Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

The employment effects of high-technology : a case study of machine vision /

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Effect of uncorrected astigmatism on vision

PURPOSE: To examine the effect of uncorrected astigmatism in older adults. SETTING: University Vision Clinic METHOD: Twenty-one healthy presbyopes, aged 58.9±2.8 years, had astigmatism of 0.0 to -4.0 x 90?DC and -3.0DC of cylinder at 90?, 180? and 45? induced with spectacle lenses, with the mean spherical equivalent compensated to plano, in random order. Visual acuity was assessed binocularly using a computerised test chart at 95%, 50% and 10% contrast. Near acuity and reading speed were measured using standardised reading texts. Light scatter was quantified with the cQuant and driving reaction times with a computer simulator. Finally visual clarity of a mobile phone and computer screen was subjectively rated. RESULTS: Distance visual acuity decreased with increasing uncorrected astigmatic power (F=174.50, p<0.001) and was reduced at lower contrasts (F=170.77, p<0.001). Near visual acuity and reading speed also decreased with increasing uncorrected astigmatism power (p<0.001). Light scatter was not significantly affected by uncorrected astigmatism (p>0.05), but the reliability and variability of measurements decreased with increasing uncorrected astigmatic power (p<0.05). Driving simulator performance was also unaffected by uncorrected astigmatism (p>0.05), but subjective rating of clarity decreased with increasing uncorrected astigmatic power (p<0.001). Uncorrected astigmatism at 45? or 180? orientation resulted in a worse distance and near visual acuity, and subjective rated clarity than 90? orientation (p<0.05). CONCLUSION: Uncorrected astigmatism, even as low as 1.0DC, causes a significant burden on a patient’s vision. If left uncorrected, this could impact significantly on their independence, quality of life and wellbeing.

Bars and edges: what makes a feature for human vision?

There have been two main approaches to feature detection in human and computer vision - luminance-based and energy-based. Bars and edges might arise from peaks of luminance and luminance gradient respectively, or bars and edges might be found at peaks of local energy, where local phases are aligned across spatial frequency. This basic issue of definition is important because it guides more detailed models and interpretations of early vision. Which approach better describes the perceived positions of elements in a 3-element contour-alignment task? We used the class of 1-D images defined by Morrone and Burr in which the amplitude spectrum is that of a (partially blurred) square wave and Fourier components in a given image have a common phase. Observers judged whether the centre element (eg ±458 phase) was to the left or right of the flanking pair (eg 0º phase). Lateral offset of the centre element was varied to find the point of subjective alignment from the fitted psychometric function. This point shifted systematically to the left or right according to the sign of the centre phase, increasing with the degree of blur. These shifts were well predicted by the location of luminance peaks and other derivative-based features, but not by energy peaks which (by design) predicted no shift at all. These results on contour alignment agree well with earlier ones from a more explicit feature-marking task, and strongly suggest that human vision does not use local energy peaks to locate basic first-order features. [Supported by the Wellcome Trust (ref: 056093)]

Edge coding in human vision: a psychophysical and computational investigation

This thesis presents a study of how edges are detected and encoded by the human visual system. The study begins with theoretical work on the development of a model of edge processing, and includes psychophysical experiments on humans, and computer simulations of these experiments, using the model. The first chapter reviews the literature on edge processing in biological and machine vision, and introduces the mathematical foundations of this area of research. The second chapter gives a formal presentation of a model of edge perception that detects edges and characterizes their blur, contrast and orientation, using Gaussian derivative templates. This model has previously been shown to accurately predict human performance in blur matching tasks with several different types of edge profile. The model provides veridical estimates of the blur and contrast of edges that have a Gaussian integral profile. Since blur and contrast are independent parameters of Gaussian edges, the model predicts that varying one parameter should not affect perception of the other. Psychophysical experiments showed that this prediction is incorrect: reducing the contrast makes an edge look sharper; increasing the blur reduces the perceived contrast. Both of these effects can be explained by introducing a smoothed threshold to one of the processing stages of the model. It is shown that, with this modification,the model can predict the perceived contrast and blur of a number of edge profiles that differ markedly from the ideal Gaussian edge profiles on which the templates are based. With only a few exceptions, the results from all the experiments on blur and contrast perception can be explained reasonably well using one set of parameters for each subject. In the few cases where the model fails, possible extensions to the model are discussed.

The vision strategy of golf putting

Golfers, coaches and researchers alike, have all keyed in on golf putting as an important aspect of overall golf performance. Of the three principle putting tasks (green reading, alignment and the putting action phase), the putting action phase has attracted the most attention from coaches, players and researchers alike. This phase includes the alignment of the club with the ball, the swing, and ball contact. A significant amount of research in this area has focused on measuring golfer’s vision strategies with eye tracking equipment. Unfortunately this research suffers from a number of shortcomings, which limit its usefulness. The purpose of this thesis was to address some of these shortcomings. The primary objective of this thesis was to re-evaluate golfer’s putting vision strategies using binocular eye tracking equipment and to define a new, optimal putting vision strategy which was associated with both higher skill and success. In order to facilitate this research, bespoke computer software was developed and validated, and new gaze behaviour criteria were defined. Additionally, the effects of training (habitual) and competition conditions on the putting vision strategy were examined, as was the effect of ocular dominance. Finally, methods for improving golfer’s binocular vision strategies are discussed, and a clinical plan for the optometric management of the golfer’s vision is presented. The clinical management plan includes the correction of fundamental aspects of golfers’ vision, including monocular refractive errors and binocular vision defects, as well as enhancement of their putting vision strategy, with the overall aim of improving performance on the golf course. This research has been undertaken in order to gain a better understanding of the human visual system and how it relates to the sport performance of golfers specifically. Ultimately, the analysis techniques and methods developed are applicable to the assessment of visual performance in all sports.

A method for enhancing digital information displayed to computer users with visual refractive errors via spatial and spectral processing

This research pursued the conceptualization, implementation, and verification of a system that enhances digital information displayed on an LCD panel to users with visual refractive errors. The target user groups for this system are individuals who have moderate to severe visual aberrations for which conventional means of compensation, such as glasses or contact lenses, does not improve their vision. This research is based on a priori knowledge of the user's visual aberration, as measured by a wavefront analyzer. With this information it is possible to generate images that, when displayed to this user, will counteract his/her visual aberration. The method described in this dissertation advances the development of techniques for providing such compensation by integrating spatial information in the image as a means to eliminate some of the shortcomings inherent in using display devices such as monitors or LCD panels. Additionally, physiological considerations are discussed and integrated into the method for providing said compensation. In order to provide a realistic sense of the performance of the methods described, they were tested by mathematical simulation in software, as well as by using a single-lens high resolution CCD camera that models an aberrated eye, and finally with human subjects having various forms of visual aberrations. Experiments were conducted on these systems and the data collected from these experiments was evaluated using statistical analysis. The experimental results revealed that the pre-compensation method resulted in a statistically significant improvement in vision for all of the systems. Although significant, the improvement was not as large as expected for the human subject tests. Further analysis suggest that even under the controlled conditions employed for testing with human subjects, the characterization of the eye may be changing. This would require real-time monitoring of relevant variables (e.g. pupil diameter) and continuous adjustment in the pre-compensation process to yield maximum viewing enhancement.

A method for enhancing digital information displayed to computer users with visual refractive errors via spatial and spectral processing

This research pursued the conceptualization, implementation, and verification of a system that enhances digital information displayed on an LCD panel to users with visual refractive errors. The target user groups for this system are individuals who have moderate to severe visual aberrations for which conventional means of compensation, such as glasses or contact lenses, does not improve their vision. This research is based on a priori knowledge of the user's visual aberration, as measured by a wavefront analyzer. With this information it is possible to generate images that, when displayed to this user, will counteract his/her visual aberration. The method described in this dissertation advances the development of techniques for providing such compensation by integrating spatial information in the image as a means to eliminate some of the shortcomings inherent in using display devices such as monitors or LCD panels. Additionally, physiological considerations are discussed and integrated into the method for providing said compensation. In order to provide a realistic sense of the performance of the methods described, they were tested by mathematical simulation in software, as well as by using a single-lens high resolution CCD camera that models an aberrated eye, and finally with human subjects having various forms of visual aberrations. Experiments were conducted on these systems and the data collected from these experiments was evaluated using statistical analysis. The experimental results revealed that the pre-compensation method resulted in a statistically significant improvement in vision for all of the systems. Although significant, the improvement was not as large as expected for the human subject tests. Further analysis suggest that even under the controlled conditions employed for testing with human subjects, the characterization of the eye may be changing. This would require real-time monitoring of relevant variables (e.g. pupil diameter) and continuous adjustment in the pre-compensation process to yield maximum viewing enhancement.

CASIMIRO: a robot head for human-computer interaction

The physical appearance and behavior of a robot is an important asset in terms of Human-Computer Interaction. Multimodality is also fundamental, as we humans usually expect to interact in a natural way with voice, gestures, etc. People approach complex interaction devices with stances similar to those used in their interaction with other people. In this paper we describe a robot head, currently under development, that aims to be a multimodal (vision, voice, gestures,...) perceptual user interface.