Desarrollo de arquitecturas para procesamiento de control de la mirada en sistemas de visión activa con resolución espacial variable

En esta tesis se aborda la implementación de un sistema completo de visión activa, en el que se capturan y generan imágenes de resolución espacial variable. Todo el sistema se integra en un sólo dispositivo del tipo AP SoC (All Programmable System on Chip), lo que nos permite llevar a cabo el codiseño hardware-software del mismo, implementando en la parte lógica los bloques de preprocesado intensivo, y en la parte software los algoritmos de procesado de control más complejo. El objetivo es que, trabajando con un campo visual del orden de Megapíxeles, se pueda procesar una tasa moderada de imágenes por segundo. Las imágenes multiresolución se generan a partir de sensores de resolución uniforme con una latencia nula, lo que permite tener preparada la imagen de resolución variable en el mismo instante en que se ha terminado de capturar la imagen original. Como innovación con respecto a las primeras contribuciones relacionadas con esta Tesis, se procesan imágenes con toda la información de color. Esto implica la necesidad de diseñar conversores entre espacios de color distintos, para adecuar la información al tipo de procesado que se va a realizar con ella. Estos bloques se integran sin alterar la latencia de entrega de los sucesivos fotogramas. El procesamiento de estas imágenes multirresolución genera un mapa de saliencia que permite mover la fóvea hacía la región considerada como más relevante en la escena. El contenido de la imagen se estructura en una jerarquía de niveles de abstracción. A diferencia de otras arquitecturas de este tipo, como son la pirámide regular y el polígono foveal, en las que se trabaja con imágenes de resolución uniforme en los distintos niveles de la jerarquía, la pirámide irregular foveal que se propone en esta tesis combina las ideas de trabajar con una imagen realmente multirresolución, que incluya el campo de visión completo que abarcan sensor y óptica, con el procesamiento jerárquico propio de las pirámides irregulares. Para ello en esta tesis se propone la implementación de un algoritmo de diezmado irregular que, tomando como base la imagen multirresolución, dará como resultado una estructura piramidal donde los distintos niveles no son imágenes sino grafos orientados a la resolución del problema de segmentación y estimación de saliencia. Todo el sistema se integra en torno a la arquitectura de bus AXI, que permite conectar entre si todos los cores desarrollados en la parte lógica, así como el acceso a la memoria compartida con los algoritmos implementados en la parte software. Esto es posible gracias a los bloques de acceso directo a memoria AXI-VDMA, en una propuesta de configuración que permite tanto la integración perfectamente coordinada de la transferencia de la imagen multirresolución generada a la zona de trabajo del algoritmo de segmentación como su recuperación para la posterior visualización del resultado del proceso, y todo ello con una tasa de trabajo que mejora los resultados de plataformas similares

A Modular and Open-Source Framework for Virtual Reality Visualisation and Interaction in Bioimaging

Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data from analysis of such data or simulations. The advent of new imaging technologies, such as lightsheet microscopy, has resulted in the users being confronted with an ever-growing amount of data, with even terabytes of imaging data created within a day. With the possibility of gentler and more high-performance imaging, the spatiotemporal complexity of the model systems or processes of interest is increasing as well. Visualisation is often the first step in making sense of this data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualisations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we present scenery, a modular and extensible visualisation framework for the Java VM that can handle mesh and large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms, and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features, and discuss its use with VR/AR hardware and in distributed rendering. In addition to the visualisation framework, we present a series of case studies, where scenery can provide tangible benefit in developmental and systems biology: With Bionic Tracking, we demonstrate a new technique for tracking cells in 4D volumetric datasets via tracking eye gaze in a virtual reality headset, with the potential to speed up manual tracking tasks by an order of magnitude. We further introduce ideas to move towards virtual reality-based laser ablation and perform a user study in order to gain insight into performance, acceptance and issues when performing ablation tasks with virtual reality hardware in fast developing specimen. To tame the amount of data originating from state-of-the-art volumetric microscopes, we present ideas how to render the highly-efficient Adaptive Particle Representation, and finally, we present sciview, an ImageJ2/Fiji plugin making the features of scenery available to a wider audience.:Abstract Foreword and Acknowledgements Overview and Contributions Part 1 - Introduction 1 Fluorescence Microscopy 2 Introduction to Visual Processing 3 A Short Introduction to Cross Reality 4 Eye Tracking and Gaze-based Interaction Part 2 - VR and AR for System Biology 5 scenery — VR/AR for Systems Biology 6 Rendering 7 Input Handling and Integration of External Hardware 8 Distributed Rendering 9 Miscellaneous Subsystems 10 Future Development Directions Part III - Case Studies C A S E S T U D I E S 11 Bionic Tracking: Using Eye Tracking for Cell Tracking 12 Towards Interactive Virtual Reality Laser Ablation 13 Rendering the Adaptive Particle Representation 14 sciview — Integrating scenery into ImageJ2 & Fiji Part IV - Conclusion 15 Conclusions and Outlook Backmatter & Appendices A Questionnaire for VR Ablation User Study B Full Correlations in VR Ablation Questionnaire C Questionnaire for Bionic Tracking User Study List of Tables List of Figures Bibliography Selbstständigkeitserklärun

Approximate Spatial Layout Processing in the Visual System: Modeling Texture-Based Segmentation and Shape Estimation

Moving through the environment, grasping objects, orienting oneself, and countless other tasks all require information about spatial organization. This in turn requires determining where surfaces, objects and other elements of a scene are located and how they are arranged. Humans and other animals can extract spatial organization from vision rapidly and automatically. To better understand this capability, it would be useful to know how the visual system can make an initial estimate of the spatial layout. Without time or opportunity for a more careful analysis, a rough estimate may be all that the system can extract. Nevertheless, rough spatial information may be sufficient for many purposes, even if it is devoid of details that are important for tasks such as object recognition. The human visual system uses many sources of information for estimating layout. Here I focus on one source in particular: visual texture. I present a biologically reasonable, computational model of how the system can exploit patterns of texture for performing two basic tasks in spatial layout processing: locating possible surfaces in the visual input, and estimating their approximate shapes. Separately, these two tasks have been studied extensively, but they have not previously been examined together in the context of a model grounded in neurophysiology and psychophysics. I show that by integrating segmentation and shape estimation, a system can share information between these processes, allowing the processes to constrain and inform each other as well as save on computations. The model developed here begins with the responses of simulated complex cells of the primary visual cortex, and combines a weak membrane/functional minimization approach to segmentation with a shape estimation method based on tracking changes in the average dominant spatial frequencies across a surface. It includes mechanisms for detecting untextured areas and flat areas in an input image. In support of the model, I present a software simulation that can perform texture-based segmentation and shape estimation on images containing multiple, curved, textured surfaces.Ph.D.Applied SciencesBiological SciencesCognitive psychologyComputer scienceNeurosciencesPsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/131446/2/9909908.pd

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog

Improving command selection in smart environments by exploiting spatial constancy

With the a steadily increasing number of digital devices, our environments are becoming increasingly smarter: we can now use our tablets to control our TV, access our recipe database while cooking, and remotely turn lights on and off. Currently, this Human-Environment Interaction (HEI) is limited to in-place interfaces, where people have to walk up to a mounted set of switches and buttons, and navigation-based interaction, where people have to navigate on-screen menus, for example on a smart-phone, tablet, or TV screen. Unfortunately, there are numerous scenarios in which neither of these two interaction paradigms provide fast and convenient access to digital artifacts and system commands. People, for example, might not want to touch an interaction device because their hands are dirty from cooking: they want device-free interaction. Or people might not want to have to look at a screen because it would interrupt their current task: they want system-feedback-free interaction. Currently, there is no interaction paradigm for smart environments that allows people for these kinds of interactions. In my dissertation, I introduce Room-based Interaction to solve this problem of HEI. With room-based interaction, people associate digital artifacts and system commands with real-world objects in the environment and point toward these real-world proxy objects for selecting the associated digital artifact. The design of room-based interaction is informed by a theoretical analysis of navigation- and pointing-based selection techniques, where I investigated the cognitive systems involved in executing a selection. An evaluation of room-based interaction in three user studies and a comparison with existing HEI techniques revealed that room-based interaction solves many shortcomings of existing HEI techniques: the use of real-world proxy objects makes it easy for people to learn the interaction technique and to perform accurate pointing gestures, and it allows for system-feedback-free interaction; the use of the environment as flat input space makes selections fast; the use of mid-air full-arm pointing gestures allows for device-free interaction and increases awareness of other’s interactions with the environment. Overall, I present an alternative selection paradigm for smart environments that is superior to existing techniques in many common HEI-scenarios. This new paradigm can make HEI more user-friendly, broaden the use cases of smart environments, and increase their acceptance for the average user