Abstract: An apparatus for retraining an object detector according to an exemplary embodiment includes an inputter configured to receive an undetected image, a style transferer configured to generate one or more first augmented images that have the same content attribute as an object area of the undetected image, but a different style attribute, a content transferer configured to generate one or more second augmented images that have the same style attribute as the object area, but a different content attribute, and an influence analyzer configured to analyze a cause of non-detection of the undetected image by comparing object detection reliabilities of the undetected image, the first augmented image, and the second augmented image.

Abstract: An apparatus for retraining an object detector according to an exemplary embodiment includes an inputter configured to receive an undetected image, a style transferer configured to generate one or more first augmented images that have the same content attribute as an object area of the undetected image, but a different style attribute, a content transferer configured to generate one or more second augmented images that have the same style attribute as the object area, but a different content attribute, and an influence analyzer configured to analyze a cause of non-detection of the undetected image by comparing object detection reliabilities of the undetected image, the first augmented image, and the second augmented image.

Abstract: There is provided a method of masking an object of non-interest by a masking apparatus. The method comprises acquiring first video information of a region of interest, determining a first object of non-interest area as an area in which motion vectors are present in the first video information of the region of interest, removing spatial noise from the first object of non-interest area to acquire a second object of non-interest area including at least a part of the first object of non-interest area and generating a mask corresponding to the second object of non-interest area.

Abstract: A method includes acquiring, by a device, encoded image data corresponding to an original image. The method includes decoding, by the device, the encoded image data. The method included acquiring, by the device, a foreground extraction target frame and an encoding parameter associated with an encoding process of the original image based on decoding the encoded image data. The method includes extracting, by the device, a first candidate foreground associated with the foreground extraction target frame based on the encoding parameter. The method includes extracting, by the device, a second candidate foreground associated with the foreground extraction target frame based on a preset image processing algorithm. The method includes determining, by the device, a final foreground associated with the foreground extraction target frame based on the first candidate foreground and the second candidate foreground.

Abstract: A method for selecting an image for object recognition is provided. The method comprises receiving an image bitstream; acquiring predetermined first codec metadata information among codec metadata information from the received image bitstream; calculating a first quality measurement value using the acquired first codec metadata information; calculating a quality score of the image by using the calculated first quality measurement value; and selecting a predetermined number of images based on the calculated quality score of the image.

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 people counting apparatus including: a reception unit which receives a video of an area including an entrance captured by a video capture device; a line setting unit which sets an inline at the entrance and sets an outline such that a specific region is formed on a side of the inline; a detection unit which detects moving objects in the video using information differences between frames of the received video and detects human moving objects among the detected moving objects; a tracking unit which tracks the movement of each of the detected moving objects; and a counting unit which determines whether each of the moving objects passed the inline and the outline based on the tracked movement of each of the moving objects and counts the number of people based on the determination result.

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: 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: 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 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 people counting apparatus including: a reception unit which receives a video of an area including an entrance captured by a video capture device; a line setting unit which sets an inline at the entrance and sets an outline such that a specific region is formed on a side of the inline; a detection unit which detects moving objects in the video using information differences between frames of the received video and detects human moving objects among the detected moving objects; a tracking unit which tracks the movement of each of the detected moving objects; and a counting unit which determines whether each of the moving objects passed the inline and the outline based on the tracked movement of each of the moving objects and counts the number of people based on the determination result.