Biologically Inspired Computer Vision

Expériences autour de la perception de la forme en art et science

Meetup Art et Neurosciences Quoi Meetup Art et Neurosciences Qui Association NeuroNautes Quand 25 Janvier 2018 Où Salle des voutes campus Saint Charles Support visuel https://laurentperrinet.github.io/sciblog/files/2018-01-25_meetup-neuronautes.html (notes: la présentation peut mettre un certain temps à charger. Une fois que le titre apparait, appuyer sur la touche “F” pour mettre en plein écran)

M2APix: a bio-inspired auto-adaptive visual sensor for robust ground height estimation

This paper presents for the first time the embedded stand-alone version of the bio-inspired M2APix (Michaelis-Menten auto-adaptive pixels) sensor as a ventral optic flow sensor to endow glider-type unmanned aerial vehicles with autonomous landing …

Tutorial: Sparse optimization in neural computations

Differential response of the retinal neural code with respect to the sparseness of natural images

Biologically-inspired characterization of sparseness in natural images

Categorization of microscopy images using a biologically inspired edge co-occurrences descriptor

See a followup in Perrinet and Bednar, 2015

2016-10-26 : EUVIP BICV

EUVIP Session 7: Biologically Inspired Computer Vision (Special Session).

Biologically-inspired characterization of sparseness in natural images

Natural images follow statistics inherited by the structure of our physical (visual) environment. In particular, a prominent facet of this structure is that images can be described by a relatively sparse number of features. We designed a sparse …

Introduction

This is the introductory chapter of the book, which serves as a comprehensive but rigorous reference in the area of biologically inspired computer vision modeling. Biological vision shows excellence in terms of performance and robustness. …

Sparse Models for Computer Vision

The representation of images in the brain is known to be sparse. That is, as neural activity is recorded in a visual area ---for instance the primary visual cortex of primates--- only a few neurons are active at a given time with respect to the whole …

Visual motion processing and human tracking behavior

Biologically Inspired Computer Vision

As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and volume, the need to process and interpret all the data has made image processing and computer vision also increasingly …

Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences

Oriented edges in images of natural scenes tend to be aligned in co-linear or co-circular arrangements, with lines and smooth curves more common than other possible arrangements of edges (the good continuation law of Gestalt psychology). The visual …

Edge co-occurrences can account for rapid categorization of natural versus animal images

Making a judgment about the semantic category of a visual scene, such as whether it contains an animal, is typically assumed to involve high-level associative brain areas. Previous explanations require progressively analyzing the scene hierarchically …

Active inference, eye movements and oculomotor delays

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference …

Edge co-occurrences are sufficient to categorize natural versus animal images

Analysis and interpretation of a visual scene to extract its category, such as whether it contains an animal, is typically assumed to involve higher-level associative brain areas. Previous proposals have been based on a series of processing steps …

Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network

see Kaplan and al, 2014

Edge co-occurrences and categorizing natural images

See a followup in Perrinet and Bednar, 2015

Advances in Texture Analysis for Emphysema Classification

In recent years, with the advent of High-resolution Computed Tomography (HRCT), there has been an increased interest for diagnosing Chronic Obstructive Pulmonary Disease (COPD), which is commonly presented as emphysema. Since low-attenuation areas in …

Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images

If modern computers are sometimes superior to cognition in some specialized tasks such as playing chess or browsing a large database, they can't beat the efficiency of biological vision for such simple tasks as recognizing a relative or following an …

Self-Invertible 2D Log-Gabor Wavelets

Meanwhile biorthogonal wavelets got a very popular image processing tool, alternative multiresolution transforms have been proposed for solving some of their drawbacks, namely the poor selectivity in orientation and the lack of translation in- …

Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas

Sparse Gabor wavelets by local operations

Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, but most of them are limited by a heavy computationalcost and by difficulties to find the optimal solutions. We …

Efficient representation of natural images using local cooperation

Low-level perceptual computations may be understood in terms of efficient codes (Simoncelli and Olshausen, 2001, Annual Review of Neuroscience 24 1193-216). Following this argument, we explore models of representation for natural static images as a …

Coding static natural images using spiking event times: do neurons cooperate?

To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of visual processing for static images. We will first present the retinal model which was introduced by Van Rullen and …