3D scene reconstruction: why, when, and how?
Jonah C. McBride, Magnús Snorrason, Thomas Goodsell, Ross Eaton, Mark R. Stevens
- 发表年份
- 2004
- 引用次数
- 3
摘要
Mobile robot designers frequently look to computer vision to solve navigation, obstacle avoidance, and object detection problems. Potential solutions using low-cost video cameras are particularly alluring. Recent results in 3D scene reconstruction from a single moving camera seem particularly relevant, but robot designers who attempt to use such 3D techniques have uncovered a variety of practical concerns. We present lessons-learned from developing a single-camera 3D scene reconstruction system that provides both a real-time camera motion estimate and a rough model of major 3D structures in the robot’s vicinity. Our objective is to use the motion estimate to supplement GPS (indoors in particular) and to use the model to provide guidance for further vision processing (look for signs on <i>walls</i>, obstacles on the <i>ground</i>, etc.). The computational geometry involved is closely related to traditional two-camera stereo, however a number of degenerate cases exist. We also demonstrate how SFM can use used to improve the performance of two specific robot navigation tasks.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002