스테레오 영상처리 기반의 3차원 객체 검출을 위한 3차원 포인트 필터링 알고리즘

Abstract

Unlike LIDAR-based 3D object detection algorithms, stereo-based 3D object detection algorithms have low performance. The main reason for this problem is the low accuracy of the 3D information predicted from stereo image processing. Inaccurate 3D information distorts the 3D shape of an object. Therefore, this study aims to improve the performance of the stereo-based 3D object detection algorithms by proposing a filtering algorithm that can filter out inaccurate 3D information. The filtering algorithm uses a 3D offset, which is the distance between a 3D point on an object and the center of gravity of the object. Since the object size is limited, the 3D offset length of the points constituting the object is always smaller than the object size itself. However, there is a case where the 3D offset length of inaccurate 3D information is larger than the object size. The proposed filtering algorithm filters out inaccurate 3D information to address this issue. This study experimentally proves that the filtering algorithm is effective in enhancing the stereo-based 3D object detection performance.