A disparity energy model improved by line, edge and keypoint correspondences

Disparity energy models (DEMs) estimate local depth information on the basis ofVl complex cells. Our recent DEM (Martins et al, 2011 ISSPlT261-266) employs a population code. Once the population's cells have been trained with randorn-dot stereograms, it is applied at all retinotopic positions in the visual field. Despite producing good results in textured regions, the model needs to be made more precise, especially at depth transitions.

Brightness perception: one simple model explaines most if not all effects

Few models can explain Mach bands (Pessoa, 1996 Vision Research 36 3205-3227) . Our own employs multiscale line and edge coding by simple and complex cells. Lines are interpreted by Gaussian functions, edges by bipolar, Gaussian-truncated errorfunctions. Widths of these functions are coupled to the scales of the underlying cells and the amplitudes are determined by their responses.

Improved line/edge detection and visual reconstruction

Lines and edges provide important information for object categorization and recognition. In addition, one brightness model is based on a symbolic interpretation of the cortical multi-scale line/edge representation. In this paper we present an improved scheme for line/edge extraction from simple and complex cells and we illustrate the multi-scale representation. This representation can be used for visual reconstruction, but also for nonphotorealistic rendering. Together with keypoints and a new model of disparity estimation, a 3D wireframe representation of e.g. faces can be obtained in the future.

A vision fronted with a new disparity model

We are developing a frontend that is based on the image representation in the visual cortex and plausible processing schemes. This frontend consists of multiscale line/edge and keypoint (vertex) detection, using models of simple, complex and end-stopped cells. This frontend is being extended by a new disparity model. Assuming that there is no neural inverse tangent operator, we do not exploit Gabor phase information. Instead, we directly use simple cell (Gabor) responses at positions where lines and edges are detected.

Disparity energy model with keypoint disparity validation

A biological disparity energy model can estimate local depth information by using a population of V1 complex cells. Instead of applying an analytical model which explicitly involves cell parameters like spatial frequency, orientation, binocular phase and position difference, we developed a model which only involves the cells’ responses, such that disparity can be extracted from a population code, using only a set of previously trained cells with random-dot stereograms of uniform disparity. Despite good results in smooth regions, the model needs complementary processing, notably at depth transitions. We therefore introduce a new model to extract disparity at keypoints such as edge junctions, line endings and points with large curvature. Responses of end-stopped cells serve to detect keypoints, and those of simple cells are used to detect orientations of their underlying line and edge structures. Annotated keypoints are then used in the leftright matching process, with a hierarchical, multi-scale tree structure and a saliency map to segregate disparity. By combining both models we can (re)define depth transitions and regions where the disparity energy model is less accurate.

Comparison of on-line learning algorithms for RBF models in greenhouse environmental control problems

The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

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.

Species and size selectivity in a Portuguese multispecies artisanal long-line fishery

The species and size selectivity of long-lines using small hooks were studied off the south coast of Portugal using ''Mustad'' brand round bent, flatted sea hooks (Quality 2316 DT) numbers 15, 13, and 11 baited with razor shell clam (Ei-isis siliqua). Hook numbers 13 and 11 are 49 and 109% larger respectively than number 15 hooks in terms of overall size (maximum width x maximum length). A total of 39 900 hooks were fished in 45 sets and 35 species of fish and cephalopods were caught. As a group, 13 species of sea breams (Sparidae) dominated the catch by numbers (58%) and weight (73%). Six species of sea breams, along with the greater weever fish (Trachinus draco) accounted for 81% of the total catch by weight, with the common or white sea bream (Diplodus sargus) bring the most important (29%). Catch size distributions by hook size were, in general, highly overlapped for all species and hook size had little apparent effect on minimum size at capture. All hooks caught a wide range of sizes per species, but the catch rate (number of fish per 100 hooks) was significantly lower for the largest hook. Except for the black sea bream (Spondyliosoma cantharus), capture of illegally sized or immature fish was minimal. Small increases in average size with hook size were evident for four species: Diplodus sargus, D. vulgaris, Lithognathus mormyrus and Serranus cabrilla. No differences in size selectivity were detected for Boops boops, D. annularis, Spondyliosoma cantharus and Trachinus draco. A skew-normal model adequately described differences in size selectivity in five of six species. (C) 1996 International Council for the Exploration of the Sea