camera and identify the object according to the artificial intelligence model. Thereby, a user may be informed that the robot cleaner has ingested the object.

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Suwon-si, South Korea

Junho Rim