Robust localization using panoramic view-based recognition
M Jogan, A Leonardis - Proceedings 15th International …, 2000 - ieeexplore.ieee.org
The results of earlier studies on the possibility of spatial localization from panoramic images
have shown good prospects for view-based methods. The major advantages of these
methods are a wide field-of-view, capability of modeling cluttered environments, and
flexibility in the learning phase. The redundant information captured in similar views is
efficiently handled by the eigenspace approach. However, the standard approaches are
sensitive to noise and occlusion. We present a method of view-based localization in a robust …
have shown good prospects for view-based methods. The major advantages of these
methods are a wide field-of-view, capability of modeling cluttered environments, and
flexibility in the learning phase. The redundant information captured in similar views is
efficiently handled by the eigenspace approach. However, the standard approaches are
sensitive to noise and occlusion. We present a method of view-based localization in a robust …
Robust Localization Using Panoramic View-Based Recognition
A Leonardis - Proceedings of the International Conference on Pattern …, 2000 - dl.acm.org
The results of recent studies on the possibility of spatial localization from panoramic images
have shown good prospects for view-based methods. The major advantages of these
methods are a wide field-of-view, capability of modeling cluttered environments, and
flexibility in the learning phase. The redundant information captured in similar views is
efficiently handled by the eigenspace approach. However, the standard approaches are
sensitive to noise and occlusion. In this paper, we present a method of view-based …
have shown good prospects for view-based methods. The major advantages of these
methods are a wide field-of-view, capability of modeling cluttered environments, and
flexibility in the learning phase. The redundant information captured in similar views is
efficiently handled by the eigenspace approach. However, the standard approaches are
sensitive to noise and occlusion. In this paper, we present a method of view-based …
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