Vision-based traffic monitoring system with hierarchical camera auto-calibration

Texto en inglés.En las últimas décadas, el tráfico, debido al aumento de su volumen y al consiguiente incremento en la demanda de infraestructuras de transporte, se ha convertido en un gran problema en ciudades de casi todo el mundo. Constituye un fenómeno social, económico y medioambiental en el que se encuentra inmersa toda la sociedad, por lo que resulta importante tomarlo como un aspecto clave a mejorar. En esta línea, y para garantizar una movilidad segura, fluida y sostenible, es importante analizar el comportamiento e interacción de los vehículos y peatones en diferentes escenarios. Hasta el momento, esta tarea se ha llevado a cabo de forma limitada por operarios en los centros de control de tráfico. Sin embargo, el avance de la tecnología, sugiere una evolución en la metodología hacia sistemas automáticos de monitorización y control. Este trabajo se inscribe en el marco de los Sistemas Inteligentes de Transporte (ITS), concretamente en el ámbito de la monitorización para la detección y predicción de incidencias (accidentes, maniobras peligrosas, colapsos, etc.) en zonas críticas de infraestructuras de tráfico, como rotondas o intersecciones. Para ello se propone el enfoque de la visión artificial, con el objetivo de diseñar un sistema sensor compuesto de una cámara, capaz de medir de forma robusta parámetros correspondientes a peatones y vehículos que proporcionen información a un futuro sistema de detección de incidencias, control de tráfico, etc.El problema general de la visión artificial en este tipo de aplicaciones, y que es donde se hace hincapié en la solución propuesta, es la adaptabilidad del algoritmo a cualquier condición externa. De esta forma, cambios en la iluminación o en la meteorología, inestabilidades debido a viento o vibraciones, oclusiones, etc. son compensadas. Además el funcionamiento es independiente de la posición de la cámara, con la posibilidad de utilizar modelos con pan-tilt-zoom variable para aumentar la versatilidad del sistema. Una de las aportaciones de esta tesis es la extracción y uso de puntos de fuga (a partir de elementos estructurados de la escena), para obtener una calibración de la cámara sin conocimiento previo. Esta calibración proporciona un tamaño aproximado de los objetos buscados, mejorando así el rendimiento de las siguientes etapas del algoritmo. Para segmentar la imagen se realiza una extracción de los objetos móviles a partir del modelado del fondo, basándose en mezcla de Gaussianas (GMM) y métodos de detección de sombras. En cuanto al seguimiento de los objetos segmentados, se desecha la idea tradicional de considerarlos un conjunto. Para ello se extraen características cuya evolución es analizada para conseguir finalmente una agrupación óptima que sea capaz de solventar oclusiones. El sistema ha sido probado en condiciones de tráfico real sin ningún conocimiento previo de la escena, con resultados bastante satisfactorios que muestran la viabilidad del método

TOWARDS SUSTAINABLE AUTONOMOUS VEHICLES

Ph.DDOCTOR OF PHILOSOPH

Sensory Augmentation for Navigation in Difficult Urban Environments by People With Visual Impairment

Independent mobility in completing such tasks as walking through a town centre is taken for granted by well-bodied individuals. However, for those with a disability such as impairment of vision, mobility and navigation can become challenging tasks not easily undertaken. The barriers to access for blind and partially sighted individuals are increased when familiar navigational cues are removed in difficult urban environments such as Shared Space. The research consisted of investigating methods of navigation employed by people with visual impairment and designing a device to restore confidence to this group so as to lower the barriers of access to such environments. Investigation was carried out through the deployment of a questionnaire; discussions with groups representing blind and partially sighted people; and a site visit to Shared Space environments. Statistical analysis was carried out on the results of the questionnaire to ascertain the navigational habits of blind and partially sighted individuals in different environments. From the analysis and the results of the discussions and site visit it was established that it would be socially acceptable to design a secondary aid to navigation that would complement the primary aids of long cane or guide dog. A concept experiment was carried out to test the idea that knowledge about changes in surface colour could help with navigation. A prototype device that could be used by individuals with visual impairment to increase their confidence when navigating a difficult environment was designed, built and tested. Different programming methods were researched and trialled to effectively use machine vision to provide a solution to analyse video feed from a passive camera and return useful information to a blind or partially sighted user. The device was tested indoors and outdoors and found to be effective at detecting changes in surface colour. Further work is needed to run the software on a more compact platform such as a mobile phone, but initial results show that the concept is viable and that the barriers that present to blind and partially sighted people navigating difficult urban environments can be much reduced through the use of this technology

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Automatic biological object segmentation and tracking in unconstrained microscopic video conditions

Cell and small biological organism tracking research is of fundamental importance for the analysis of dynamic behaviour for assisting the development of many biomedical image related applications. With the rapid development of digitised imaging systems, the immense collections of experimental (microscopic) videos make it nearly impossible to manually analyse the obtained data. Therefore, recent research has drawn attention to building automatic tracking systems to track the movement of cells and small biological organism models using videos taken by microscopes. Although general object tracking (such as traffic cars and pedestrians) has been studied for decades, existing general object tracking systems cannot directly be applied to cell and small biological organism tracking, due to the differences in the imaging devices and conditions of the targets. This research therefore investigates the novel application of computer vision techniques to reliably, accurately and effectively track the movement of cells and small biological organisms automatically. Due to difficulties in generating video segmentation ground-truth, there is a general lack of segmentation datasets with annotated ground-truth (particularly for biomedical images). This work proposes an efficient and scalable crowdsourced approach to generate video segmentation ground-truth and develops a tracking ground-truth generation system. To illustrate the proposed approach, an annotated zebrafish larvae video segmentation dataset and three tracking datasets have been generated and made freely available online. Automatic cell tracking techniques require accurate cell image segmentation; however, current general object segmentation techniques are susceptible to errors due to the poor microscopic imaging conditions, which include low contrast typical of cell microscopic images. This work proposes a novel image pre-processing technique to enhance low greyscale image contrast for improved cell image segmentation accuracy. An adaptive, shifted bi-Gaussian mixture model is matched to the original cell image intensity histogram for greater differentiation between the cell foreground and image background, while maintaining the original intensity histogram shape. Small biological organism videos taken by microscope imaging devices under realistic experimental conditions have more complex video backgrounds than cell videos. This work first investigates single zebrafish larvae tracking using dense SIFT flow and downsampling techniques. Many existing multiple small organism tracking systems require very strict video imaging conditions, which typically result in unreliable tracking results for realistic experimental conditions. Thus, this research further investigates the adaptation of advanced segmentation techniques to improve the performance of small organism segmentation under complex imaging conditions. Finally, this work improves the multiple object association method based on the segmentation module for the proposed system, to address object misdetection and overlapping problems. This system is then evaluated on zebrafish videos, Artemia franciscana videos and Daphnia magna videos, under a wide variety of (complex) video conditions, including shadowing, labels, and background artefacts (such as water bubbles of different sizes). The tracking accuracy of the proposed system outperforms three existing tracking systems. Thus, the work in this thesis has contributions in automatic cell and biological organism tracking, where the investigation studied the region-based segmentation dataset construction generalised for biological organisms, intensity contrast enhancement for micrographs, segmentation improvement by removing imaging constraints and the final tracking accuracy enhancement

NASA Tech Briefs, July 1990

Topics include: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Proceedings. 9th 3DGeoInfo Conference 2014, [11-13 November 2014, Dubai]

It is known that, scientific disciplines such as geology, geophysics, and reservoir exploration intrinsically use 3D geo-information in their models and simulations. However, 3D geo-information is also urgently needed in many traditional 2D planning areas such as civil engineering, city and infrastructure modeling, architecture, environmental planning etc. Altogether, 3DGeoInfo is an emerging technology that will greatly influence the market within the next few decades. The 9th International 3DGeoInfo Conference aims at bringing together international state-of-the-art researchers and practitioners facilitating the dialogue on emerging topics in the field of 3D geo-information. The conference in Dubai offers an interdisciplinary forum of sub- and above-surface 3D geo-information researchers and practitioners dealing with data acquisition, modeling, management, maintenance, visualization, and analysis of 3D geo-information