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A Graph Theoretic Approach to Direct Processing of Sparse Unwarped Panoramic Images

机译:一种直接处理稀疏未使用的全景图像的图形理论方法

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The use of omnidirectional cameras has had a significant impact on the success of vision systems for video surveillance and autonomous robot navigation. Typically images obtained from such cameras are transformed to sparse panoramic images that are interpolated prior to low level image processing. We present a graph theoretic approach that enables image processing techniques, principally feature extraction, to be performed directly on sparse panoramic images, avoiding the need for image interpolation. We thus aim to reduce the computational overheads of processing images arising from omnidirectional cameras, whilst retaining accuracy sufficient for application to real-time robot vision
机译:全向相机的使用对视频监控和自治机器人导航的视觉系统的成功产生了重大影响。 通常,从这种相机获得的图像被转换为在低电平图像处理之前内插的稀疏全景图像。 我们介绍了一种图形理论方法,其能够直接在稀疏的全景图像上执行图像处理技术,主要是特征提取,避免对图像插值的需要。 因此,我们旨在减少从全向相机产生的图像的计算开销,同时保持足以应用于实时机器人视觉的精度

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