A New Vehicle Image Dynamic Tracking Approach

Abstract: For the purpose of moving target’s detecting, a new image tracking approach based on the changing factor of reference background learning and the direction predicting operator is presented. The high-speed moving vehicle is used as the detecting target for establishing a changing factor, on this basis the image sequence’s reference background learning is conducted, then by cross-correlation matching and coordinate transforming the moving target-vehicle is coordinate-positioned and speed-determined, combining with the direction predicting operator the moving direction of the target vehicle is predicted, thus the vehicle imagetracking can be realized. Through tracking experiment and performance comparison it is proved that by this new approach an accurate and stable tracking results of moving vehicle can be gotten; a new idea can also be provided for the research of moving target’s image-monitoring. Copyright © 2014 IFSA Publishing, S. L

Texture and Colour in Image Analysis

Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

Mathematical surfaces models between art and reality

In this paper, I want to document the history of the mathematical surfaces models used for the didactics of pure and applied “High Mathematics” and as art pieces. These models were built between the second half of nineteenth century and the 1930s. I want here also to underline several important links that put in correspondence conception and construction of models with scholars, cultural institutes, specific views of research and didactical studies in mathematical sciences and with the world of the figurative arts furthermore. At the same time the singular beauty of form and colour which the models possessed, aroused the admiration of those entirely ignorant of their mathematical attraction

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

Derivation of forest inventory parameters from high-resolution satellite imagery for the Thunkel area, Northern Mongolia. A comparative study on various satellite sensors and data analysis techniques.

With the demise of the Soviet Union and the transition to a market economy starting in the 1990s, Mongolia has been experiencing dramatic changes resulting in social and economic disparities and an increasing strain on its natural resources. The situation is exacerbated by a changing climate, the erosion of forestry related administrative structures, and a lack of law enforcement activities. Mongolia’s forests have been afflicted with a dramatic increase in degradation due to human and natural impacts such as overexploitation and wildfire occurrences. In addition, forest management practices are far from being sustainable. In order to provide useful information on how to viably and effectively utilise the forest resources in the future, the gathering and analysis of forest related data is pivotal. Although a National Forest Inventory was conducted in 2016, very little reliable and scientifically substantiated information exists related to a regional or even local level. This lack of detailed information warranted a study performed in the Thunkel taiga area in 2017 in cooperation with the GIZ. In this context, we hypothesise that (i) tree species and composition can be identified utilising the aerial imagery, (ii) tree height can be extracted from the resulting canopy height model with accuracies commensurate with field survey measurements, and (iii) high-resolution satellite imagery is suitable for the extraction of tree species, the number of trees, and the upscaling of timber volume and basal area based on the spectral properties. The outcomes of this study illustrate quite clearly the potential of employing UAV imagery for tree height extraction (R2 of 0.9) as well as for species and crown diameter determination. However, in a few instances, the visual interpretation of the aerial photographs were determined to be superior to the computer-aided automatic extraction of forest attributes. In addition, imagery from various satellite sensors (e.g. Sentinel-2, RapidEye, WorldView-2) proved to be excellently suited for the delineation of burned areas and the assessment of tree vigour. Furthermore, recently developed sophisticated classifying approaches such as Support Vector Machines and Random Forest appear to be tailored for tree species discrimination (Overall Accuracy of 89%). Object-based classification approaches convey the impression to be highly suitable for very high-resolution imagery, however, at medium scale, pixel-based classifiers outperformed the former. It is also suggested that high radiometric resolution bears the potential to easily compensate for the lack of spatial detectability in the imagery. Quite surprising was the occurrence of dark taiga species in the riparian areas being beyond their natural habitat range. The presented results matrix and the interpretation key have been devised as a decision tool and/or a vademecum for practitioners. In consideration of future projects and to facilitate the improvement of the forest inventory database, the establishment of permanent sampling plots in the Mongolian taigas is strongly advised.2021-06-0

Actas do 10º Encontro Português de Computação Gráfica

Actas do 10º Encontro Portugês de Computação Gráfica, Lisboa, 1-3 de Outubro de 2001A investigação, o desenvolvimento e o ensino na área da Computação Gráfica constituem, em Portugal, uma realidade positiva e de largas tradições. O Encontro Português de Computação Gráfica (EPCG), realizado no âmbito das actividades do Grupo Português de Computação Gráfica (GPCG), tem permitido reunir regularmente, desde o 1º EPCG realizado também em Lisboa, mas no já longínquo mês de Julho de 1988, todos os que trabalham nesta área abrangente e com inúmeras aplicações. Pela primeira vez no historial destes Encontros, o 10º EPCG foi organizado em ligação estreita com as comunidades do Processamento de Imagem e da Visão por Computador, através da Associação Portuguesa de Reconhecimento de Padrões (APRP), salientando-se, assim, a acrescida colaboração, e a convergência, entre essas duas áreas e a Computação Gráfica. Este é o livro de actas deste 10º EPCG.INSATUniWebIcep PortugalMicrografAutodes

Metalogues on the thickened ground: landscape production and urban morphologies

Could we consider urban morphologies as figures that emerge as ‘horizontal phenomena’? Could we consider urban morphologies as embedded within the complex systems of the city rather than assume they demarcate the city through an overlay of lines? Could the urban form then be considered as an affect which emerges from a dynamic thickened ground, creating a new landscape? If landscapes are understood in terms of their connectability to the order of things in the universe (as, for example, in physics), where landscape’s connectability is a reciprocation of forces between itself and its context at all scales, then each connection is a shared force, a received and distributed force. If the order of the landscape is inherent in its process of transformations, to what extent does this order produce the city? This research aims to contribute to the discourse on Landscape Urbanism which is often positioned and grounded within the philosophical and scientific fields. However, it is argued that the ability to open up new possibilities, new ways of thinking and acting, lies in the act of design. This research, therefore, aimed to reveal these possibilities through a structured design process which linked the disciplinary fields of Landscape Architecture and Architecture

Dataset shift in land-use classification for optical remote sensing

Multimodal dataset shifts consisting of both concept and covariate shifts are addressed in this study to improve texture-based land-use classification accuracy for optical panchromatic and multispectral remote sensing. Multitemporal and multisensor variances between train and test data are caused by atmospheric, phenological, sensor, illumination and viewing geometry differences, which cause supervised classification inaccuracies. The first dataset shift reduction strategy involves input modification through shadow removal before feature extraction with gray-level co-occurrence matrix and local binary pattern features. Components of a Rayleigh quotient-based manifold alignment framework is investigated to reduce multimodal dataset shift at the input level of the classifier through unsupervised classification, followed by manifold matching to transfer classification labels by finding across-domain cluster correspondences. The ability of weighted hierarchical agglomerative clustering to partition poorly separated feature spaces is explored and weight-generalized internal validation is used for unsupervised cardinality determination. Manifold matching solves the Hungarian algorithm with a cost matrix featuring geometric similarity measurements that assume the preservation of intrinsic structure across the dataset shift. Local neighborhood geometric co-occurrence frequency information is recovered and a novel integration thereof is shown to improve matching accuracy. A final strategy for addressing multimodal dataset shift is multiscale feature learning, which is used within a convolutional neural network to obtain optimal hierarchical feature representations instead of engineered texture features that may be sub-optimal. Feature learning is shown to produce features that are robust against multimodal acquisition differences in a benchmark land-use classification dataset. A novel multiscale input strategy is proposed for an optimized convolutional neural network that improves classification accuracy to a competitive level for the UC Merced benchmark dataset and outperforms single-scale input methods. All the proposed strategies for addressing multimodal dataset shift in land-use image classification have resulted in significant accuracy improvements for various multitemporal and multimodal datasets.Thesis (PhD)--University of Pretoria, 2016.National Research Foundation (NRF)University of Pretoria (UP)Electrical, Electronic and Computer EngineeringPhDUnrestricte

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described