Abstract: An apparatus and method for searching for a building on the basis of an image and a method of constructing a building search database (DB) for image-based building search. The method includes constructing a building search DB, receiving a query image from a user terminal, detecting a region to which a building belongs in the query image, extracting features of the region detected in the query image, and searching the building search DB for a building matching the extracted features. Therefore, building search performance can be improved.

Abstract: A machine learning method for learning how to form bounding boxes, performed by a machine learning apparatus, includes extracting learning images including a target object among a plurality of learning images included in a learning database, generating additional learning images in which the target object is rotated from the learning images including the target object, and updating the learning database using the additional learning images.

Abstract: An apparatus and method for searching for a building on the basis of an image and a method of constructing a building search database (DB) for image-based building search. The method includes constructing a building search DB, receiving a query image from a user terminal, detecting a region to which a building belongs in the query image, extracting features of the region detected in the query image, and searching the building search DB for a building matching the extracted features. Therefore, building search performance can be improved.

Abstract: A server for providing a city street search service includes a street information database configured to store city street images, a feature selection unit configured to select at least one feature according to a predetermined criterion when a city street image for searching and two or more features for the image are received from a user terminal, a candidate extraction unit configured to extract a candidate list of a city street image, a feature matching unit configured to match the city street image for registration included in the extracted candidate list and the at least one selected feature, and a search result provision unit configured to provide the user terminal with a result of the matching as result information regarding the city street image for searching.

Abstract: An omni-channel management method includes receiving a distribution channel information and a product purchase information from each of a plurality of distribution channels, and integrating the received distribution channel information and the product purchase information; applying an image identification technology and a voice identification technology to retrieve and integrate information related to a product; receiving and integrating product information from a manufacturer, a seller, or a web site; verifying consistency of the integrated product information by checking whether detailed information included in the integrated product information is related to a same product; and providing the consistency-secured product information to a consumer and a plurality of distribution channels.

Abstract: A machine learning method for learning how to form bounding boxes, performed by a machine learning apparatus, includes extracting learning images including a target object among a plurality of learning images included in a learning database, generating additional learning images in which the target object is rotated from the learning images including the target object, and updating the learning database using the additional learning images.

Abstract: An apparatus for food search service includes a food region extractor configured to perform detection in regions in an image where food is present and extract a plurality of candidate regions; a candidate region refiner configured to cluster the candidate regions into groups according to a ratio of overlap between the candidate regions; and a search result generator configured to determine a position of a food region and a food item from the grouped candidate regions.

Abstract: A method for extracting features from an image for use in a computing device, the method comprising: producing Gaussian Scale Space (GSS) images in the type of a pyramid from the image inputted to the computing device; performing a Scale Normalized Laplacian Filtering on the GSS images; detecting interest points from the images that are subject to the Scale Normalized Laplacian Filtering; and extracting features of the image using the detected interest points.

Abstract: An apparatus for food search service includes a food region extractor configured to perform detection in regions in an image where food is present and extract a plurality of candidate regions; a candidate region refiner configured to cluster the candidate regions into groups according to a ratio of overlap between the candidate regions; and a search result generator configured to determine a position of a food region and a food item from the grouped candidate regions.

Abstract: A server for providing a city street search service includes a street information database configured to store city street images, a feature selection unit configured to select at least one feature according to a predetermined criterion when a city street image for searching and two or more features for the image are received from a user terminal, a candidate extraction unit configured to extract a candidate list of a city street image, a feature matching unit configured to match the city street image for registration included in the extracted candidate list and the at least one selected feature, and a search result provision unit configured to provide the user terminal with a result of the matching as result information regarding the city street image for searching.

Abstract: Provided are an apparatus and method for automatically generating a visual annotation with respect to a massive image based on a visual language. The apparatus for automatically generating a visual annotation based on a visual language includes an image input unit configured to receive an input image, an image analyzing unit configured to extract feature information of the input image received by the image input unit, a searching unit configured to search a similar image with respect to the input Image and text information included in the similar image by using the feature information extracted by the image analyzing unit, and a visual annotation configuring unit configured to configure a visual annotation with respect to the input image by using the text information searched by the searching unit.

Abstract: Provided is a visual search system. The visual search system according to an embodiment of the inventive concept may include a database that stores characteristic information for a visual search, and a visual search update server that updates the DB based on an image of a target captured by a moving object or a fixed object. According to an embodiment of the inventive concept, it is possible to efficiently update a DB for a visual search because images captured by not only the moving object but also the fixed object are used.

Abstract: Provided are a shoe image retrieval apparatus and method using a matching pair, which can accurately retrieve image information corresponding to an inputted image from the database and provide the retrieved image information, by normalizing a correspondence relation in consideration of geometric image transformation about the matching pair and allowing a similar image to be retrieved by applying the normalized correspondence relation. It is possible to detect optimum geometric image transformation from a matching pair between the inputted shoe image and the image stored in the database and simultaneously retrieve a plurality of objects in the inputted shoe image based on the detected geometric image transformation, thereby providing an efficient shoe retrieval service.

Abstract: A method and system for extracting a visual descriptor using a feature selection are provided. The system includes an image input unit configured to receive an image, a candidate feature point group detecting unit configured to detect a point having a local maximum or minimum of local region filtering in scale-space images as being included in a candidate feature point group, a feature point selecting unit configured to calculate an importance for each candidate feature point, depending on its characteristics, select the candidate feature point as a feature point when its importance is greater than the predetermined threshold value, a dominant orientation calculating unit configured to calculate a dominant orientation of the selected feature point and a visual descriptor extracting unit configured to extract a patch for each feature point, according to its scale, location and dominant orientation, and extract a visual descriptor from the patch.

Abstract: A method for extracting features from an image for use in a computing device, the method comprising: producing Gaussian Scale Space (GSS) images in the type of a pyramid from the image inputted to the computing device; performing a Scale Normalized Laplacian Filtering on the GSS images; detecting interest points from the images that are subject to the Scale Normalized Laplacian Filtering; and extracting features of the image using the detected interest points.

Abstract: Provided are an apparatus and method for automatically generating a visual annotation with respect to a massive image based on a visual language. The apparatus for automatically generating a visual annotation based on a visual language includes an image input unit configured to receive an input image, an image analyzing unit configured to extract feature information of the input image received by the image input unit, a searching unit configured to search a similar image with respect to the input Image and text information included in the similar image by using the feature information extracted by the image analyzing unit, and a visual annotation configuring unit configured to configure a visual annotation with respect to the input image by using the text information searched by the searching unit.

Abstract: Provided are a shoe image retrieval apparatus and method using a matching pair, which can accurately retrieve image information corresponding to an inputted image from the database and provide the retrieved image information, by normalizing a correspondence relation in consideration of geometric image transformation about the matching pair and allowing a similar image to be retrieved by applying the normalized correspondence relation. It is possible to detect optimum geometric image transformation from a matching pair between the inputted shoe image and the image stored in the database and simultaneously retrieve a plurality of objects in the inputted shoe image based on the detected geometric image transformation, thereby providing an efficient shoe retrieval service.

Abstract: A method and system for extracting a visual descriptor using a feature selection are provided. The system includes an image input unit configured to receive an image, a candidate feature point group detecting unit configured to detect a point having a local maximum or minimum of local region filtering in scale-space images as being included in a candidate feature point group, a feature point selecting unit configured to calculate an importance for each candidate feature point, depending on its characteristics, select the candidate feature point as a feature point when its importance is greater than the predetermined threshold value, a dominant orientation calculating unit configured to calculate a dominant orientation of the selected feature point and a visual descriptor extracting unit configured to extract a patch for each feature point, according to its scale, location and dominant orientation, and extract a visual descriptor from the patch.

Abstract: An apparatus and method for processing an image based on feature points is provided, more specifically, provides a technology used in extracting feature points with high importance after determination of importance, searching images, and the like. Therefore, matching images can be effectively performed, and efficiency of time and memory can be increased.

Abstract: A feature descriptor extracting method in a feature descriptor extracting apparatus is provided. The feature descriptor extracting method involves receiving an image from which a feature descriptor will be extracted, extracting a point at which a change in a pixel statistical value of the image is large as a feature point, and extracting a patch centered on the feature point, blocking the patch to calculate a statistical value of each of a plurality of patch blocks, calculating a morphological gradient by using a statistical value of the block-converted patch, and extracting a feature descriptor by using the morphological gradient in consideration of required feature descriptor complexity.