Korea Electronics Technology Institute

Ju Hong Yoon

Min Gyu Park

Je Woo Kim

Choong Sang Cho

Young Han Lee

Young Bae Hwang

Ju Mi Kang

Yong Hoon Kwon

There are provided an apparatus and a method for reconstructing a 3D human object in real time based on a monocular color image. A 3D human object reconstruction apparatus according to an embodiment extracts a pixel-aligned feature from a monocular image, extracts a ray-invariant feature from the pixel-aligned feature, generates encoded position information by encoding position information of a point, predicts a SD of a point from the ray-invariant feature and the encoded position information which are extracted, and reconstructs a 3D human object by using the predicted SD. Accordingly, the ray-invariant feature extracted from the pixel-aligned feature, and the encoded position information are used, so that an amount of computation for predicting SDs of points of a 3D space can be noticeably reduced and a speed can be remarkably enhanced.

Real-time 3D human object reconstruction apparatus and method based on monocular color image

There is provided a self-directed visual intelligence system, The self-directed visual intelligence system according to an embodiment prepares data necessary for training a visual intelligence model when a change in a visual context of a real world is recognized, configures a visual intelligence model and configures training data of the visual intelligence model, based on the changed visual context of the real world, trains the configured visual intelligence model with the training data, and evaluates performance of the trained visual intelligence model. Accordingly, the visual intelligence model is corrected/improved in a self-directed way according to a change in a visual context of a real world, and is grown/advanced by itself, so that performance of the visual intelligence model is maintained in a best state even in response to any change in the context of the real world.

Self-directed visual intelligence system

A method and an apparatus for detecting a lane is provided. The lane detection apparatus according to an embodiment includes: an acquisition unit configured to acquire a front image of a vehicle; and a processor configured to input the image acquired through the acquisition unit to an AI model, and to detect information of a lane on a road, and the AI model is trained to detect lane information that is expressed in a plane form from an input image. Accordingly, data imbalance between a lane area and a non-lane area can be solved by using the AI model which learns/predicts lane information that is expressed in a plane form, not in a segment form such as a straight line or curved line.

Image-based lane detection and ego-lane recognition method and apparatus

An endoscopic stereo matching method and apparatus using a direct attenuation model is provided. A method for generating a depth image according to an embodiment includes: generating a stereo image; and estimating a depth image from the stereo image based on an attenuation trend of light of an illumination used to generate the stereo image. Accordingly, a dense depth image can be obtained by using images obtained from a capsule endoscope, and thus the geometric structure of the inside of the GI tract can be estimated.

Growing community of inventors

Sejong-si, South Korea

Ju Hong Yoon