Electronics and Telecommunications Research Institute

Sung Chan Oh

Jeun Woo Lee

Yong Jin Kwon

Jin Young Moon

Ki Min Yun

Jong Youl Park

Hyung Il Kim

Yu Seok Bae

Joong Won Hwang

Disclosed herein are a method and apparatus for processing feature information based on an artificial neural network. According to an embodiment of the present disclosure, the apparatus for processing feature information based on an artificial neural network may include a memory for storing data and a processor for controlling the memory, and the processor may further be configured to extract a graph, which includes vertices, based on a feature map of an image, to extract a feature vector corresponding to the vertices and to process the graph and the feature vector based on an artificial neural network, and the graph may include positions of the vertices and information on a connection relationship between the vertices.

Method and apparatus for feature transforming and processing based on artificial neural network

Provided is an apparatus for classifying an attribute of an image object, including: a first memory configured to store target object images that are indexed; a second memory configured to store target object images that are un-indexed; and an object attribute classification module configured to perform learning on the un-indexed target object images to construct a classifier for classifying a detailed attribute of target object, and finely adjust the classifier on the basis of the indexed target object images.

Apparatus and method for classifying attribute of image object

A domain adaptation-based object recognition apparatus includes a memory configured to store a domain adaptation-based object recognition program and a processor configured to execute the program. The processor learns a generative model for generating a feature or an image similar to a gallery image on the basis of domain adaptation in association with an input probe image and learns an object recognition classification model by using a learning database corresponding to the gallery image and the input probe image, thereby performing object recognition using the input probe image.

Domain adaptation-based object recognition apparatus and method

Provided is a dynamic object detecting technique, and more specifically, a system and method for determining a state of a motion of a camera on the basis of a local motion estimated on the basis of a video captured by a dynamic camera and a result of analyzing a global motion, flexibly updating a background model according to the state of the motion of the camera, and flexibly detecting a dynamic object according to the state of the motion of the camera.

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Seoul, South Korea

Sung Chan Oh