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An Effective Binocular Vision-based Sensing Approach for IAUV

机译:一种有效的基于双目视觉的IAUV传感方法

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IAUV (Intervention Class AUV) is a challenging field for AUV's new development, suitable for underwater manipulation with certain target in limited environment. Visual sensor makes vivid description of the scene, so could be helpful in solving key issues in IAUV autonomous manipulation. Existing visual sensing approaches for IAUV are mostly applicable for target with prior knowledge and may be lack of robustness and flexibility. Here a binocular sensing approach is proposed using texture-control based pyramid NCC (normalized cross correlation) to extract target region or outline, and target range. Making use of the texture difference between foreground and background, the target was extracted by texture control. Regions with low texture level would be discarded, so time was saved and matching efficiency improved. A series of other methods were also used to further quicken the approach and improve its accuracy. Its overall capabilities, especially the real-time performance, were quantificationally analysed through repeated experiments in lab. Finally the approach was validated in a water tank with both clear and turbid water.
机译:IAUV(介入类AUV)是AUV新开发的一个充满挑战的领域,适用于在有限环境中对某些目标进行水下操纵。视觉传感器可以生动描述场景,因此有助于解决IAUV自主操纵中的关键问题。现有的IAUV视觉传感方法大多适用于具有先验知识的目标,并且可能缺乏鲁棒性和灵活性。在这里,提出了一种双目传感方法,它使用基于纹理控制的金字塔NCC(归一化互相关)来提取目标区域或轮廓以及目标范围。利用前景和背景之间的纹理差异,通过纹理控制提取目标。低纹理级别的区域将被丢弃,从而节省了时间并提高了匹配效率。还使用了一系列其他方法来进一步加快该方法并提高其准确性。通过在实验室中进行重复实验,定量分析了其总体功能,尤其是实时性能。最后,该方法在装有清水和浑浊水的水箱中得到了验证。

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