Low bitrate coding schemes for local image descriptors

Efficient coding of local image descriptors is of paramount importance when they need to be transmitted to a remote destination on bandwidth constrained networks. This is a case that arises, e.g., in mobile visual search and visual wireless sensor networks. In this work we consider SURF, a popular descriptor suitable for low-complexity devices, and we provide a comparative study of lossy coding schemes operating at low bitrate (e.g., less than 128 bits / descriptor). Our investigation covers schemes that address both intra- and inter-descriptor redundancy, including methods that have not been tested before in this context, e.g., sparse coding, lifting-based coding on trees, and hybrid intra and inter-descriptor coding. The experimental evaluation is carried out on two publicly available datasets, in terms of both rate-distortion and rate-accuracy, for the specific task of object recognition. Our results show that a rate saving of 15–30% can be achieved by exploiting intra-descriptor redundancy. On the other side, addressing inter-descriptor redundancy does not lead to substantial gains when applied alone, whereas it leads to marginal gains (up to 3%) when used in hybrid schemes jointly with intra-descriptor coding.