Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Provided is a machine learning-based object detection method performed by an object detection apparatus. the method comprises constructing an object detection model by performing machine learning on a training image set, wherein the object detection model is a model for detecting a target object in an input image based on the result of comparing a confidence score for the target object with a threshold value, obtaining an input image given a detection result for the target object, wherein the obtained input image is an image not included in the training image set, predicting one or more object regions, in which the target object exists, in the obtained input image by using the object detection model, classifying a region not matching the detection result among the predicted object regions as a false detection region; and adjusting the threshold value of the object detection model based on a confidence score of the false detection region.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Provided is a machine learning-based object detection method performed by an object detection apparatus. the method comprises constructing an object detection model by performing machine learning on a training image set, wherein the object detection model is a model for detecting a target object in an input image based on the result of comparing a confidence score for the target object with a threshold value, obtaining an input image given a detection result for the target object, wherein the obtained input image is an image not included in the training image set, predicting one or more object regions, in which the target object exists, in the obtained input image by using the object detection model, classifying a region not matching the detection result among the predicted object regions as a false detection region; and adjusting the threshold value of the object detection model based on a confidence score of the false detection region.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Disclosed is a method for reducing noise. The method comprises decoding a bitstream encoded with a first codec, acquiring Quantization Parameter (QP) values determined in a process of encoding the bitstream with the first codec, detecting a frame with noise by using the QP values and inputting the frame with noise to a predefined noise filter.

Abstract: According to a first aspect of the present invention, a method for setting a region of interest may include: detecting a mark in an image frame photographed by a camera; and setting a region of interest using the detected mark.

Abstract: Disclosed is a method for reducing noise. The method comprises decoding a bitstream encoded with a first codec, acquiring Quantization Parameter (QP) values determined in a process of encoding the bitstream with the first codec, detecting a frame with noise by using the QP values and inputting the frame with noise to a predefined noise filter.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: According to an aspect of the present invention, there is provided a method of detecting a repetitive pattern. The method includes: clustering a plurality of pixels that form an input image according to color and obtaining one or more color layers composed of pixels included in each cluster; selecting one or more effective layers from the color layers, wherein each of the effective layers includes a predetermined number or more of pixel components, each composed of a plurality of pixels and having a predetermined shape or a predetermined size of area; selecting a unit pattern repeatedly disposed at different locations in each effective layer from the pixel components included in each effective layer; calculating distances between the unit patterns in each effective layer; and calculating a repetition cycle of the unit pattern of the input image based on the calculated distances in each effective layer.

Abstract: According to an aspect of the present invention, there is provided a method of detecting a repetitive pattern. The method includes: clustering a plurality of pixels that form an input image according to color and obtaining one or more color layers composed of pixels included in each cluster; selecting one or more effective layers from the color layers, wherein each of the effective layers includes a predetermined number or more of pixel components, each composed of a plurality of pixels and having a predetermined shape or a predetermined size of area; selecting a unit pattern repeatedly disposed at different locations in each effective layer from the pixel components included in each effective layer; calculating distances between the unit patterns in each effective layer; and calculating a repetition cycle of the unit pattern of the input image based on the calculated distances in each effective layer.

Abstract: According to an aspect of the present invention, there is provided a method of detecting a repetitive pattern. The method includes: clustering a plurality of pixels that form an input image according to color and obtaining one or more color layers composed of pixels included in each cluster; selecting one or more effective layers from the color layers, wherein each of the effective layers includes a predetermined number or more of pixel components, each composed of a plurality of pixels and having a predetermined shape or a predetermined size of area; selecting a unit pattern repeatedly disposed at different locations in each effective layer from the pixel components included in each effective layer; calculating distances between the unit patterns in each effective layer; and calculating a repetition cycle of the unit pattern of the input image based on the calculated distances in each effective layer.

Abstract: A method of creating a texture map is provided. The method includes extracting feature points of a particular object from one or more image frames captured by a camera; selecting one of the image frames as an image frame to be used in the creation of a texture map of the particular object based on information regarding the extracted feature points; and creating the texture map of the particular object using the selected image frame.

Abstract: According to a first aspect of the present invention, a method for setting a region of interest may include: detecting a mark in an image frame photographed by a camera; and setting a region of interest using the detected mark.

Abstract: According to an aspect of the present invention, there is provided a method of detecting a repetitive pattern. The method includes: clustering a plurality of pixels that form an input image according to color and obtaining one or more color layers composed of pixels included in each cluster; selecting one or more effective layers from the color layers, wherein each of the effective layers includes a predetermined number or more of pixel components, each composed of a plurality of pixels and having a predetermined shape or a predetermined size of area; selecting a unit pattern repeatedly disposed at different locations in each effective layer from the pixel components included in each effective layer; calculating distances between the unit patterns in each effective layer; and calculating a repetition cycle of the unit pattern of the input image based on the calculated distances in each effective layer.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.

Abstract: Disclosed is a method for photographing a panoramic image including the steps of recognizing movement of a corresponding photographing apparatus by comparing a current real-time input image with a previous image through a motion estimation mechanism with exposure compensation, determining a time to photograph each next picture by determining whether movement in a photography direction reaches a preset threshold value, and photographing each next picture by manual or automatic operation at the determined time.