Perceived depth in non-transitive stereo displays

AbstractThe separation between the eyes shapes the distribution of binocular disparities and gives a special role to horizontal disparities. However, for one-dimensional stimuli, disparity direction, like motion direction, is linked to stimulus orientation. This makes the perceived depth of one-dimensional stimuli orientation dependent and generally non-veridical. It also allows perceived depth to violate transitivity. Three stimuli, A, B, and C, can be arranged such that A>B (stimulus A is seen as farther than stimulus B when they are presented together) and B>C, yet A⩽C. This study examines how the visual system handles the depth of A, B, and C when they are presented together, forming a pairwise inconsistent stereo display. Observers’ depth judgments of displays containing a grating and two plaids resolved transitivity violations among the component stimulus pairs. However, these judgments were inconsistent with judgments of the same stimuli within depth-consistent displays containing no transitivity violations. To understand the contribution of individual disparity signals, observers were instructed in subsequent experiments to judge the depth of a subset of display stimuli. This attentional instruction was ineffective; relevant and irrelevant stimuli contributed equally to depth judgments. Thus, the perceived depth separating a pair of stimuli depended on the disparities of the other stimuli presented concurrently. This context dependence of stereo depth can be approximated by an obligatory pooling and comparison of the disparities of one- and two-dimensional stimuli along an axis defined locally by the stimuli

Using The Symmetry Of False Matches To Solve The Correspondence Problem

Veridical stereoscopic depth depends on matching corresponding image points. This requires solving the stereo correspondence problem: how are true matches distinguished from false ones? Conventional algorithms select true matches on the basis of feature detection [what do you mean by ‘feature detection’ here? Is there some more specific term?] and adherence to natural statistics. They reject false matches as noise. We propose here an alternative that uses the signals present in false matches to delineate the true solution. When visualized in a Keplerian array, binocular matches are symmetrically reflected about an axis that is a potential solution. Properties such as extent and curvature of the solution are encoded the transformation that describes how one-half of the matches reflects onto the other. To implement this strategy, left and right images were convolved with Gaussian kernels of various standard deviations (spatial frequencies). Keplerian arrays comparing filter responses across left and right spatial-frequency combinations were then constructed. Responses that are minimally different across the eyes give rise to regions of high symmetry; position within the Keplerian array indicates the location of a solution in space. Solutions that possess natural surface regularities consistently showed minimal differences for one left : right spatial frequency ratio, which is correlated with local surface slant. As a result, combining responses within particular ratio families can distinguish true matches from false ones. True matches tend to be long and smoothly contoured, and symmetry would be preserved across all members of a ratio family from low to high spatial-frequency combinations. This approach is efficient; preprocessing is minimal since no feature extraction is involved. It can be implemented in machine vision to solve the correspondence problem for depth sensing algorithms. It is robust when tested against perfectly camouflaged surfaces in random dot stereograms and consistent with physiological data showing that false match signals are propagated to higher cortical areas along the dorsal pathway

Structural and functional characterization of signaling protein complexes

Ph.DDOCTOR OF PHILOSOPH

Attentional selection in judgments of stereo depth

Stereoscopic depth is most useful when it comes from relative rather than absolute disparities. However, the depth perceived from relative disparities can vary with stimulus parameters that have no connection with depth or are irrelevant to the task. We investigated observers’ ability to judge the stereo depth of task-relevant stimuli while ignoring irrelevant stimuli. The calculation of depth from disparity differs for 1-D and 2-D stimuli and we investigated the role this difference plays in observers’ ability to selectively process relevant information. We show that the presence of irrelevant disparities affects perceived depth differently depending on stimulus dimensionality. Observers could not ignore disparities of irrelevant stimuli when they judged the relative depth between a 1-D stimulus (a grating) and a 2-D stimulus (a plaid). Yet these irrelevant disparities did not affect judgments of the relative depth between 2-D stimuli. Two processes contributing to stereo depth were identified, only one of which computes depth from a horizontal disparity metric and permits attentional selection. The other uses all stimuli, relevant and irrelevant, to calculate an effective disparity direction for comparing disparity magnitudes. These processes produce inseparable effects in most data sets. Using multiple disparity directions and comparing 1-D and 2-D stimuli can distinguish them

False-Match Symmetry: Data Files and Simulation Code

This record provides data from random-dot stereograms to use in solving the binocular correspondence problem through false-match symmetry. It also provides an implementation of the algorithm used in the article ‘Solving the stereo correspondence problem with false matches’ [Ng CJ, Farell B (2019) Solving the stereo correspondence problem with false matches. PLoSONE 14(7): e0219052. https://doi.org/10.1371/journal.pone.0219052]. The record consists of two parts, Data and Algorithm Demo. The Data component consists of pre-computed Keplerian arrays of all possible matches between filtered random-dot image pairs containing stereoscopically defined surfaces. The Algorithm Demo allows data files to be computed afresh from supplied pairs of images of various surface configurations. Plotting of data is possible in both cases. An interactive demo can also be used to explore the target image selection process

Additional Serine/Threonine Phosphorylation Reduces Binding Affinity but Preserves Interface Topography of Substrate Proteins to the c-Cbl TKB Domain

The E3-ubiquitin ligase, c-Cbl, is a multi-functional scaffolding protein that plays a pivotal role in controlling cell phenotype. As part of the ubiquitination and downregulation process, c-Cbl recognizes targets, such as tyrosine kinases and the Sprouty proteins, by binding to a conserved (NX/R)pY(S/T)XXP motif via its uniquely embedded SH2 domain (TKB domain). We previously outlined the mode of binding between the TKB domain and various substrate peptide motifs, including epidermal growth factor receptor (EGFR) and Sprouty2 (Spry2), and demonstrated that an intrapetidyl hydrogen bond forms between the (pY-1) arginine or (pY-2) asparagine and the phosphorylated tyrosine, which is crucial for binding. Recent reports demonstrated that, under certain types of stimulation, the serine/threonine residues at the pY+1 and/or pY+2 positions within this recognition motif of EGFR and Sprouty2 may be endogenously phosphorylated. Using structural and binding studies, we sought to determine whether this additional phosphorylation could affect the binding of the TKB domain to these peptides and consequently, whether the type of stimulation can dictate the degree to which substrates bind to c-Cbl. Here, we show that additional phosphorylation significantly reduces the binding affinity between the TKB domain and its target proteins, EGFR and Sprouty2, as compared to peptides bearing a single tyrosine phosphorylation. The crystal structure indicates that this is accomplished with minimal changes to the essential intrapeptidyl bond and that the reduced strength of the interaction is due to the charge repulsion between c-Cbl and the additional phosphate group. This obvious reduction in binding affinity, however, indicates that Cbl's interactions with its TKB-centered binding partners may be more favorable in the absence of Ser/Thr phosphorylation, which is stimulation and context specific in vivo. These results demonstrate the importance of understanding the environment in which certain residues are phosphorylated, and the necessity of including this in structural investigations

Investigation of noise removal algorithms for medical applications

There are various ways to review, study and diagnose new and existing undesired health symptoms. Two of the common used types are Laboratory diagnosis and Radiology diagnosis. Rather than getting the information from the physical examination of the patient, Laboratory diagnosis rely greatly on laboratory reports and test outcomes. On the other hand, Radiology diagnosis is based on the results of medical imaging. Radiology diagnosis will be the main focus for this project. Radiology diagnosis uses imaging technology to diagnose and treat diseases. By using this method of diagnosis, health professionals such as doctors, will be able to see the inner structure of the body and hence, review the cause of the undesired health symptoms. Imaging technology can be used to diagnose different types of illnesses like breast cancer, colon cancer, heart disease e.g. Imaging technology is also used to monitor the health conditions of the patient. One of the examples is to monitor how well the body system is responding to a certain treatment or medication that has been given to treat the disease. There are numerous types of diagnostic radiology. Computed Tomography (CT), also known as CAT (Computerized Axial Tomography), uses X-rays to produce images of the inner structure of the body. Ultrasound is a diagnostic radiology, which uses high frequency sound waves to capture images of the inner structure of the body. Magnetic resonance imaging (MRI) uses both magnetic field and radio wave signals to create images of the organs and structures in the body. The advantage of MRI is that it provides different information about the structure inside the body which can be seen with CT and Ultrasound scan. It also provides information which cannot be shown in both CT and Ultrasound scan. MRI will be the main focus for this project. However, unwanted signals like noise, often exist in the medical images. With the existing of noise in the radiology images, it creates challenges for health professionals to effectively analyze and diagnose the health symptoms that the patient is having. In diagnostic radiology such as medical imaging, to ensure that productive and effective diagnose can be made by the health professionals, it is important that the medical images contains as minimal amount of noise as possible. Noise removal is a process of which unwanted noise is being extracted from the signal. To prevent inaccurate diagnosis of the medical images, it is a challenging problem to make sure that apart from the undesired noise, the rest of information in the medical images are being preserved after performing noise removal practices. There are numerous types of noise removal algorithms for medical applications. This report will be focusing on the removal of undesirable noise using algorithms of appropriate filters that have been implemented by the author. This report will give the explanation of the performance of four types of filters. These four filters are then applied to the medical images that contain different types of unwanted noise. The medical images that were being used are MRI images. To analyze which filter is the most effective in removing the particular noise from the particular MRI image, performance measurements are performed, calculated and evaluated.Bachelor of Engineerin

OUT OF SIGHT, OUT OF MIND?: AN EMPIRICAL ANALYSIS OF CPFIS MUTUAL FUND EXPENSE RATIO

Bachelor'sBACHELOR OF BUSINESS ADMINISTRATION WITH HONOUR

Solving the stereo correspondence problem with false matches.

The stereo correspondence problem exists because false matches between the images from multiple sensors camouflage the true (veridical) matches. True matches are correspondences between image points that have the same generative source; false matches are correspondences between similar image points that have different sources. This problem of selecting true matches among false ones must be overcome by both biological and artificial stereo systems in order for them to be useful depth sensors. The proposed re-examination of this fundamental issue shows that false matches form a symmetrical pattern in the array of all possible matches, with true matches forming the axis of symmetry. The patterning of false matches can therefore be used to locate true matches and derive the depth profile of the surface that gave rise to them. This reverses the traditional strategy, which treats false matches as noise. The new approach is particularly well-suited to extract the 3-D locations and shapes of camouflaged surfaces and to work in scenes characterized by high degrees of clutter. We demonstrate that the symmetry of false-match signals can be exploited to identify surfaces in random-dot stereograms. This strategy permits novel depth computations for target detection, localization, and identification by machine-vision systems, accounts for physiological and psychophysical findings that are otherwise puzzling and makes possible new ways for combining stereo and motion signals

Stereoacuity improves after short-term binocular pattern mismatch.

Monocular deprivation can chronically suppress vision in the deprived eye, if it is applied for sufficient duration early in life. However, it can have a transient effect in the opposite direction if applied briefly (a few hours) to normal adults. This short-term monocular deprivation appears to increase the gain for the deprived eye relative to the undeprived eye, affecting binocular vision by shifting the interocular balance. An interocular gain difference produced by patching a single eye might be expected to lower stereoacuity in normal observers, since raising contrast in just one eye reduces stereoacuity (the ‘contrast paradox’). We hypothesized that alternately depriving each eye in turn might benefit stereoacuity by increasing post‐deprivation gain in both eyes and dampening interocular suppression. We switched a translucent patch between the eyes of visually normal adult observers hourly for 6 hours. The unpatched eye viewed the natural visual environment. Compared to pre-patch performance, post-patch grating stereoacuity, measured during 20 minutes following patch removal, improved by 20% to 33%. In a second experiment, we alternately covered the left and right eyes of two observers with cylinder lenses to determine the existence of orientation-specific gain. Each eye was ‘patched’ with the lens for 45 or 60 minute periods, giving a total through-the-lens viewing of 4 to 6 hours. Unexpectedly, post-patching stereoacuity improved for test gratings with the same orientation as seen through the lens and worsened for orthogonal gratings. This result cannot be explained by monocular orientation adaptation. It implies that the interocular balance has a channel structure that is modulated not specifically by monocular deprivation but rather by interocular pattern mismatch. The post-patching enhancement evident in both experiments indicates that interocular suppression may limit stereoacuity under natural viewing conditions