361 resultados para Visual estimate

em Queensland University of Technology - ePrints Archive


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This study is the first to investigate the effect of prolonged reading on reading performance and visual functions in students with low vision. The study focuses on one of the most common modes of achieving adequate magnification for reading by students with low vision, their close reading distance (proximal or relative distance magnification). Close reading distances impose high demands on near visual functions, such as accommodation and convergence. Previous research on accommodation in children with low vision shows that their accommodative responses are reduced compared to normal vision. In addition, there is an increased lag of accommodation for higher stimulus levels as may occur at close reading distance. Reduced accommodative responses in low vision and higher lag of accommodation at close reading distances together could impact on reading performance of students with low vision especially during prolonged reading tasks. The presence of convergence anomalies could further affect reading performance. Therefore, the aims of the present study were 1) To investigate the effect of prolonged reading on reading performance in students with low vision 2) To investigate the effect of prolonged reading on visual functions in students with low vision. This study was conducted as cross-sectional research on 42 students with low vision and a comparison group of 20 students with normal vision, aged 7 to 20 years. The students with low vision had vision impairments arising from a range of causes and represented a typical group of students with low vision, with no significant developmental delays, attending school in Brisbane, Australia. All participants underwent a battery of clinical tests before and after a prolonged reading task. An initial reading-specific history and pre-task measurements that included Bailey-Lovie distance and near visual acuities, Pelli-Robson contrast sensitivity, ocular deviations, sensory fusion, ocular motility, near point of accommodation (pull-away method), accuracy of accommodation (Monocular Estimation Method (MEM)) retinoscopy and Near Point of Convergence (NPC) (push-up method) were recorded for all participants. Reading performance measures were Maximum Oral Reading Rates (MORR), Near Text Visual Acuity (NTVA) and acuity reserves using Bailey-Lovie text charts. Symptoms of visual fatigue were assessed using the Convergence Insufficiency Symptom Survey (CISS) for all participants. Pre-task measurements of reading performance and accuracy of accommodation and NPC were compared with post-task measurements, to test for any effects of prolonged reading. The prolonged reading task involved reading a storybook silently for at least 30 minutes. The task was controlled for print size, contrast, difficulty level and content of the reading material. Silent Reading Rate (SRR) was recorded every 2 minutes during prolonged reading. Symptom scores and visual fatigue scores were also obtained for all participants. A visual fatigue analogue scale (VAS) was used to assess visual fatigue during the task, once at the beginning, once at the middle and once at the end of the task. In addition to the subjective assessments of visual fatigue, tonic accommodation was monitored using a photorefractor (PlusoptiX CR03™) every 6 minutes during the task, as an objective assessment of visual fatigue. Reading measures were done at the habitual reading distance of students with low vision and at 25 cms for students with normal vision. The initial history showed that the students with low vision read for significantly shorter periods at home compared to the students with normal vision. The working distances of participants with low vision ranged from 3-25 cms and half of them were not using any optical devices for magnification. Nearly half of the participants with low vision were able to resolve 8-point print (1M) at 25 cms. Half of the participants in the low vision group had ocular deviations and suppression at near. Reading rates were significantly reduced in students with low vision compared to those of students with normal vision. In addition, there were a significantly larger number of participants in the low vision group who could not sustain the 30-minute task compared to the normal vision group. However, there were no significant changes in reading rates during or following prolonged reading in either the low vision or normal vision groups. Individual changes in reading rates were independent of their baseline reading rates, indicating that the changes in reading rates during prolonged reading cannot be predicted from a typical clinical assessment of reading using brief reading tasks. Contrary to previous reports the silent reading rates of the students with low vision were significantly lower than their oral reading rates, although oral and silent reading was assessed using different methods. Although the visual acuity, contrast sensitivity, near point of convergence and accuracy of accommodation were significantly poorer for the low vision group compared to those of the normal vision group, there were no significant changes in any of these visual functions following prolonged reading in either group. Interestingly, a few students with low vision (n =10) were found to be reading at a distance closer than their near point of accommodation. This suggests a decreased sensitivity to blur. Further evaluation revealed that the equivalent intrinsic refractive errors (an estimate of the spherical dioptirc defocus which would be expected to yield a patient’s visual acuity in normal subjects) were significantly larger for the low vision group compared to those of the normal vision group. As expected, accommodative responses were significantly reduced for the low vision group compared to the expected norms, which is consistent with their close reading distances, reduced visual acuity and contrast sensitivity. For those in the low vision group who had an accommodative error exceeding their equivalent intrinsic refractive errors, a significant decrease in MORR was found following prolonged reading. The silent reading rates however were not significantly affected by accommodative errors in the present study. Suppression also had a significant impact on the changes in reading rates during prolonged reading. The participants who did not have suppression at near showed significant decreases in silent reading rates during and following prolonged reading. This impact of binocular vision at near on prolonged reading was possibly due to the high demands on convergence. The significant predictors of MORR in the low vision group were age, NTVA, reading interest and reading comprehension, accounting for 61.7% of the variances in MORR. SRR was not significantly influenced by any factors, except for the duration of the reading task sustained; participants with higher reading rates were able to sustain a longer reading duration. In students with normal vision, age was the only predictor of MORR. Participants with low vision also reported significantly greater visual fatigue compared to the normal vision group. Measures of tonic accommodation however were little influenced by visual fatigue in the present study. Visual fatigue analogue scores were found to be significantly associated with reading rates in students with low vision and normal vision. However, the patterns of association between visual fatigue and reading rates were different for SRR and MORR. The participants with low vision with higher symptom scores had lower SRRs and participants with higher visual fatigue had lower MORRs. As hypothesized, visual functions such as accuracy of accommodation and convergence did have an impact on prolonged reading in students with low vision, for students whose accommodative errors were greater than their equivalent intrinsic refractive errors, and for those who did not suppress one eye. Those students with low vision who have accommodative errors higher than their equivalent intrinsic refractive errors might significantly benefit from reading glasses. Similarly, considering prisms or occlusion for those without suppression might reduce the convergence demands in these students while using their close reading distances. The impact of these prescriptions on reading rates, reading interest and visual fatigue is an area of promising future research. Most importantly, it is evident from the present study that a combination of factors such as accommodative errors, near point of convergence and suppression should be considered when prescribing reading devices for students with low vision. Considering these factors would also assist rehabilitation specialists in identifying those students who are likely to experience difficulty in prolonged reading, which is otherwise not reflected during typical clinical reading assessments.

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Position estimation for planetary rovers has been typically limited to odometry based on proprioceptive measurements such as the integration of distance traveled and measurement of heading change. Here we present and compare two methods of online visual odometry suited for planetary rovers. Both methods use omnidirectional imagery to estimate motion of the rover. One method is based on robust estimation of optical flow and subsequent integration of the flow. The second method is a full structure-from-motion solution. To make the comparison meaningful we use the same set of raw corresponding visual features for each method. The dataset is an sequence of 2000 images taken during a field experiment in the Atacama desert, for which high resolution GPS ground truth is available.

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Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3D)-edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long-term robust operation. Previous 3D-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions.

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This paper presents a vision-based method of vehicle localisation that has been developed and tested on a large forklift type robotic vehicle which operates in a mainly outdoor industrial setting. The localiser uses a sparse 3D edgemap of the environment and a particle filter to estimate the pose of the vehicle. The vehicle operates in dynamic and non-uniform outdoor lighting conditions, an issue that is addressed by using knowledge of the scene to intelligently adjust the camera exposure and hence improve the quality of the information in the image. Results from the industrial vehicle are shown and compared to another laser-based localiser which acts as a ground truth. An improved likelihood metric, using peredge calculation, is presented and has shown to be 40% more accurate in estimating rotation. Visual localization results from the vehicle driving an arbitrary 1.5km path during a bright sunny period show an average position error of 0.44m and rotation error of 0.62deg.

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In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the Autonomous Tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.

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Purpose: To compare accuracies of different methods for calculating human lens power when lens thickness is not available. Methods: Lens power was calculated by four methods. Three methods were used with previously published biometry and refraction data of 184 emmetropic and myopic eyes of 184 subjects (age range [18, 63] years, spherical equivalent range [–12.38, +0.75] D). These three methods consist of the Bennett method, which uses lens thickness, our modification of the Stenström method and the Bennett¬Rabbetts method, both of which do not require knowledge of lens thickness. These methods include c constants, which represent distances from lens surfaces to principal planes. Lens powers calculated with these methods were compared with those calculated using phakometry data available for a subgroup of 66 emmetropic eyes (66 subjects). Results: Lens powers obtained from the Bennett method corresponded well with those obtained by phakometry for emmetropic eyes, although individual differences up to 3.5D occurred. Lens powers obtained from the modified¬Stenström and Bennett¬Rabbetts methods deviated significantly from those obtained with either the Bennett method or phakometry. Customizing the c constants improved this agreement, but applying these constants to the entire group gave mean lens power differences of 0.71 ± 0.56D compared with the Bennett method. By further optimizing the c constants, the agreement with the Bennett method was within ± 1D for 95% of the eyes. Conclusion: With appropriate constants, the modified¬Stenström and Bennett¬Rabbetts methods provide a good approximation of the Bennett lens power in emmetropic and myopic eyes.

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This paper presents a reactive Sense and Avoid approach using spherical image-based visual servoing. Avoidance of point targets in the lateral or vertical plane is achieved without requiring an estimate of range. Simulated results for static and dynamic targets are provided using a realistic model of a small fixed wing unmanned aircraft.

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This paper presents a reactive collision avoidance method for small unmanned rotorcraft using spherical image-based visual servoing. Only a single point feature is used to guide the aircraft in a safe spiral like trajectory around the target, whilst a spherical camera model ensures the target always remains visible. A decision strategy to stop the avoidance control is derived based on the properties of spiral like motion, and the effect of accurate range measurements on the control scheme is discussed. We show that using a poor range estimate does not significantly degrade the collision avoidance performance, thus relaxing the need for accurate range measurements. We present simulated and experimental results using a small quad rotor to validate the approach.

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Purpose. The purpose of this article was to present methods capable of estimating the size and shape of the human eye lens without resorting to phakometry or magnetic resonance imaging (MRI). Methods. Previously published biometry and phakometry data of 66 emmetropic eyes of 66 subjects (age range [18, 63] years, spherical equivalent range [−0.75, +0.75] D) were used to define multiple linear regressions for the radii of curvature and thickness of the lens, from which the lens refractive index could be derived. MRI biometry was also available for a subset of 30 subjects, from which regressions could be determined for the vertex radii of curvature, conic constants, equatorial diameter, volume, and surface area. All regressions were compared with the phakometry and MRI data; the radii of curvature regressions were also compared with a method proposed by Bennett and Royston et al. Results. The regressions were in good agreement with the original measurements. This was especially the case for the regressions of lens thickness, volume, and surface area, which each had an R2 > 0.6. The regression for the posterior radius of curvature had an R2 < 0.2, making this regression unreliable. For all other regressions we found 0.25 < R2 < 0.6. The Bennett-Royston method also produced a good estimation of the radii of curvature, provided its parameters were adjusted appropriately. Conclusions. The regressions presented in this article offer a valuable alternative in case no measured lens biometry values are available; however care must be taken for possible outliers.

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Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

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This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.