Bag of k-nearest visual words for hieroglyph retrieval

摘要

Hieroglyph retrieval has emerged as a tool to facilitate and support the cultural heritage preservation. For this task, hieroglyphs should be represented according its visual content. In the literature, the Bag of Visual Words (BoVW) model has been widely used for representing hieroglyphs with retrieval purposes. One crucial step in the BoVW model consists in replacing each local descriptor, obtained from a hieroglyph, by its nearest visual word in the vocabulary. However, it may result in similar local descriptors replaced by different visual words. Thus, the similarity of these local descriptors is lost. In this work, this problem is addressed by replacing each local descriptor by its k-nearest visual words in the vocabulary, instead of just one visual word (the nearest). Considering this multiple replacement, we introduce a hieroglyph representation that takes into account the frequency of the visual words and the co-occurrence of visual word pairs. Our experiments show that our proposed hieroglyph representation allows obtaining better retrieval results than those obtained by using state of the art representations.