Browsing by Subject "Vision"
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Item 3D Multi-Field Multi-Scale Features From Range Data In Spacecraft Proximity Operations(2012-07-16) Flewelling, Brien RoyA fundamental problem in spacecraft proximity operations is the determination of the 6 degree of freedom relative navigation solution between the observer reference frame and a reference frame tied to a proximal body. For the most unconstrained case, the proximal body may be uncontrolled, and the observer spacecraft has no a priori information on the body. A spacecraft in this scenario must simultaneously map the generally poorly known body being observed, and safely navigate relative to it. Simultaneous localization and mapping(SLAM)is a difficult problem which has been the focus of research in recent years. The most promising approaches extract local features in 2D or 3D measurements and track them in subsequent observations by means of matching a descriptor. These methods exist for both active sensors such as Light Detection and Ranging(LIDAR) or laser RADAR(LADAR), and passive sensors such as CCD and CMOS camera systems. This dissertation presents a method for fusing time of flight(ToF) range data inherent to scanning LIDAR systems with the passive light field measurements of optical systems, extracting features which exploit information from each sensor, and solving the unique SLAM problem inherent to spacecraft proximity operations. Scale Space analysis is extended to unstructured 3D point clouds by means of an approximation to the Laplace Beltrami operator which computes the scale space on a manifold embedded in 3D object space using Gaussian convolutions based on a geodesic distance weighting. The construction of the scale space is shown to be equivalent to both the application of the diffusion equation to the surface data, as well as the surface evolution process which results from mean curvature flow. Geometric features are localized in regions of high spatial curvature or large diffusion displacements at multiple scales. The extracted interest points are associated with a local multi-field descriptor constructed from measured data in the object space. Defining features in object space instead of image space is shown to bean important step making the simultaneous consideration of co-registered texture and the associated geometry possible. These descriptors known as Multi-Field Diffusion Flow Signatures encode the shape, and multi-texture information of local neighborhoods in textured range data. Multi-Field Diffusion Flow Signatures display utility in difficult space scenarios including high contrast and saturating lighting conditions, bland and repeating textures, as well as non-Lambertian surfaces. The effectiveness and utility of Multi-Field Multi-Scale(MFMS) Features described by Multi-Field Diffusion Flow Signatures is evaluated using real data from proximity operation experiments performed at the Land Air and Space Robotics(LASR) Laboratory at Texas A&M University.Item Adaptation in a deep network(2011-05) Ruiz, Vito Manuel; Pillow, Jonathan W.; Miikkulainen, Risto; Fiete, Ila; Geisler, Wilson; Seidemann, EyalThough adaptational effects are found throughout the visual system, the underlying mechanisms and benefits of this phenomenon are not yet known. In this work, the visual system is modeled as a Deep Belief Network, with a novel “post-training” paradigm (i.e. training the network further on certain stimuli) used to simulate adaptation in vivo. An optional sparse variant of the DBN is used to help bring about meaningful and biologically relevant receptive fields, and to examine the effects of sparsification on adaptation in their own right. While results are inconclusive, there is some evidence of an attractive bias effect in the adapting network, whereby the network’s representations are drawn closer to the adapting stimulus. As a similar attractive bias is documented in human perception as a result of adaptation, there is thus evidence that the statistical properties underlying the adapting DBN also have a role in the adapting visual system, including efficient coding and optimal information transfer given limited resources. These results are irrespective of sparsification. As adaptation has never been tested directly in a neural network, to the author’s knowledge, this work sets a precedent for future experiments.Item Cerebral hemispheric reaction to single vision accuracy of music sightreading(Texas Tech University, 1977-05) Hoffman, Lynne RNot availableItem Democracy and values in public schools: A case study of founding members of the Visioning Institute of Texas(2010-12) Hindman, Janet L.; Klinker, JoAnn F.; McMillan, Sally; Valle, FernandoLittle empirical evidence existed that measured how democracy and democratic values were instilled in American schools. The problem of this qualitative collective case study was to investigate in what ways the efficacy and praxis of the superintendents of independent public school districts as founding members of the Public Education Visioning Institute of Texas had been influenced by their participation, how their vision for public education for their school districts and for Texas had changed through creative and innovative leadership, and how educational leadership interacted as either more of a science or as an art. Through qualitative methodology, this critical, narrative, and interpretive case study design explored what values were promoted by the Public Education Visioning Institute of Texas and if/how the superintendents as school leaders were implementing these values within their schools. Data was gathered through the use of qualitative tools of data collection, analysis, and management that included a questionnaire, interviews, observations, field notes, archival data documents, and the pilot study. This case study attempts to move from the public to the private (Denzin, 2001) through narrative and interpretive story to discover if the participants in the Public Education Visioning Institute of Texas had experienced epiphanies in regard to democracy and democratic values. Study findings indicated a transcendent epiphany in unity of values, vision, and passion for change among the superintendents through their leadership and vision and a constancy of purpose to improve public schools not only for their own students, but also for all children, and uncovered resources that informed their leadership practice. Findings confirm the need for further development of the Visioning Institute as a moral imperative to sustain democracy and democratic schools. To know who we are and where we are going in public education, a requisite need arises to conduct additional research in educational leadership as both science and as art.Item Discovery and representation of human strategies for visual search(2007-12) Tavassoli, Abtine, 1978-; Bovik, Alan C. (Alan Conrad), 1958-; Cormack, Lawrence K.Visual search can simply be defined as the task of looking for an object of interest in a visual environment. Due to its foveated nature, the human visual system succeeds at such task by making many discrete fixations linked by rapid eye movements called saccades. However, very little is known about how saccadic targets (fixation loci) are selected by the brain in such naturalistic tasks. Discoveries to be made are not only invaluable to the field of vision science but are very important in designing automated vision systems, which to this day lag in performance vis-à-vis human observers. What I have sought to accomplish in this dissertation has been to reveal previously unknown saccadic targeting and target selection strategies used by human observers in naturalistic visual search tasks. My driving goal has been to understand how the brain selects fixation loci and target candidates upon fixation, with the objective of using these findings for automated fixation selection algorithms employed for visual search. I have proposed a novel and efficient technique akin to psychophysical reverse correlation to study human observer strategies in locating low-contrast targets under a variety of experimental conditions. My technique has successfully been used to study saccadic programming and target selection in various experimental conditions, including visual searches for targets with known characteristics, targets whose orientation attributes are not known a priori, and targets containing multiple orientations. I have found visual guidance in saccadic targeting and target selection under all experimental conditions, revealed by observers' selectivity for spatial frequencies and/or orientations of stimuli close to that of the target. I have shown that under uncertainty, observers rely on known target characteristics to direct their saccades and to select target candidates upon foveal scrutiny. Moreover, I have demonstrated that multiple orientation characteristics of targets are represented in observer search strategies, modulated by their sensitivity / selectivity for each orientation. Some of my findings have been applied towards applications for automated visual search algorithms.Item The leaf identification problem : natural scene statistics and human performance(2010-05) Ing, Almon David; Geisler, Wilson S.; Diehl, Randy L.; Cormack, Larry K.; Gilden, David L.; Cummings, Molly E.For animals with advanced nervous systems, survival and reproduction can depend upon accurate perception of the environment. To understand how a perceptual system should solve a perception task, it is important to consider designs for an ideal observer, a theoretical system that solves a perception task in an optimal way given specific constraints. I studied three specific classification tasks related to the problem of identifying and segmenting leaves in foliage-rich images. In order to derive the ideal observers for these tasks, I created a database of hand-segmented leaves which served to define the ground-truth for these tasks. I also created a new method that uses the ground-truth as a basis for performing statistical inference (classification) in a nearly optimal way. This made it possible for me to approximate ideal observers by approximating an optimal classifier for each task. I also conducted psychophysical experiments to measure human performance in these tasks. The results provide information about how the human visual system should and does interpret foliage-rich images.Item Manipulating spatial frequency to understand global and local information processing in 7-month-old infants(2009-08) Gora, Keith Matthew; Cohen, Leslie B.It has been shown that infants build representations of their visual world by forming relations among its parts. However little is known about how they select the parts to relate. One possibility is that while constructing their visual world part by part they are also decomposing it, using finer and finer parts. One way to test this theory is to simply control the parts infants see. This easiest way to do this is to filter real life objects of their high and low spatial frequencies. High spatial frequencies provide information about the smaller parts where as low spatial frequencies provide information about the larger ones. By removing high or low spatial frequency we can control the coarseness of their representation and ultimately determine the level at which they function best. The present study examined infants’ ability to use high and low spatial frequencies to discriminate between objects. Infants were habituated and tested using a combination of high and low spatial frequency images. Only infants experiencing a consistent spatial frequency across habituation and test were able to discriminate between objects. Infants were also better at discriminating between objects containing high spatial frequencies. In a second study designed to be more true to life, infants were habituated to broadband images and tested using high or low spatial frequencies. This time infants did not discriminate between objects but they did look longer at low spatial frequency information than at the high. From these findings we can conclude that infants use both high and low spatial frequency information when discriminating objects, and that in certain cases one frequency may become more important than the other. The spatial frequency they use may be dependent on the context of the task. Numerous studies have shown that adults prioritize high and low spatial frequency information depending on how fast they want to process the object, the amount of detail they require, and whether they used high or low spatial frequency information during previous experiences. Infants may be similar. At times they may emphasize low spatial frequency information and the big picture. At other times they may emphasize high spatial frequency information and the detail. More studies examining how infants select information for processing are necessary and spatial frequency will likely to be an important tool in the investigation.Item Measuring visual stimulation and attention signals in human superior colliculus using high-resolution fMRI(2013-05) Katyal, Sucharit; Ress, David BruceThe superior colliculus (SC) is a laminated oculomotor structure in the midbrain. In non-human primates SC has long been known to contain a retinotopically-organized map of visual stimulation in its superficial layers, which is aligned to a map of saccadic eye movements in the deeper layers. Microstimulation and electrophysiology experiments have shown that SC also plays a key role in covert visuospatial attention and suggest that attentional modulation also occurs in a retinotopic manner. Retinotopic organization of the visual field can be non-invasively mapped in humans using functional MRI with a technique called phase-encoded retinotopy. In this technique, rotating wedges and expanding rings of visual stimuli are used to map the polar angle and eccentricity dimensions of a polar coordinates system, respectively. A similar technique can also be used to map spatial attention by keeping the visual stimulus constant and cueing subjects to attend to apertures of rotating wedges and expanding rings within the stimulus. A previous study using fMRI has shown the polar angle representation of visual stimulation in human SC but was unable to find a representation of eccentricity. This work uses high-resolution fMRI along with special surface analysis techniques developed in our lab to demonstrate maps of both polar angle and eccentricity for visual stimulation. Moreover, visual attention is also shown to be topographically organized within SC and in registration with visual stimulation. Finally, in human visual cortex, fMRI is known to show activity for sustained spatial attention even in the absence of a significant visual stimulus, an attentional "base response". In this work, SC is shown to exhibit a similar sustained attention base response using a threshold-contrast detection paradigm. This base response was compared with a response for attention with visual stimulation. The peak amplitude of the base response occurred more deeply within SC tissue than the peak for attention with stimulation. It is proposed that this reflects the specific attentional enhancement of the deeper visuomotor neurons, which are hypothesized to be a direct neuronal correlate of the oculomotor theory of attention.Item Naturalistic depth perception(2015-05) McCann, Brian Clark; Geisler, Wilson S.; Hayhoe, Mary; Huk, Alex; Cormack, Larry; Bovik, AlMaking inferences about the 3-dimensional spatial structure of natural scenes is a critical visual function. While spatial discrimination both in depth and on the image plane has been well characterized for simple stimuli, little is known about our ability to discriminate depth in natural scenes, particularly at far distances. To begin filling in this gap we: (i) developed a database of 80 stereoscopic images paired with the corresponding measured distance information, (ii) used these scenes as psychophysical stimuli and measured near-far discrimination acuity in 4 observers as a function of distance and the visual angle separating the targets, (iii) made additional measurements under patched-eye (monocular) viewing conditions to evaluate the importance of binocular vision in depth discrimination as a function of viewing geometries. We find that binocular thresholds are roughly a constant Weber fraction of the distance for absolute distances ranging from 4 to 28 meters. Further, measured thresholds were around 1% for small separations, and increased to 4% for stimuli separated by 10 deg. Thus, the ability to discriminate depth in natural scenes is very good out to considerable distances. To investigate the basis of this discrimination ability, monocular thresholds were measured. We found that monocular thresholds were elevated for distances less than 15 meters, but were comparable to binocular thresholds for greater distances. Accurate depth perception depends on combining (fusing) multiple sources of sensory information. Thus binocular thresholds probably involve fusing separate monocular and disparity-derived estimates. Under the assumption of Gaussian distributed independent estimates, Bayes rule provides a simple reliability-weighted summation model of cue combination. Using disparity threshold measurements by Blakemore (1970), and the current monocular thresholds, parameter-free predictions were generated for the current binocular thresholds. These predictions were in broad agreement with the data, suggesting that the disparity and monocular cues are separable and combined optimally in natural scenes.Item Pattern detection in natural images(2016-12) Sebastian, Stephen P.; Geisler, Wilson S.; Bovik, Alan; Hayhoe, Mary; Cormack, Lawrence K; Seideman, EyalA fundamental visual task is to detect target objects within a background scene. Using relatively simple stimuli, vision science has identified several major factors that affect detection thresholds, such as the luminance of the background, the contrast of the background, the spatial similarity of the background to the target, and uncertainty due to random variations in the properties of the background and in the amplitude of the target. Here I use a new experimental approach together with a theoretical analysis based on signal detection theory, to discover how these factors affect detection in natural scenes. First, I sorted a large collection of natural image backgrounds into multidimensional bins, where each bin corresponds to a narrow range of luminance, contrast and similarity. Detection thresholds were measured by randomly sampling a natural image background from a bin on each trial. In low uncertainty conditions both the bin and the amplitude of the target were blocked and in high uncertainty conditions the bin and amplitude varied randomly on each trial. I found that thresholds increased approximately linearly along all three dimensions and that detection accuracy was unaffected by bin and amplitude uncertainty. The entire set of results was predicted from first principles by a normalized matched template detector, where the dynamic normalizing factor follows directly from the statistical properties of the natural backgrounds. This model assumed that the properties of the background underneath the target were constant across the image, but in natural images this is often not the case. Therefore, in a separate experiment, I measured detection thresholds on backgrounds where the contrast was modulated underneath the target. I found that varying the contrast underneath the target signal had a substantial effect on detectability, and that the pattern of results was predicted by an ideal observer that weighted its response based on an estimate of the local contrast (under the target). This suggests that the human visual system is able to use the varying properties of the background under the target in an near optimal way. Taken together, the results provide a new explanation for some classic laws of psychophysics and their underlying neural mechanisms.Item Picture of a decision : neural correlates of perceptual decisions by population activity in primary visual cortex of primates(2012-12) Michelson, Charles Andrew; Seidemann, Eyal; Geisler, Wilson; Huk, Alex; Cormack, Lawrence; Heeger, DavidThe goal of this dissertation is to advance our understanding of perceptual decisions. A perceptual decision is a decision that is based on sensory evidence. For example, a monkey must choose whether to eat a food item based on sensory information such as its color, texture or odor. Previous research has identified regions of the brain involved in the encoding of sensory information as well as areas involved in transforming encoded representations of stimuli into signals useful for forming decisions about those stimuli. Researchers carried out much of this work by painstakingly observing the firing of single neurons or small groups of neurons while a subject performs a task, and used this information to propose and evaluate models of the decision process. However, previous studies have also shown that sensory stimuli are encoded in a distributed fashion across populations of neurons rather than in individual or small groups of neurons. Thus it is likely that populations of neurons, rather than individual neurons, are responsible for the formation of a decision. Here I directly address the question of how decisions are formed through the collective activity of populations of cortical neurons. I used voltage-sensitive dye imaging, a technique that allowed me to simultaneously monitor millions of neurons in sensory cortex, while primates performed a simple yet challenging binary decision task. I also used psychophysical techniques and computational modeling to address fundamental questions about the nature of perceptual decisions. Here I provide new evidence that choice-related neural activity is distributed across a broad population of neurons, and that most of the decision-related neural activity occurs as early as primary sensory cortex. I propose a physiological and computational mechanism for the subject’s decision process in our task, and demonstrate that this process is likely sub-optimal due to intrinsic uncertainty about sensory stimuli. Overall, I conclude that in our task, perceptual decisions are likely to be limited primarily by the quality of evidence that resides in populations of neurons in sensory cortex, secondarily by sub-optimal decoding of these sensory signals, and to a much lesser extent by additional downstream neural variability.Item Statistical analysis and selection of visual fixations(2005) Rajashekar, Umesh; Bovik, Alan C. (Alan Conrad), 1958-; Cormack, Lawrence K.Item The effect of prolonged exposure to visual and auditory stimulation on form discrimination(Texas Tech University, 1966-08) Brummett, Richard DavidNot available