본문 바로가기
  • Home

Recognition and Modeling of 3D Environment based on Local Invariant Features

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2006, 11(3), pp.31-40
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Daesik Jang 1

1군산대학교

Candidate

ABSTRACT

This paper presents a novel approach to real-time recognition of 3D environment and objects for various applications such as intelligent robots, intelligent vehicles, intelligent buildings,..etc. First, we establish the three fundamental principles that humans use for recognizing and interacting with the environment. These principles have led to the development of an integrated approach to real-time 3D recognition and modeling, as follows: 1) It starts with a rapid but approximate characterization of the geometric configuration of workspace by identifying global plane features. 2) It quickly recognizes known objects in environment and replaces them by their models in database based on 3D registration. 3) It models the geometric details on the fly adaptively to the need of the given task based on a multi-resolution octree representation. SIFT features with their 3D position data, referred to here as stereo-sis SIFT, are used extensively, together with point clouds, for fast extraction of global plane features, for fast recognition of objects, for fast registration of scenes, as well as for overcoming incomplete and noisy nature of point clouds.

Citation status

* References for papers published after 2022 are currently being built.