Search

Structure-preserving image filtering is an image smoothing technique that aims to preserve prominent structures while removing unwanted details in natural images. However, relevant studies mainly focus on small variances/fluctuations suppression and are vulnerable to separate pixels connected by some low-contrast edges or cluster pixels which exhibit strong differences between neighbors in highly textured region. Inspired by the fact that the human visual system significantly outperforms manually designed operators in extracting meaningful structures from natural scenes, we present an efficient structure-preserving filtering method which integrates similarity, proximity and continuation principles of human perception to accomplish high-contrast details (textures/noises) smoothing. Additionally, a Liebig’s law of minimum-based distance transform is presented to seamlessly incorporate the three properties for the description of the filter kernel. Experiments demonstrate that our distance transform keeps a clustering-like manner of separating different image pixels and grouping similar ones with the awareness of structure. When integrating this affinity measure into the bilateral-filter-like framework, our method can efficiently remove high-contrast textures/noises while preserving major structures.

Due to the arbitrary scales, uncertain distributions of objects and cluttered background in natural scenes, uniformly detecting salient regions remains a challenge. This paper first proposes a Gestalt-grouping connectedness method based on path analysis to reflect the topological relationship between image pixels. Inspired by the Gestalt principles of feature grouping, we apply a smoothest path-based distance metric to capture the similarity, local proximity and global continuity between image pixels. The distance is small if the image pixels belong to the same visual region and large otherwise. To identify salient regions in natural images, we then propose a path-based background saliency model that integrates both the topological connectedness and appearance dissimilarity. Experimental results demonstrate the advantage of applying the path-based background saliency model in uniformly highlighting salient regions in images with complex backgrounds.

[ES] La memoria de trabajo (MT) nos permite mantener y manipular información cuando ya no está presente a los sentidos. Cuando los estímulos se muestran de forma secuencial se ha descrito la aparición de efectos de recencia (i.e. aquellos estímulos que se muestran en las últimas posiciones de la secuencia son retenidos en MT con mayor probabilidad). La hipótesis principal que subyace este estudio es que la atención visual modula la codificación de información visual durante la fase de estimulación de MT. Nuestros resultados muestran que el efecto de recencia surge incluso cuando los estímulos se muestran de forma simultánea, de modo que determinan qué estímulos entran y son mantenidos en MT. Este efecto es consecuencia de la asignación de atención visual a los diferentes elementos durante la fase de estimulación de la tarea visual, ilustrando así el importante rol de la interrelación entre atención visual y MT., [EN] Working memory (WM) allows us to hold and manipulate information when it is no longer present to the physical senses. When stimuli are displayed sequentially, recency effects (i.e. stimuli presented later in the sequence are more likely held in WM) have been reported in visual WM. The main hypothesis that guides this study is that visual attention modulates the codification of visual information during the encoding phase of WM. Our results show that the recency effect emerges even when stimuli are shown simultaneously, thus affecting which stimuli enter and are maintained in WM. This effect emerges from the allocation of visual attention to the different items during the stimulation phase of the task, thus illustrating the important role of the interplay between visual attention and WM., Las autoras agradecen a Laura Portell su colaboración en el proyecto de investigación en el marco del cual contribuyó en el diseño del protocolo experimental de la tarea DMS. Esta investigación ha sido posible gracias a la financión recibida por parte Ministerio de Ciencia e Innovación a través del proyecto TIN2013-40630-R.

Vision is an active process in that detailed representations of our visual world are only built from actively scanning our eyes with a series of saccades and fixations. The process of actively scanning a visual scene while looking for something in a cluttered environment is known as visual search. The study of visual search processes not only offers a unique opportunity to gain fundamental insights into visual information processing in the human brain, but also opens new avenues to assess cognitive function. In this work, we show that it is possible to unveil the strategies pursued by subjects to solve visual tasks by investigating dynamical aspects inherent to eye-tracking data in a generalized N-dimensional feature domain.

In this article, a conceptual framework developed to acquire expert knowledge from eye-tracking data of skilled individuals is presented. Domain-specific knowledge is acquired from the visual behaviour of subjects whose eye movements are recorded while solving complex visual tasks. It is argued that relevant insights into the cognitive strategies followed by the observers to solve the visual search tasks may be gained by analysing the eye-tracking data in generic feature spaces, which are at the basis of the selected scheme for knowledge representation. In this context, a feature space is a domain in which each dimension is defined as a mathematical construct, which may correspond to perceptually meaningful visual cues and which can take either numerical or categorical values. A special case of such feature spaces is the spatial domain in which the spatial coordinates of the gaze points define the dimensions of such domain. In the proposed conceptual framework, the definition of similarities between visual search patterns is essential to characterise the stereotypical visual behaviour of a group of observers, and thus expert knowledge. Furthermore, since knowledge representation is closely related to the feature domain in which the search is analysed, feature relevance measures become central to knowledge gathering, and the main aspects regarding their definition are discussed in this work. Following a detailed presentation of the conceptual framework, a practical application dealing with expert knowledge gathering in lung radiology is shown both as a proof of concept and also to illustrate a particular functional implementation of the framework.

This paper presents a computational method of feature evaluation for modeling saliency in visual scenes. This is highly relevant in visual search studies since visual saliency is at the basis of visual attention deployment. Visual saliency can also become important in computer vision applications as it can be used to reduce the computational requirements by permitting processing only in those regions of the scenes containing relevant information. The method is based on Bayesian theory to describe the interaction between top-down and bottom-up information. Unlike other approaches, it evaluates and selects visual features before saliency estimation. This can reduce the complexity and, potentially, improve the accuracy of the saliency computation. To this end, we present an algorithm for feature evaluation and selection. A two-color conjunction search experiment has been applied to illustrate the theoretical framework of the proposed model. The practical value of the method is demonstrated with video segmentation of instruments in a laparoscopic cholecystectomy operation.

To use eye-tracking analysis to identify the differences in approach to and efficiency of reading thin-section CT of the lungs presented tiled and stacked soft-copy displays.Four chest radiologists read 16 thin-section CT examinations displayed in either a tiled (four images at once) or stacked (full screen cine) format. Eye-movements were recorded and analysed in terms of movement type; saccade distance (classified by the calculated range of useful peripheral vision), number of fixations, duration and direction of gaze-comparison of the areas of the images viewed.Cases presented in stacked format were read quicker than when presented in tiled format with a greater fixation frequency (5 fixations versus 4.5 fixations points per 100 data points; p0.001) and a greater proportion of short saccades (97% versus 94%; p0.005). The consistency with which the observers viewed equivalent areas of the scan images in different cases was greater when viewing in stacked format (mean kappa 0.45 versus 0.36; p0.05) suggesting a more systematic approach to reading.Eye-tracking data demonstrates why thin-section CT examinations of the lungs are read more efficiently when displayed in a stack as opposed to a tiled format.

This paper presents a new framework for capturing intrinsic visual search behavior of different observers in image understanding by analysing saccadic eye movements in feature space. The method is based on the information theory for identifying salient image features based on which visual search is performed. We demonstrate how to obtain feature space fixation density functions that are normalized to the image content along the scan paths. This allows a reliable identification of salient image features that can be mapped back to spatial space for highlighting regions of interest and attention selection. A two-color conjunction search experiment has been implemented to illustrate the theoretical framework of the proposed method including feature selection, hot spot detection, and back-projection. The practical value of the method is demonstrated with computed tomography image of centrilobular emphysema, and we discuss how the proposed framework can be used as a basis for decision support in medical image understanding.

This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.

Extensive research into the role of saccadic eye movements in human visual perception has been carried out for many years. Although the search patterns of different observers while studying the same image bear some common characteristics, there are often variations in the temporal order in which fixation points are viewed. During visual search for a defined target, there is evidence for both parallel search, with which all objects are processed concurrently, and for sequential search, in which several fixation points are found leading to the target. In this article, we present a review of both theoretical and experimental research directed towards better understanding of the underlying mechanisms of visual search. We begin by looking at the basic dynamics of saccadic eye movements and some of the major psychophysical models that have been developed over the years. An overview of the practical applications and future trends of visual search is then provided. Visual search is a common task that people perform throughout their daily life, and the number of applications inspired by the human visual search mechanism is potentially large. The purpose of this paper is to highlight some of the key opportunities for the image and vision computing community and promote further interactions between biological and computational vision research.

Decision making is a process of utmost/nimportance in our daily lives, the study of which has/nbeen receiving notable attention for decades. Nevertheless,/nthe neural mechanisms underlying decision making/nare still not fully understood. Computational modeling/nhas revealed itself as a valuable asset to address some of/nthe fundamental questions. Biophysically plausible models,/nin particular, are useful in bridging the different levels/nof description that experimental studies provide, from the/nneural spiking activity recorded at the cellular level to the/nperformance reported at the behavioral level. In this/narticle, we have reviewed some of the recent progress/nmade in the understanding of the neural mechanisms that/nunderlie decision making. We have performed a critical/nevaluation of the available results and address, from a/ncomputational perspective, aspects of both experimentation/nand modeling that so far have eluded comprehension./nTo guide the discussion, we have selected a central/ntheme which revolves around the following question: how/ndoes the spatiotemporal structure of sensory stimuli affect/nthe perceptual decision-making process? This question is a/ntimely one as several issues that still remain unresolved/nstem from this central theme. These include: (i) the role of/nspatiotemporal input fluctuations in perceptual decision/nmaking, (ii) how to extend the current results and models/nderived from two-alternative choice studies to scenarios/nwith multiple competing evidences, and (iii) to establish/nwhether different types of spatiotemporal input fluctuations/naffect decision-making outcomes in distinctive ways./nAnd although we have restricted our discussion mostly to/nvisual decisions, our main conclusions are arguably/ngeneralizable; hence, their possible extension to other/nsensory modalities is one of the points in our discussion. AI acknowledges funding from the SUR, DEC of the Generalitat de/nCatalunya and FSE. LDM is a Ramon y Cajal Fellow and acknowledges funding/nfrom the Ministry of Science and Innovation through the Ramon y Cajal/nprogramme. She also acknowledges financial support from the research project/nTIN2010-21771-C02-02 funded by the Ministry of Science and Innovation. MP was/nsupported by the CONSOLIDER-INGENIO 2010 Program CSD2007-00012. GD was/nsupported by the ERC Advanced Grant: DYSTRUCTURE (n. 295129), by the Spanish/nResearch Project SAF2010-16085 and by the CONSOLIDER-INGENIO 2010 Program/nCSD2007-00012, and the FP7-ICT BrainScales and Coronet. RR was supported by/ngrants from the Dirección de Personal Académico de la Universidad Nacional/nAutónoma de México and the Consejo Nacional de Ciencia y Tecnología.

Part 1: Long and Short Papers (Continued); International audience; Around 10% of the population has dyslexia, a reading disability that negatively affects a person’s ability to read and comprehend texts. Previous work has studied how to optimize the text layout, but adapting the text content has not received that much attention. In this paper, we present an eye-tracking study that investigates if people with dyslexia would benefit from content simplification. In an experiment with 46 people, 23 with dyslexia and 23 as a control group, we compare texts where words were substituted by shorter/longer and more/less frequent synonyms. Using more frequent words caused the participants with dyslexia to read significantly faster, while the use of shorter words caused them to understand the text better. Amongst the control group, no significant effects were found. These results provide evidence that people with dyslexia may benefit from interactive tools that perform lexical simplification.

When investigating multi-item WM, and in contrast to single item experiments, a decision must be made regarding a key aspect of the stimulation protocol: how the memory set is presented to the subject simultaneously or sequentially. It is worth noting that most studies investigating multi-item WM do not address this issue and focus either in simultaneous stimulation protocols (e.g. [1,2]) or in sequential stimulation protocols (e.g. [3]) without confronting the two situations. This is nevertheless an aspect which provides a benchmark to probe and compare the different theories regarding how resources are allocated among the different items of a memory set [4,5]. In this study, we explore a biophysically-realistic attractor model of visual working memory (VWM) endowed with synaptic facilitation and investigate what are the effects of varying the dynamics of the facilitation process. We fi nd that: 1) it is possible to reproduce experimentally observed effects such as the recency effect in sequential stimulation protocols (i.e. items presented in the final positions of a sequence are more likely to be retained in WM), and 2) WM capacity is boosted in both sequential and stimulation protocols when endowing the attractor network with synaptic facilitation. Conclusions In agreement with our previous results [2], synaptic facilitation boosts the WM capacity limit by effectively increasing the synaptic strengths just for those pools to which a cue is applied, and then maintaining the synaptic facilitation by the continuing neuronal firing in only these pools when the cue is removed. In this study, the time constant τF of the synaptic facilitation process has been found to play an important role in modulating this effect with large τF values leading to larger capacity limits in both sequential and simultaneous stimulation protocols. However, too large τF values lead to neuronal dynamics which are not compatible with the recency effect, thus constraining the range of values that τF may take.

Rupture of intracranial saccular aneurysms is the most common cause of spontaneous subarachnoid hemorrhage, which has significant morbidity and mortality. Although there is still controversy regarding the decision on which unruptured aneurysms should be treated, this is based primarily on their size. Nonetheless, many large lesions do not rupture whereas some small ones do. It is commonly accepted that hemodynamical factors are important to better understand the natural history of cerebral aneurysms. However, it might not always be practical to carry out a detailed computational analysis of such factors if a prompt assessment is required. Since shape is likely to be dependent on the balance between hemodynamic forces and the aneurysmal surrounding environment, an appropriate morphological 3-D characterization is likely to provide a practical surrogate to quickly evaluate the risk of rupture. In this paper, an efficient and novel methodology for 3-D shape characterization of cerebral aneurysms is described. The aneurysms are isolated by taking into account a portion of their adjacent vessels. Two methods to characterize the morphology of the aneurysms models using moment invariants have been considered: geometrical moment invariants (GMI) and Zernike moment invariants (ZMI). The results have been validated in a database containing 53 patients with a total of 31 ruptured aneurysms and 24 unruptured aneurysms. It has been found that ZMI indices are more robust than GMI, and seem to provide a reliable way to discriminate between ruptured and unruptured aneurysms. Correct rupture prediction rates of approximately equal to 80% were achieved in contrast to 66% that is found when the aspect ratio index is considered.

Haemodynamics, and in particular wall shear stress, is thought to play a critical role in the progression and rupture of intracranial aneurysms. A novel method is presented that combines image-based wall motion estimation obtained through non-rigid registration with computational fluid dynamics (CFD) simulations in order to provide realistic intra-aneurysmal flow patterns and understand the effects of deforming walls on the haemodynamic patterns. In contrast to previous approaches, which assume rigid walls or ad hoc elastic parameters to perform the CFD simulations, wall compliance has been included in this study through the imposition of measured wall motions. This circumvents the difficulties in estimating personalized elasticity properties. Although variations in the aneurysmal haemodynamics were observed when incorporating the wall motion, the overall characteristics of the wall shear stress distribution do not seem to change considerably. Further experiments with more cases will be required to establish the clinical significance of the observed variations.

The rupture mechanism of intracranial aneurysms is still not fully understood. Although the size of the aneurysm is the shape index most commonly used to predict rupture, some controversy still exists about its adequateness as an aneurysm rupture predictor. In this work, an automatic method to geometrically characterize the shape of cerebral saccular aneurysms using 3D moment invariants is proposed. Geometric moments are efficiently computed via application of the Divergence Theorem over the aneurysm surface using a non-structured mesh. 3D models of the aneurysm and its connected parent vessels have been reconstructed from segmentations of both 3DRA and CTA images. Two alternative approaches have been used for segmentation, the first one based on isosurface deformable models, and the second one based on the level set method. Several experiments were also conducted to both assess the influence of pre-processing steps in the stability of the aneurysm shape descriptors, and to know the robustness of the proposed method. Moment invariants have proved to be a robust technique while providing a reliable way to discriminate between ruptured and unruptured aneurysms (Sensitivity=0.83, Specificity=0.74) on a data set containing 55 aneurysms. Further investigation over larger databases is necessary to establish their adequateness as reliable predictors of rupture risk.

The role of eye movements in medical image understanding has been extensively studied. To assess the visual search behaviour of observers in examining images from different patients, it is necessary to account for patient-specific morphological variations, such that fixations related to specific feature landmarks are co-registered. This paper proposes a framework for analysing the spatial dynamics of the eye movements through the introduction of standardised lung anatomy. The reference lungs have been obtained by using hierarchical free-form registration of high resolution computed tomography (HRCT) lung images. The registration procedure is used to map patient-specific gaze points to the reference anatomy such that the general visual behaviour of different observers can be assessed.

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

Publisher Summary In drawing portraits from life, the eye plays a central role as it is the means by which visual input is acquired from the external world, as well as the means by which the hand is guided as it draws, and the results are evaluated. This chapter explores painter's eye movements to establish the ground data required to understand the picture production process. Drawing from life entails eye movements from paper to model and back. Glancing at a model to acquire detailed visual information is best achieved with single and stable fixations. The information is then available in the painter's visual memory for about two seconds before needing to be refreshed, although in the advanced stages of the drawing, work may proceed for longer periods on the basis of the lines already existing on the paper. On the paper, the painter's fixations do not coincide with the pencil point but are located at a distance of half to one degree, and as the pencil moves, small saccades keep up with the line as it is being drawn. Closed-loop type situations may arise between the eye and the hand when the hand practices a line to be drawn without actually marking the paper, gradually honing in to its final position and direction.

Estimation of Sea Surface Temperature (SST) from split- window algorithms for NOAA-AVHRR data can be determined with rms values of 0.7 K on a global basis. However, this figure is not compatible with the stringent accuracy of 0.3 K required by climate studies. Among the different sources of errors, the presence of tropospheric aerosols in the satellite field of view prevents the retrieval of accurate satellite SSTs. Still, the effect of aerosols on temperature measurements derived from remote sensing techniques has been traditionally overlooked. Very few studies have addressed the problem of giving split-window algorithms which incorporate aerosol correction, although retrieving algorithms of the aerosol loading from the images do exist. The aim of this study is the evaluation of the effect of the aerosols on the SST MODTRAN code. Such code was used to compute the upwelling radiances and, subsequently k, the brightness temperatures under cloud-free conditions. The filter response functions for the NOAA14 instrument are used to produce theoretical brightness temperatures for the zenith angles: 0 degrees, 30 degrees and 55 degrees. The results show that for most of all the atmospheres that we have considered, deviations as far as 0.8 K are reached compared with the case in which the aerosols are not considered. It is important to point up that deviations higher than 0.4K are able to mask the improvement introduced by a diminution of the Noise Equivalent Temperature in the new sensors as a consequence of error propagation.

Multi-angle algorithms for estimating sea and land surface temperature with ATSR data require a precise knowledge of the angular variation of surface emissivity in the thermal infrared. Nowadays, very few measurements do exist of this variation. In this work an experimental investigation of the angular variation of the infrared emissivity in the thermal infrared (8 - 14 micrometer) band of some representative samples has been made at angles of 0 degrees - 65 degrees (at 5 degree increments) to the surface normal. The results show a decrease of the emissivity with increasing viewing angles, being water the substance with highest angular dependence (about 7% from 0 degree to 65 degree views). Clay, sand, slimy and gravel show variations about 1 - 3% in the same range of views while an homogeneous grass cover does not show angular dependence. Finally, we include an evaluation of the impact that these data can produce in the algorithms for determining land and sea surface temperature from double angle views.

Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent/nneurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the/nmore common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate/npossible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model/nwhich is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is/npresented. The proposed computational model successfully accounts for well known psychophysical effects for static/ncontexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas./nThis work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and/nreveals how a common general architecture may account for several different fundamental processes, such as visual/nsaliency and brightness induction, which emerge early in the visual processing pathway. This research has been partially supported by the Spanish Ministry of Science and Innovation through the research projects TIN2010-21771-C02-01 and TIN2010-21771-C02-02. OP is supported by the Spanish Ministry of Science and Innovation through the research project Consolider Ingenio (CSD 2007-00018).

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging. This work was supported by the Spanish Research Projects BFU2007-61710, CONSOLIDER CSD2007-00012; the Oxford McDonnell Centre for Cognitive Neuroscience; the Oxford Centre for Computational Neuroscience; MIDECO through the Ramon y Cajal Programme (LDM); and from the TIN2010-21771-C02-02 project (LDM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the storage capacity limit has been thoroughly studied [1], its origin still remains a matter of debate. Several neurophysiological studies suggest that items are maintained in working memory through elevated firing activity in cortical neural assemblies that selectively respond to specific stimuli. Accounting for this experimental observation, Edin et al. [2] proposed a mechanistic explanation of the top-down control of working memory capacity and, based on a mean-field analysis, established an upper boundary to the number of items that can be held in memory. By also making use of a recurrent network model of working memory [3], we have further investigated the mechanisms underlying working memory capacity while also accounting for the two following experimental observations: 1) visual saliency reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory in delay match-to-sample tasks at the cost of not keeping as many non-salient items. Figure 1 Theoretical prediction of the performance derived from computational simulations of a delayed match-to-sample task with n selective neural assemblies simultaneously stimulated. Performance is calculated by assuming that an item is held in memory when ...