Memory-based self-localization using omnidirectional images
Memory-based self-localization using omnidirectional images
复制标题
使用全向图像的基于记忆的自定位
DOI：
10.1109/icpr.1998.712078
复制
发表时间：
1998
期刊：
影响因子：
--
通讯作者：
H. Takemura
中科院分区：
文献类型：
--
作者：
H. Iwasa;N. Aihara;N. Yokoya;H. Takemura
本文提出了一种新的自定位方法，使用全方位图像传感器，可以观察周围环境的360度视图。该方法通过从观察到的全向图像生成自相关图像来提取对于传感器的位置相同并且对于传感器的旋转不变的信息。通过评估观测图像的自相关图像与存储的自相关图像之间的相似性来估计传感器的位置。自相关图像的相似性评估在低维特征空间与存储的自相关图像生成。我们已经进行了实验与真实的图像，并检查所提出的方法的性能。结果表明，准确和鲁棒的估计传感器的位置是可能的，与我们的方法。
This paper proposes a new self-localization method using an omnidirectional image sensor which can observe a surrounding environment with 360-degree of view. The method extracts information which is identical for the position of a sensor and invariant against the rotation of the sensor by generating an autocorrelation image from an observed omnidirectional image. The location of the sensor is estimated by evaluating the similarity among the autocorrelation image of an observed image and stored autocorrelation images. The similarity of autocorrelation images is evaluated in low dimensional eigenspaces generated with stored autocorrelation images. We have conducted experiments with real images and examined the performance of the proposed method. The results show that accurate and robust estimation of the sensor's position is possible with our method.