On the Completeness of Coding with Image Features
On the Completeness of Coding with Image Features
复制标题
论图像特征编码的完备性
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
F. Schindler
中科院分区：
文献类型：
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作者：
W. Förstner;Timo Dickscheid;F. Schindler
我们提出了一种从图像编码角度衡量局部特征提取完整性的方案。完整性在这里被认为是由特征对相关图像信息的良好覆盖。由于每个功能需要一定数量的位，这是代表某一子区域的图像，我们解释的覆盖范围作为一个稀疏编码方案。因此，该度量基于图像域上的两个密度的比较：基于局部图像统计的熵密度pH（x），以及从每个特定的局部特征集合直接计算的特征编码密度pc（x）。受JPEG中的编码方案的启发，熵分布以统计上合理的方式从每个像素位置周围的局部补丁的功率谱导出。由于用于编码图像和用局部特征表示图像的比特总数可能不同，我们通过pH（x）和pc（x）之间的Hellinger距离来衡量不完整性。我们将推导出一个程序来测量可能混合的局部特征集的不完整性，并使用一些最流行的区域和关键点检测器（包括Lowe，MSER和最近发表的SFOP检测器）在标准数据集上显示结果。此外，我们将得出一些关于检测器互补性的有趣结论。
We present a scheme for measuring completeness of local feature extraction in terms of image coding. Completeness is here considered as good coverage of relevant image information by the features. As each feature requires a certain number of bits which are representative for a certain subregion of the image, we interpret the coverage as a sparse coding scheme. The measure is therefore based on a comparison of two densities over the image domain: An entropy density pH(x) based on local image statistics, and a feature coding density pc(x) which is directly computed from each particular set of local features. Motivated by the coding scheme in JPEG, the entropy distribution is derived from the power spectrum of local patches around each pixel position in a statistically sound manner. As the total number of bits for coding the image and for representing it with local features may be different, we measure incompleteness by the Hellinger distance between pH(x) and pc(x). We will derive a procedure for measuring incompleteness of possibly mixed sets of local features and show results on standard datasets using some of the most popular region and keypoint detectors, including Lowe, MSER and the recently published SFOP detectors. Furthermore, we will draw some interesting conclusions about the complementarity of detectors.