Electronics and Telecommunications Research Institute

Keun Dong Lee

Weon Geun Oh

Seung Jae Lee

Da Un Jung

Hyung Kwan Son

Young Ho Suh

Jong Gook Ko

Won Young Yoo

Wook Ho Son

Sang Il Na

Sung Kwan Je

Hyuk Jeong

Wookho Son

Seon Tae Kim

Gil Haeng Lee

Su Woong Lee

Seungjae Lee

Dong Seok Jeong

Da-Un Jung

Ju Kyong Jin

Sangil Na

Sungkwan Je

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.

Apparatus and method for searching for building based on image and method of constructing building search database for image-based building search

A fast object detection method and a fast object detection apparatus using an artificial neural network. The fast object detection method includes obtaining an input image; inputting the obtained input image into an object detection neural network using a plurality of preset bounding boxes; and detecting an object included in the input image by acquiring output data of the object detection neural network.

Method and apparatus for high speed object detection using artificial neural network

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.

Machine learning method and apparatus

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.

Server and method for providing city street search service

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.

Apparatus and method for food search service

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.

Method and apparatus for extracting image feature

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.

Shoe image retrieval apparatus and method using matching pair

A system for managing and searching for a digital video includes: a video feature point extraction unit decoding an input video and extracting a feature point; a video feature point database (DB) storing and managing a feature point of a video to be compared (i.e., a comparison target video), and a video feature point comparison unit coarsely comparing the feature point of the input video and that of the comparison target video to acquire a candidate group, and minutely comparing the candidate group to detect a content repeated section, and informing a user of the content repeated section.

Growing community of inventors

Daejeon, South Korea

Keun Dong Lee