AVLAD: Optimizing the VLAD Image Signature for Specific Feature Descriptors
Recent works on content-based image retrieval have successfully used the Vector of Locally Aggregated Descriptors (VLAD) as a compact image signature. In this paper, we improve the VLAD signature by tailoring the VLAD representation to the specific properties of the visual feature descriptors. We combine this improvement with the recently proposed hierarchical VLAD approach and demonstrate the effectiveness of this extension for the two well-known feature descriptors SIFT and SURF. Furthermore, we investigate how to efficiently reduce the dimensionality of the resulting representation using different unsupervised dimensionality reduction techniques.