BINK: Biological binary keypoint descriptor.

Learning robust keypoint descriptors has become an active research area in the past decade. Matching local features is not only important for computational applications, but may also play an important role in early biological vision for disparity and motion processing. Although there were already some floating-point descriptors like SIFT and SURF that can yield high matching rates, the need for better and faster descriptors for real-time applications and embedded devices with low computational power led to the development of binary descriptors, which are usually much faster to compute and to match. Most of these descriptors are based on purely computational methods. The few descriptors that take some inspiration from biological systems are still lagging behind in terms of performance. In this paper, we propose a new biologically inspired binary keypoint descriptor: BINK. Built on responses of cortical V1 cells, it significantly outperforms the other biologically inspired descriptors. The new descriptor can be easily integrated with a V1-based keypoint detector that we previously developed for real-time applications.

Development and Testing of a Dual Accelerometer Vector Sensor for AUV Acoustic Surveys.

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper.