Abstract:
Disclosed herein are an object recognition apparatus of an automated driving system using error removal based on object classification and a method using the same. The object recognition method is configured to train a multi-object classification model based on deep learning using training data including a data set corresponding to a noise class, into which a false-positive object is classified, among classes classified by the types of objects, to acquire a point cloud and image data respectively using a LiDAR sensor and a camera provided in an autonomous vehicle, to extract a crop image, corresponding to at least one object recognized based on the point cloud, from the image data and input the same to the multi-object classification model, and to remove a false-positive object classified into the noise class, among the at least one object, by the multi-object classification model.
Abstract:
An apparatus for recognizing a user's posture in a horse-riding simulator, the apparatus comprising: a standard posture model generation module configured to find out a standard posture model by selecting feature points from an expert database, and generate the standard posture model; and a posture recognizing module configured to obtain a user's posture from the horse-riding simulator, recognize a user's horse-riding posture by matching the obtained user's posture with the standard posture model generated in the standard posture model generation module, and suggest a standard posture model appropriate for a user's level.
Abstract:
An apparatus for recognizing a user's posture in a horse-riding simulator, the apparatus comprising: a standard posture model generation module configured to find out a standard posture model by selecting feature points from an expert database, and generate the standard posture model; and a posture recognizing module configured to obtain a user's posture from the horse-riding simulator, recognize a user's horse-riding posture by matching the obtained user's posture with the standard posture model generated in the standard posture model generation module, and suggest a standard posture model appropriate for a user's level.