1,808 research outputs found
Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning
A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.Air Force Office of Scientific Research (F49620-01-1-0397, F49620-01-1-0423); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624
Change blindness: eradication of gestalt strategies
Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task
Bodily awareness and novel multisensory features
According to the decomposition thesis, perceptual experiences resolve without remainder into their different modality-specific components. Contrary to this view, I argue that certain cases of multisensory integration give rise to experiences representing features of a novel type. Through the coordinated use of bodily awareness—understood here as encompassing both proprioception and kinaesthesis—and the exteroceptive sensory modalities, one becomes perceptually responsive to spatial features whose instances couldn’t be represented by any of the contributing modalities functioning in isolation. I develop an argument for this conclusion focusing on two cases: 3D shape perception in haptic touch and experiencing an object’s egocentric location in crossmodally accessible, environmental space
Correcciones para la presbicia : implicaciones ópticas, perceptuales y adaptativas
Tesis de la Universidad Complutense de Madrid, Facultad de Óptica y Optometría, leída el 18-05-2016Presbyopia is the physiological inability of the crystalline lens to accommodate for objects at near distance. While accommodative lenses are the ideal solutions for presbyopia, current optical solutions rely on providing an acceptable quality of vision at near and far distances. Optimization of the optical solutions rely on better understanding of how the visual system copes with the visual quality produced by the various optical solutions. The aim of this thesis is to study optical, visual and perceptual performance of different presbyopic corrections such as alternating vision, monovision and simultaneous vision, and to study the effect of adaptation on perceptual performances. Methods: We measured and corrected ocular aberrations using custom developed adaptive optics setup, used images blurred by real aberrations of different orientation and/or magnitude and measured the internal code for blur in eyes with long term differences in blur magnitude or orientation using a classification-image like technique. We later used numerically convolved images of different far/near energy and different near additions to study the short term adaptation to pure simultaneous vision using single stimulus detection and scoring tasks...La presbicia es la incapacidad del cristalino para enfocar objetos cercanos. Mientras que las lentes acomodativas son una buena solución para la presbicia, las soluciones más actuales se basan en una corrección aceptable de la visión cercana y lejana simultáneamente. La optimización de estas soluciones pasa por comprender cómo reacciona el sistema a las diferentes correcciones ópticas. El objetivo de esta tesis es el estudio óptico, visual y perceptual de diferentes correcciones a la presbicia como la visión alternante, la mono visión y la visión simultánea, y el estudio del efecto dela adaptación desde el punto de vista perceptual. MétodosSe han medido y corregido las aberraciones oculares mediante un sistema de óptica adaptativa de construcción propia y se han usado imágenes desenfocadas con aberraciones reales con diferentes magnitudes y/u orientaciones para medir el código interno de emborronamiento en los ojos para los diferentes desenfoques y orientaciones mediante métodos de clasificación de imágenes. Posteriormente se han usado imágenes convolucionadas numéricamente con diferentes proporciones en las energías del enfoque cercano o lejano y con diferentes adiciones para estudiar laadaptación a corto plazo en la visión simultánea pura a través de la detección y valoración de estímulos individuales...Fac. de Óptica y OptometríaTRUEunpu
Deep into the Eyes: Applying Machine Learning to improve Eye-Tracking
Eye-tracking has been an active research area with applications in personal and behav- ioral studies, medical diagnosis, virtual reality, and mixed reality applications. Improving the robustness, generalizability, accuracy, and precision of eye-trackers while maintaining privacy is crucial. Unfortunately, many existing low-cost portable commercial eye trackers suffer from signal artifacts and a low signal-to-noise ratio. These trackers are highly depen- dent on low-level features such as pupil edges or diffused bright spots in order to precisely localize the pupil and corneal reflection. As a result, they are not reliable for studying eye movements that require high precision, such as microsaccades, smooth pursuit, and ver- gence. Additionally, these methods suffer from reflective artifacts, occlusion of the pupil boundary by the eyelid and often require a manual update of person-dependent parame- ters to identify the pupil region. In this dissertation, I demonstrate (I) a new method to improve precision while maintaining the accuracy of head-fixed eye trackers by combin- ing velocity information from iris textures across frames with position information, (II) a generalized semantic segmentation framework for identifying eye regions with a further extension to identify ellipse fits on the pupil and iris, (III) a data-driven rendering pipeline to generate a temporally contiguous synthetic dataset for use in many eye-tracking ap- plications, and (IV) a novel strategy to preserve privacy in eye videos captured as part of the eye-tracking process. My work also provides the foundation for future research by addressing critical questions like the suitability of using synthetic datasets to improve eye-tracking performance in real-world applications, and ways to improve the precision of future commercial eye trackers with improved camera specifications
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Characterization and modeling of the human left atrium using optical coherence tomography
With current needs to better understand the interaction between atrial tissue microstructure and atrial fibrillation dynamics, micrometer scale imaging with optical coherence tomography has significant potential to provide further insight on arrhythmia mechanisms and improve treatment guidance. However, optical coherence tomography imaging of cardiac tissue in humans is largely unexplored, and the ability of optical coherence tomography to identify the structural substrate of atrial fibrillation has not yet been investigated. Therefore, the objective of this thesis was to develop an optical coherence tomography imaging atlas of the human heart, study the utility of optical coherence tomography in providing useful features of human left atrial tissues, and develop a framework for optical coherence tomography-informed cardiac modeling that could be used to probe dynamics between electrophysiology and tissue structure.
Human left atrial tissues were comprehensively imaged by optical coherence tomography for the first time, providing an imaging atlas that can guide identification of left atrial tissue features from optical coherence tomography imaging. Optical coherence tomography image features corresponding to myofiber and collagen fiber orientation, adipose tissue, endocardial thickness and composition, and venous media were established. Varying collagen fiber distributions in the myocardial sleeves were identified within the pulmonary veins. A scheme for mapping optical coherence tomography data of dissected left atrial tissues to a three-dimensional, anatomical model of the human left atrium was also developed, enabling the mapping of distributions of imaged adipose tissue and fiber orientation to the whole left atrial geometry. These results inform future applications of structural substrate mapping in the human left atrium using optical coherence tomography-integrated catheters, as well as potential directions of ex vivo optical coherence tomography atrial imaging studies.
Additionally, we developed a workflow for creating optical mapping models of atrial tissue as informed by optical coherence tomography. Tissue geometry, fiber orientation, ablation lesion geometry, and heterogeneous tissue types were extracted from optical coherence tomography images and incorporated into tissue-specific meshes. Electrophysiological propagation was simulated and combined with photon scattering simulations to evaluate the influence of tissue-specific structure on electrical and optical mapping signals. Through tissue-specific modeling of myofiber orientation, ablation lesions, and heterogeneous tissue types, the influence of myofiber orientation on transmural activation, the relationship between fluorescent signals and lesion geometry, and the blurring of optical mapping signals in the presence of heterogeneous tissue types were investigated.
By providing a comprehensive optical coherence tomography image database of the human left atrium and a workflow for developing optical coherence tomography-informed cardiac tissue models, this work establishes the foundation for utilizing optical coherence tomography to improve the structural substrate characterization of atrial fibrillation. Future developments include analysis of optical coherence tomography imaged tissue structure with respect to clinical presentation, development of automated processing to better leverage the large amount of imaging data, enhancements and validation of the modeling scheme, and in vivo evaluation of the left atrial structural substrate through optical coherence tomography-integrated catheter
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