Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-Scale Image Retrieval

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertic...

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