为什么我们需要一个粗量化器？ [英] Why we need a coarse quantizer?

问题描述

在最近邻搜索的产品量化中，涉及到第IV.A节，它说他们会使用一个粗略的量化器（我们感觉到它只是一个更小的产品量化器，较小的wrt k 的质心）。

我真的不明白为什么这有助于搜索过程，原因可能是我觉得我没有得到他们使用的方式。

解决方案

如非排除性搜索部分所述，

产品量化器近似最近邻搜索
很快，大大降低了存储描述符的
的内存需求。

然而，搜索是穷尽的。

粗量化器是非详尽的搜索。它首先检索候选集，然后根据PQ在候选集中搜索最近的邻居。因此，IMO的性能在很大程度上取决于粗略量化器的性能。如果候选人集合首先不包含一些真正的最近邻居，那么我们不能在随后的PQ步骤中得到它们。

而且，是ANN的基本算法之一，它不必与PQ一起使用。

In Product Quantization for Nearest Neighbor Search, when it comes to section IV.A, it says they they will use a coarse quantizer too (which they way I feel it, is just a really smaller product quantizer, smaller w.r.t. k, the number of centroids).

I don't really get why this helps the search procedure and the cause might be that I think I don't get the way they use it. Any ides please?

解决方案

As mentioned in the NON EXHAUSTIVE SEARCH section,

Approximate nearest neighbor search with product quantizers is fast and reduces significantly the memory requirements for storing the descriptors.

Nevertheless, the search is exhaustive.

The coarse quantizer is for non-exhaustive search. It retrieves a candidate set first, then searches within the candidate set for nearest neighbors based on PQ.

Thus IMO the performance depends largely on the performance of the coarse quantizer. If the candidate set does not contain some the true nearest neighbors in the first place, we can not get them in the subsequent PQ step either.

And afaik the coarse quantizer thing is one of the basic algorithms for ANN, it doesn't have to be used together with PQ.

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