1,721,167 research outputs found
A Computational Model for the Neural Representation and Estimation of the Binocular Vector Disparity from Convergent Stereo Image Pairs
No full textThe depth cue is a fundamental piece of information for artificial and living beings who interact with the surrounding environment in order to handle objects and to avoid obstacles: in such situations, the disparity patterns, which arise when agents fixate objects, are vector fields. We propose a biologically-inspired computational model to estimate dense horizontal and vertical disparity maps by exploiting the cortical paradigms of the primate visual system: in particular, we aim to model the disparity sensitivity of the V1-MT visual pathway. The proposed model is based on a first processing stage composed of a bank of spatial band-pass filters and a static nonlinearity, mimicking complex binocular cells. Then, subsequent pooling stages and decoding strategies allow the model to estimate the vector disparity, after having represented it as a population of MT-like units. We assess the proposed model by using standard benchmarking stereo images, the Middlebury dataset, and specific stereo images that have horizontal and vertical disparities, which characterize the stimuli produced by active vision systems. Moreover, we systemically analyze how the different processing stages affect the model performance, and we discuss their implications for the neural modeling
Enhanced Log-Polar implementation of Blind-Spot model
No full textSviluppo di un simulatore del modello spazio variante di acquisizione di immagini "Log-polar Blind
Spot Model" presentato nel lavoro in conferenza di M. Chessa, S.P. Sabatini, F. Solari, F. Tatti
dal titolo "A Quantitative Comparison of Speed and Reliability for Log-Polar Mapping
Techniques". Tale simulatore (realizzato da M. Chessa e F. Solari) e` disponibile nella libreria di
Computer Vision OpenCV (http://opencv.org/).Enhanced Log-Polar implementation (that uses Blind-Spot model) has been contributed by Fabio Solari and Manuela Chessa, see http://code.opencv.org/projects/opencv/wiki/2012 ( opencv/contrib/contrib.hpp, LogPolar_* classes and opencv/samples/cpp/logpolar_bsm.cpp sample)
FFV1MT: A V1-MT feedforward architecture for optical flow estimation
No full textA neural feed-forward model composed of two layers that mimic the V1-MT primary motion pathway, derived from previous works by Heeger and Simoncelli. Reference: Solari F, Chessa M, Medathati NVK, Kornprobst P (2015) What can we expect from a V1-MT feedforward architecture for optical flow estimation? Signal Processing: Image Communicatio
Análisis de la inversión en un monitor de rendimiento y una fertilizadora de dosis variable para realizar agricultura de precisión en la pampa ondulada
Full text linkFil: Muschietti Piana, María del Pilar. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Fertilidad y Fertilizantes. Buenos Aires, Argentina.Fil: Solari, Fabio Adrián. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Topografía. Buenos Aires, Argentina.tbls., gráfs
Emergence of Motion-in-depth Selectivity in the Visual Cortex through Linear Combination of Binocular Energy Complex Cells with Different Ocular Dominance
No full text
Emergence of oscillations and spatio-temporal coherence states in a continuum-model of excitatory and inhibitory neurons
No full textA neural field model of the reaction-diffusion type for the emergence of oscillatory phenomena in visual cortices is proposed. To investigate the joint spatio-temporal oscillatory dynamics in a continuous distribution of excitatory and inhibitory neurons, the coupling among oscillators is modelled as a diffusion process, combined with non-linear point interactions. The model exhibits cooperative activation properties in both time and space, by reacting to volleys of activations at multiple cortical sites with ordered spatio-temporal oscillatory states, similar to those found in the physiological experiments on slow-wave field potentials. The possible use of the resulting spatial distributions of coherent states, as a flexible medium to establish feature association, is discussed
Computational and implementation strategies for smart visual sensors in automotive applications.
No full textFast space-variant image analysis through steerable Gabor-like filters
No full textThe log-polar image geometry, first introduced to model the space-variant topology of the human retina receptors in relation to the data compression it achieves, has become popular in the active vision community for the important algorithmic benefits it provides. Despite these advantages, foveated sensing has not been widely used due to the lack of specific image processing tools. We demonstrate that it is possible to perform multichannel space-variant image processing with high computational efficiency through Gabor-like steerable kernels in the cortical domain
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