Electronics and Telecommunications Research Institute

Yun Won Choi

Jang Woon Baek

Yun Su Chung

Kwang Yong Kim

Kil Taek Lim

Byung Gil Han

Joon Goo Lee

Provided is a method of creating a local database for local optimization of an object detector based on a deep neural network. The method includes performing preprocessing on an image extracted from real-time collected or pre-collected images from an edge device, modeling a static background image based on the image received through the pre-processing unit and calculating a difference image between a current input image and a background model to model a dynamic foreground image, detecting an object image from the image based on a training model, and creating a local database based on the background image, the foreground image synthesized with the background image, and the object image synthesized with the background image.

System for local optimization of object detector based on deep neural network and method of creating local database therefor

Provided is a method of separating a foreground and a background by extracting a depth image through a stereo camera, generating an occupancy grid map on the basis of the depth image, predicting a free space, and computing a membership value, the method including setting a threshold value of a foreground object existing in a free space boundary region of the predicted free space, determining whether the membership value reaches the threshold value of the foreground object while the membership value is computed, terminating the computing of the membership value when it is determined that the membership value being computed reaches the threshold value of the foreground object in the determining, and separating a foreground and a background through the computed membership value.

Method and apparatus for accelerating foreground and background separation in object detection using stereo camera

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Daegu, South Korea

Yun Won Choi