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David Berga; Xavier Otazu; Xose R. Fernandez-Vidal; Victor Leboran; Xose M. Pardo |
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Generating Synthetic Images for Visual Attention Modeling |
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2019 |
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Perception |
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PER |
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48 |
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99 |
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NEUROBIT; no menciona |
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Admin @ si @ BOF2019 |
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3309 |
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Author |
Arash Akbarinia; C. Alejandro Parraga |
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Title |
Feedback and Surround Modulated Boundary Detection |
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2018 |
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International Journal of Computer Vision |
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IJCV |
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126 |
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12 |
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1367–1380 |
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Boundary detection; Surround modulation; Biologically-inspired vision |
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Edges are key components of any visual scene to the extent that we can recognise objects merely by their silhouettes. The human visual system captures edge information through neurons in the visual cortex that are sensitive to both intensity discontinuities and particular orientations. The “classical approach” assumes that these cells are only responsive to the stimulus present within their receptive fields, however, recent studies demonstrate that surrounding regions and inter-areal feedback connections influence their responses significantly. In this work we propose a biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1). In our model we account for four kinds of receptive field surround, i.e. full, far, iso- and orthogonal-orientation, whose contributions are contrast-dependant. The output signal from V1 is pooled in its perpendicular direction by larger V2 neurons employing a contrast-variant centre-surround kernel. We further introduce a feedback connection from higher-level visual areas to the lower ones. The results of our model on three benchmark datasets show a big improvement compared to the current non-learning and biologically-inspired state-of-the-art algorithms while being competitive to the learning-based methods. |
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NEUROBIT; 600.068; 600.072 |
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Admin @ si @ AkP2018b |
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2991 |
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C. Alejandro Parraga |
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Title |
Colours and Colour Vision: An Introductory Survey |
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2017 |
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Perception |
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PER |
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46 |
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5 |
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640-641 |
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NEUROBIT; no menciona |
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Par2017 |
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3101 |
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Arash Akbarinia; C. Alejandro Parraga |
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Title |
Colour Constancy Beyond the Classical Receptive Field |
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2018 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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40 |
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9 |
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2081 - 2094 |
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The problem of removing illuminant variations to preserve the colours of objects (colour constancy) has already been solved by the human brain using mechanisms that rely largely on centre-surround computations of local contrast. In this paper we adopt some of these biological solutions described by long known physiological findings into a simple, fully automatic, functional model (termed Adaptive Surround Modulation or ASM). In ASM, the size of a visual neuron's receptive field (RF) as well as the relationship with its surround varies according to the local contrast within the stimulus, which in turn determines the nature of the centre-surround normalisation of cortical neurons higher up in the processing chain. We modelled colour constancy by means of two overlapping asymmetric Gaussian kernels whose sizes are adapted based on the contrast of the surround pixels, resembling the change of RF size. We simulated the contrast-dependent surround modulation by weighting the contribution of each Gaussian according to the centre-surround contrast. In the end, we obtained an estimation of the illuminant from the set of the most activated RFs' outputs. Our results on three single-illuminant and one multi-illuminant benchmark datasets show that ASM is highly competitive against the state-of-the-art and it even outperforms learning-based algorithms in one case. Moreover, the robustness of our model is more tangible if we consider that our results were obtained using the same parameters for all datasets, that is, mimicking how the human visual system operates. These results might provide an insight on how dynamical adaptation mechanisms contribute to make object's colours appear constant to us. |
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NEUROBIT; 600.068; 600.072 |
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Admin @ si @ AkP2018a |
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2990 |
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Xim Cerda-Company; Xavier Otazu |
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Title |
Color induction in equiluminant flashed stimuli |
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2019 |
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Journal of the Optical Society of America A |
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JOSA A |
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36 |
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1 |
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22-31 |
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Color induction is the influence of the surrounding color (inducer) on the perceived color of a central region. There are two different types of color induction: color contrast (the color of the central region shifts away from that of the inducer) and color assimilation (the color shifts towards the color of the inducer). Several studies on these effects have used uniform and striped surrounds, reporting color contrast and color assimilation, respectively. Other authors [J. Vis. 12(1), 22 (2012) [CrossRef] ] have studied color induction using flashed uniform surrounds, reporting that the contrast is higher for shorter flash duration. Extending their study, we present new psychophysical results using both flashed and static (i.e., non-flashed) equiluminant stimuli for both striped and uniform surrounds. Similarly to them, for uniform surround stimuli we observed color contrast, but we did not obtain the maximum contrast for the shortest (10 ms) flashed stimuli, but for 40 ms. We only observed this maximum contrast for red, green, and lime inducers, while for a purple inducer we obtained an asymptotic profile along the flash duration. For striped stimuli, we observed color assimilation only for the static (infinite flash duration) red–green surround inducers (red first inducer, green second inducer). For the other inducers’ configurations, we observed color contrast or no induction. Since other studies showed that non-equiluminant striped static stimuli induce color assimilation, our results also suggest that luminance differences could be a key factor to induce it. |
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NEUROBIT; 600.120; 600.128 |
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Admin @ si @ CeO2019 |
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3226 |
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