Bag-of-binary-features for fast image representation

Abstract

The possibility of integrating binary features into the bag-of-features (BoFs) model is explored. The set of binary features extracted from an image are packed into a single vector form, to yield the bag-of-binary-features (BoBFs). The efficient BoBF feature extraction and quantisation provide fast image representation. The trade-off between accuracy and efficiency in BoBF compared with BoF is investigated through image retrieval tasks. Experimental results demonstrate that BoBF is a competitive alternative to BoF when the run-time efficiency is critical.