Abstract:
A method of generating a hyperlapse video includes: comparing a first reference point of a first image and a corresponding second reference point of a second image; based on the comparing, displaying a first user interface for matching the first reference point and second reference point; and determining whether to perform automatic shooting for the hyperlapse video based on whether the first reference point and the second reference point match.
Abstract:
A processor-implemented method with sensor calibration includes: estimating a portion of a rotation parameter for a target sensor among a plurality of sensors based on a capture of a reference object; estimating another portion of the rotation parameter for the target sensor based on an intrinsic parameter of the target sensor and a focus of expansion (FOE) determined based on sensing data collected with consecutive frames by the target sensor while the electronic device rectilinearly moves based on one axis; and performing calibration by determining a first extrinsic parameter for the target sensor based on the portion and the other portion of the rotation parameter.
Abstract:
Disclosed is a method and apparatus for adaptive tracking of a target object. The method includes method of tracking an object, the method including estimating a dynamic characteristic of an object in an input image based on frames of the input image, determining a size of a crop region for a current frame of the input image based on the dynamic characteristic of the object, generating a cropped image by cropping the current frame based on the size of the crop region, and generating a result of tracking the object for the current frame using the cropped image.
Abstract:
A processor-implemented neural network method includes: obtaining a first weight kernel of a weight model and pruning information of the first weight kernel; determining, based on the pruning information, a processing range of an input feature map for each weight element vector of the first weight kernel; performing a convolution operation between the input feature map and the first weight kernel based on the determined processing range; and generating an output feature map of a neural network layer based on an operation result of the convolution operation.
Abstract:
Provided are an optical sensor including graphene quantum dots and an image sensor including an optical sensing layer. The optical sensor may include a graphene quantum dot layer that includes a plurality of first graphene quantum dots bonded to a first functional group and a plurality of second graphene quantum dots bonded to a second functional group that is different from the first functional group. An absorption wavelength band of the optical sensor may be adjusted based on types of functional groups bonded to the respective graphene quantum dots and/or sizes of the graphene quantum dots.
Abstract:
Disclosed are heat dissipation structures using nano-sized graphene fragments such as graphene quantum dots (GQDs) and/or methods of manufacturing the heat dissipation structures. A heat dissipation structure includes a heating element, and a heat dissipation film on the heating element to dissipate heat generated from the heating element, to outside. The heat dissipation film may include GQDs.
Abstract:
A method of manufacturing an organic-inorganic composite thin film may include: forming a thin film from a paste that includes an inorganic powder and an organic compound binder by using a screen printing process; and/or performing a pressing process and a heating process with respect to the thin film. The heating process may be performed at a glass transition temperature of the organic compound binder or in a temperature range higher than the glass transition temperature of the organic compound binder. An X-ray detector configured to detect X-rays irradiated from an outside of the X-ray detector may include: a photoconductive material layer in which electron-hole pairs are formed due to absorption of the X-rays. The photoconductive material layer may be formed of an organic-inorganic composite thin film that includes an inorganic powder and an organic compound binder.
Abstract:
A method performed by one or more processors of an electronic device includes: processing an input image and point cloud data corresponding to the input image; projecting the point cloud data to generate a first depth map and adding new depth values to the first depth map based on the input image; obtaining a second depth map by inputting the input image to a depth estimation model configured to infer depth maps from input images; and training the depth estimation model based on a loss difference between the first depth map and the second depth map.
Abstract:
A processor-implemented method with object tracking includes: performing, using a first template, forward object tracking on first image frames in a first sequence group; determining a template candidate of a second template for second image frames in a second sequence group; performing backward object tracking on the first image frames using the template candidate; determining a confidence of the template candidate using a result of comparing a first tracking result determined by the forward object tracking performed on the first image frames and a second tracking result determined by the backward object tracking performed on the first image frames; determining the second template based on the confidence of the template candidate; and performing forward object tracking on the second image frames using the second template.
Abstract:
An electronic device comprises: a memory management module; a processor operatively connected to the memory management module; and a memory controlled by the memory management module and operatively connected to the processor. The memory is configured to store instructions which, when executed, cause the processor to: execute at least one process, identify a rate at which the at least one process is terminated, based on a preconfigured first cycle, determine a number of times the identified rate exceeds a first threshold value, and based on a determination that the number of times the identified rate exceeds the first threshold value is greater than a second threshold value, reboot the electronic device.