905 research outputs found

    Detection of dirt impairments from archived film sequences : survey and evaluations

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    Film dirt is the most commonly encountered artifact in archive restoration applications. Since dirt usually appears as a temporally impulsive event, motion-compensated interframe processing is widely applied for its detection. However, motion-compensated prediction requires a high degree of complexity and can be unreliable when motion estimation fails. Consequently, many techniques using spatial or spatiotemporal filtering without motion were also been proposed as alternatives. A comprehensive survey and evaluation of existing methods is presented, in which both qualitative and quantitative performances are compared in terms of accuracy, robustness, and complexity. After analyzing these algorithms and identifying their limitations, we conclude with guidance in choosing from these algorithms and promising directions for future research

    Misperceptions in the Trajectories of Objects undergoing Curvilinear Motion

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    Trajectory perception is crucial in scene understanding and action. A variety of trajectory misperceptions have been reported in the literature. In this study, we quantify earlier observations that reported distortions in the perceived shape of bilinear trajectories and in the perceived positions of their deviation. Our results show that bilinear trajectories with deviation angles smaller than 90 deg are perceived smoothed while those with deviation angles larger than 90 degrees are perceived sharpened. The sharpening effect is weaker in magnitude than the smoothing effect. We also found a correlation between the distortion of perceived trajectories and the perceived shift of their deviation point. Finally, using a dual-task paradigm, we found that reducing attentional resources allocated to the moving target causes an increase in the perceived shift of the deviation point of the trajectory. We interpret these results in the context of interactions between motion and position systems

    From filters to features:Scale-space analysis of edge and blur coding in human vision

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    To make vision possible, the visual nervous system must represent the most informative features in the light pattern captured by the eye. Here we use Gaussian scale-space theory to derive a multiscale model for edge analysis and we test it in perceptual experiments. At all scales there are two stages of spatial filtering. An odd-symmetric, Gaussian first derivative filter provides the input to a Gaussian second derivative filter. Crucially, the output at each stage is half-wave rectified before feeding forward to the next. This creates nonlinear channels selectively responsive to one edge polarity while suppressing spurious or "phantom" edges. The two stages have properties analogous to simple and complex cells in the visual cortex. Edges are found as peaks in a scale-space response map that is the output of the second stage. The position and scale of the peak response identify the location and blur of the edge. The model predicts remarkably accurately our results on human perception of edge location and blur for a wide range of luminance profiles, including the surprising finding that blurred edges look sharper when their length is made shorter. The model enhances our understanding of early vision by integrating computational, physiological, and psychophysical approaches. © ARVO

    Cortical Dynamics of Visual Motion Perception: Short-Range and Long Range Apparent Motion

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    This article describes further evidence for a new neural network theory of biological motion perception that is called a Motion Boundary Contour System. This theory clarifies why parallel streams Vl-> V2 and Vl-> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The Motion Boundary Contour System consists of several parallel copies, such that each copy is activated by a different range of receptive field sizes. Each copy is further subdivided into two hierarchically organized subsystems: a Motion Oriented Contrast Filter, or MOC Filter, for preprocessing moving images; and a Cooperative-Competitive Feedback Loop, or CC Loop, for generating emergent boundary segmentations of the filtered signals. The present article uses the MOC Filter to explain a variety of classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include split motion; reverse-contrast gamma motion; delta motion; visual inertia; group motion in response to a reverse-contrast Ternus display at short interstimulus intervals; speed-up of motion velocity as interfiash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, interstimulus interval, and motion threshold known as Korte's Laws; and dependence of motion strength on stimulus orientation and spatial frequency. These results supplement earlier explanations by the model of apparent motion data that other models have not explained; a recent proposed solution of the global aperture problem, including explanations of motion capture and induced motion; an explanation of how parallel cortical systems for static form perception and motion form perception may develop, including a demonstration that these parallel systems are variations on a common cortical design; an explanation of why the geometries of static form and motion form differ, in particular why opposite orientations differ by 90°, whereas opposite directions differ by 180°, and why a cortical stream Vl -> V2 -> MT is needed; and a summary of how the main properties of other motion perception models can be assimilated into different parts of the Motion Boundary Contour System design.Air Force Office of Scientific Research (90-0175); Army Research Office (DAAL-03-88-K0088); Defense Advanced Research Projects Agency (AFOSR-90-0083); Hughes Aircraft Company (S1-903136

    Computing Chromatic Adaptation

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    Most of today’s chromatic adaptation transforms (CATs) are based on a modified form of the von Kries chromatic adaptation model, which states that chromatic adaptation is an independent gain regulation of the three photoreceptors in the human visual system. However, modern CATs apply the scaling not in cone space, but use “sharper” sensors, i.e. sensors that have a narrower shape than cones. The recommended transforms currently in use are derived by minimizing perceptual error over experimentally obtained corresponding color data sets. We show that these sensors are still not optimally sharp. Using different computational approaches, we obtain sensors that are even more narrowband. In a first experiment, we derive a CAT by using spectral sharpening on Lam’s corresponding color data set. The resulting Sharp CAT, which minimizes XYZ errors, performs as well as the current most popular CATs when tested on several corresponding color data sets and evaluating perceptual error. Designing a spherical sampling technique, we can indeed show that these CAT sensors are not unique, and that there exist a large number of sensors that perform just as well as CAT02, the chromatic adaptation transform used in CIECAM02 and the ICC color management framework. We speculate that in order to make a final decision on a single CAT, we should consider secondary factors, such as their applicability in a color imaging workflow. We show that sharp sensors are very appropriate for color encodings, as they provide excellent gamut coverage and hue constancy. Finally, we derive sensors for a CAT that provide stable color ratios over different illuminants, i.e. that only model physical responses, which still can predict experimentally obtained appearance data. The resulting sensors are sharp

    Riding the South Sea bubble

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    This paper presents a case study of a well-informed investor in the South Sea bubble. We argue that Hoare's Bank, a fledgling West End London banker, knew that a bubble was in progress and nonetheless invested in the stock; it was profitable to "ride the bubble." Using a unique dataset on daily trades, we show that this sophisticated investor was not constrained by institutional factors such as restrictions on short sales or agency problems. Instead, this study demonstrates that predictable investor sentiment can prevent attacks on a bubble; rational investors may only attack when some coordinating event promotes joint action.Efficient Market Hypothesis, Bubbles, Crashes, Synchronization Risk, Investor Sentiment, South Sea Bubble, Market Timing, Limits to Arbitrage

    Doctor of Philosophy

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    dissertationSemiconductor nanocrystal quantum dots are a relatively recent area of study in materials science and engineering, but their unique, size-dependent properties have resulted in active growth over the past three decades. The motivation for this thesis has been exploiting the ability to tune the energy band gap and develop new families of geothermal reservoir tracers. While colloid transport in porous media has been studied extensively for groundwater systems, there is little existing research appropriate to high temperature geothermal systems. In this research, a multitiered approach is used to characterize quantum dot behavior at temperatures above 100 °C. First, a model system of cadmium selenide (CdSe) quantum dots is used to investigate fundamental aspects of nanocrystal growth and dissolution. Observing quantum dot dissolution and modeling the kinetic parameters yields critically important thermodynamic properties. These parameters are necessary for optimizing large-scale reactor conditions and design, and predicting fluid-phase quantum dot behavior. Insight into these thermodynamic properties provides the basis for experimentally studying transport in high temperature porous media that are surrogates for a geothermal reservoir. Core/shell quantum dots were pumped through Ottawa sand columns under a range of temperatures and salinities. Retardation and deposition were investigated as the principal transport parameters, while also considering the dynamics of quantum dot solubility and the interaction energy between quantum dots and the sand surfaces. Elevated temperatures increased the amount of quantum dot retention, following a multilayer deposition model. Finally, a novel method for detecting optically active species is introduced. Existing techniques for optical detection of quantum dots fail in turbid or high temperature environments. We demonstrate how the characteristic absorption - coupled with a long-wavelength overtone band - can be used to detect QDs in a variety of industrially relevant mixtures

    Neural Dynamics of Motion Perception: Direction Fields, Apertures, and Resonant Grouping

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    A neural network model of global motion segmentation by visual cortex is described. Called the Motion Boundary Contour System (BCS), the model clarifies how ambiguous local movements on a complex moving shape are actively reorganized into a coherent global motion signal. Unlike many previous researchers, we analyse how a coherent motion signal is imparted to all regions of a moving figure, not only to regions at which unambiguous motion signals exist. The model hereby suggests a solution to the global aperture problem. The Motion BCS describes how preprocessing of motion signals by a Motion Oriented Contrast Filter (MOC Filter) is joined to long-range cooperative grouping mechanisms in a Motion Cooperative-Competitive Loop (MOCC Loop) to control phenomena such as motion capture. The Motion BCS is computed in parallel with the Static BCS of Grossberg and Mingolla (1985a, 1985b, 1987). Homologous properties of the Motion BCS and the Static BCS, specialized to process movement directions and static orientations, respectively, support a unified explanation of many data about static form perception and motion form perception that have heretofore been unexplained or treated separately. Predictions about microscopic computational differences of the parallel cortical streams V1 --> MT and V1 --> V2 --> MT are made, notably the magnocellular thick stripe and parvocellular interstripe streams. It is shown how the Motion BCS can compute motion directions that may be synthesized from multiple orientations with opposite directions-of-contrast. Interactions of model simple cells, complex cells, hypercomplex cells, and bipole cells are described, with special emphasis given to new functional roles in direction disambiguation for endstopping at multiple processing stages and to the dynamic interplay of spatially short-range and long-range interactions.Air Force Office of Scientific Research (90-0175); Defense Advanced Research Projects Agency (90-0083); Office of Naval Research (N00014-91-J-4100

    Characterizing the Heme Uptake Proteins HtaB and ChtB in Corynebacterium diphtheriae

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    Corynebacterium diphtheriae is a Gram-positive, pathogenic bacterium. Pathogenic bacteria require iron as a key nutrient for survival. C. diphtheriae utilizes a direct heme uptake system in which the heme binds to a receptor protein that transfers the heme along the pathway to an ABC transporter, which facilitates the transfer of heme into the bacterial cell. This heme uptake pathway is encoded by the hmu and cht gene loci, which includes the genes for the surface-anchored proteins HtaB and ChtB. HtaB is proposed to have a function in transporting the heme obtained by HtaA to HmuT. ChtB is proposed to have a similar function to that of HtaB. Bioinformatics analysis shows that both HtaB and ChtB contain conserved tyrosine and histidine residues that are consistent with that of HtaA domains. A combination of UV-visible, circular dichroism, resonance Raman, and fluorescence spectroscopy have been used to characterize these proteins further
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