Electronics and Telecommunications Research Institute

Su Woong Lee

Hyung Keun Jee

Jun Suk Lee

Seung Jae Lee

Won Young Yoo

Keun Dong Lee

Yong Hun Kim

Jong Gook Ko

Sangwon Um

Shihua Ming

Suk Hyun Lim

Jun Sup Lee

Junsuk Lee

Jae Sang Yoo

Seok Bin Kang

Seokjae Lee

Ho Young Yoo

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

The present invention relates to an apparatus and method for providing personalized adaptive e-learning, and more specifically, to an apparatus and method for estimating a learner's proficiency to each attribute and providing adaptive e-learning by taking into consideration an item answering result of an individual learner in a personalized learning environment.

Apparatus and method for providing personalized adaptive e-learning

Provided is a system for detecting an object from a depth image. The system includes a communication module, a memory, and a processor. By executing the object detection program, the processor extracts a first object area and a second object area from the depth image, based on a predetermined floor plane and an outer plane which is set with respect to the predetermined floor plane. The processor extracts a target area including pixels of the second object area which are spaced apart from the first object area by a predetermined interval. The processor samples a pixel, which is not included in the target area, to extract a floor area from the second object area, calculates a boundary value of an object and a floor, based on the floor area and the target area, and extracts a foreground pixel from the target area, based on the calculated boundary value.

System and method for detecting object from depth image

Disclosed are an apparatus and a method for providing mixed reality for a virtual experience service, and more particularly, an apparatus and a method for providing mixed reality contents for learning a virtual experience based on a story that provides a service in which a user in a real world appears in a virtual world having the story to undergo a virtual experience. The method picks up the user image in the real world and synthesizes the picked-up image with a desired position of a 3D virtual world. According to the present disclosure, a realistic experience based learning can be provided while a spatial limit is overcome.

Apparatus and method for providing mixed reality contents for learning through story-based virtual experience

Disclosed are an apparatus for extracting an image object in a 3D image system and a method thereof. The apparatus for extracting an image object in a 3D image system includes: an image inputting unit receiving an image; a space setting unit setting virtual space at which the image object is positioned from the received image; and an object extracting unit extracting the image object from the set virtual space from the received image.

Apparatus for extracting image object in 3D image system and method thereof

A method for recognizing markers printed on a learning material, includes sampling an image of the learning material; grouping the sampled image of pixels into a first image group and a second image group based on a threshold; and calculating medians of the first image group and the second image group to update the threshold with a first average value of the calculated medians. Further, the method for recognizing markers printed on the learning material includes repeating the above until a difference between a previous threshold and an updated threshold is equal to or smaller than a reference value; binarizing an image captured by a camera based on the updated threshold; and detecting the markers based on the binary image.

Method for recognizing markers using dynamic threshold and learning system based on augmented reality using marker recognition

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Sejong-si, South Korea

Su Woong Lee