BIMP: A real-time biological model of multi-scale keypoint detection in V1

We present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation. (C) 2014 Elsevier B.V. All rights reserved.

The perception of woman on the example of the Odyssey of Homer and its english translation by James Huddleston and portuguese translation by Frederico Lourenço

Dissertação de mestrado, Estudos Literários e Artísticos, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2015

Second home tourism and governance: the perception of stakeholders in the Algarve

Dissertação de Mestrado, Economia do Turismo e Desenvolvimento Regional, Faculdade de Economia, Universidade do Algarve, 2016

Trophic signatures of small-scale fishing gears: implications for conservation and management

We quantified the ecosystem effects of small-scale gears operating in southern European waters (Portugal, Spain, Greece), based on a widely accepted ecosystem measure and indicator, the trophic level (TL). We used data from experimental fishing trials during 1997 to 2000. We studied a wide range of gear types and sizes: (1) gill nets of 8 mesh sizes, ranging from 44 to 80 mm; (2) trammel nets of 9 inner panel mesh sizes, ranging from 40 to 140 mm; and (3) longlines of 8 hook sizes, ranging from Nos. 15 (small) to 5 (large). We used the number of species caught per TL class for constructing trophic signatures (i.e. cumulative TL distributions), and estimated the TL at 25, 50 and 75% cumulative frequency (TL25, TL50, TL75) and the slopes using the logistic function. We also estimated the mean weighted TL of the catches (TLW). Our analyses showed that the TL characteristics of longlines varied much more than those of gill and trammel nets. The longlines of large hooks (Nos. 10, 9, 7, 5) were very TL selective, and their trophic signatures had very steep slopes, the highest mean TL50 values, very narrow mean TL25 to TL75 ranges and mean TLW > 4. In addition, the mean number of TL classes exploited was smaller and the mean TL50 and TLW were larger for the longlines of small hooks (Nos. 15, 13, 12, 11) in Greek than in Portuguese waters. Trammel and gill nets caught more TL classes, and the mean slopes of their trophic signatures were significantly smaller than those of longlines as a group. In addition, the mean number of TL classes exploited, the mean TL50 and the TLW of gill nets were significantly smaller than those of trammel nets. We attribute the differences between longlines of small hooks to bait type, and the differences between all gear types to their characteristic species and size-selectivity patterns. Finally, we showed how the slope and the TL50 Of the trophic signatures can be used to characterise different gears along the ecologically 'unsustainable-sustainable' continuum.

Looking through the eyes of the painter: from visual perception to non-photorealistic rendering

In this paper we present a brief overview of the processing in the primary visual cortex, the multi-scale line/edge and keypoint representations, and a model of brightness perception. This model, which is being extended from 1D to 2D, is based on a symbolic line and edge interpretation: lines are represented by scaled Gaussians and edges by scaled, Gaussian-windowed error functions. We show that this model, in combination with standard techniques from graphics, provides a very fertile basis for non-photorealistic image rendering.

Broad-scale mapping of seafloor habitats in the north-east Atlantic using existing environmental data

If marine management policies and actions are to achieve long-term sustainable use and management of the marine environment and its resources, they need to be informed by data giving the spatial distribution of seafloor habitats over large areas. Broad-scale seafloor habitat mapping is an approachwhich has the benefit of producing maps covering large extents at a reasonable cost. This approach was first investigated by Roff et al. (2003), who, acknowledging that benthic communities are strongly influenced by the physical characteristics of the seafloor, proposed overlaying mapped physical variables using a geographic information system (GIS) to produce an integrated map of the physical characteristics of the seafloor. In Europe the method was adapted to the marine section of the EUNIS (European Nature Information System) classification of habitat types under the MESH project, andwas applied at an operational level in 2011 under the EUSeaMap project. The present study compiled GIS layers for fundamental physical parameters in the northeast Atlantic, including (i) bathymetry, (ii) substrate type, (iii) light penetration depth and (iv) exposure to near-seafloor currents andwave action. Based on analyses of biological occurrences, significant thresholds were fine-tuned for each of the abiotic layers and later used in multi-criteria raster algebra for the integration of the layers into a seafloor habitat map. The final result was a harmonised broad-scale seafloor habitat map with a 250 m pixel size covering four extensive areas, i.e. Ireland, the Bay of Biscay, the Iberian Peninsula and the Azores. The map provided the first comprehensive perception of habitat spatial distribution for the Iberian Peninsula and the Azores, and fed into the initiative for a pan- European map initiated by the EUSeaMap project for Baltic, North, Celtic and Mediterranean seas.