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A Distance-Computation-Free Search Scheme for Binary Code Databases

机译：二进制代码数据库的无距离计算搜索方案

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摘要

Recently, binary codes have been widely used in many multimedia applications to approximate high-dimensional multimedia features for practical similarity search due to the highly compact data representation and efficient distance computation. While the majority of the hashing methods aim at learning more accurate hash codes, only a few of them focus on indexing methods to accelerate the search for binary code databases. Among these indexing methods, most of them suffer from extremely high memory cost or extensive Hamming distance computations. In this paper, we propose a new Hamming distance search scheme for large scale binary code databases, which is free of Hamming distance computations to return the exact results. Without the necessity to compare database binary codes with queries, the search performance can be improved and databases can be externally maintained. More specifically, we adopt the inverted multi-index data structure to index binary codes. Importantly, the Hamming distance information embedded in the structure is utilized in the designed search scheme such that the verification of exact results no longer relies on Hamming distance computations. As a step further, we optimize the performance of the inverted multi-index structure by taking the code distributions among different bits into account for index construction. Empirical results on large-scale binary code databases demonstrate the superiority of our method over existing approaches in terms of both memory usage and search efficiency.
机译：近来，由于高度紧凑的数据表示和有效的距离计算，二进制代码已在许多多媒体应用中广泛用于逼近高维多媒体特征以进行实际相似性搜索。尽管大多数哈希方法旨在学习更准确的哈希码，但只有少数方法着重于索引方法以加快对二进制代码数据库的搜索。在这些索引方法中，大多数方法都具有极高的存储成本或大量的汉明距离计算。在本文中，我们为大型二进制代码数据库提出了一种新的汉明距离搜索方案，该方案无需进行汉明距离计算即可返回精确结果。无需将数据库二进制代码与查询进行比较，可以提高搜索性能，并且可以从外部维护数据库。更具体地说，我们采用反向多索引数据结构来索引二进制代码。重要的是，嵌入在结构中的汉明距离信息在设计的搜索方案中得到了利用，从而精确结果的验证不再依赖于汉明距离计算。更进一步，我们通过考虑不同位之间的代码分布来构建索引，从而优化了反向多索引结构的性能。大规模二进制代码数据库上的经验结果证明，就内存使用和搜索效率而言，我们的方法优于现有方法。

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