Deep Convolutional Correlation Particle Filter for Visual Tracking

In this dissertation, we explore the advantages and limitations of the application of sequential Monte Carlo methods to visual tracking, which is a challenging computer vision problem. We propose six visual tracking models, each of which integrates a particle filter, a deep convolutional neural network, and a correlation filter. In our first model, we generate an image patch corresponding to each particle and use a convolutional neural network (CNN) to extract features from the corresponding image region. A correlation filter then computes the correlation response maps corresponding to these features, which are used to determine the particle weights and estimate the state of the target. We then introduce a particle filter that extends the target state by incorporating its size information. This model also utilizes a new adaptive correlation filtering approach that generates multiple target models to account for potential model update errors. We build upon that strategy to devise an adaptive particle filter that can decrease the number of particles in simple frames in which there is no challenging scenarios and the target model closely reflects the current appearance of the target. This strategy allows us to reduce the computational cost of the particle filter without negatively impacting its performance. This tracker also improves the likelihood model by generating multiple target models using varying model update rates based on the high-likelihood particles. We also propose a novel likelihood particle filter for CNN-correlation visual trackers. Our method uses correlation response maps to estimate likelihood distributions and employs these likelihoods as proposal densities to sample particles. Additionally, our particle filter searches for multiple modes in the likelihood distribution using a Gaussian mixture model. We further introduce an iterative particle filter that performs iterations to decrease the distance between particles and the peaks of their correlation maps which results in having a few more accurate particles in the end of iterations. Applying K-mean clustering method on the remaining particles determine the number of the clusters which is used in evaluation step and find the target state. Our approach ensures a consistent support for the posterior distribution. Thus, we do not need to perform resampling at every video frame, improving the utilization of prior distribution information. Finally, we introduce a novel framework which calculates the confidence score of the tracking algorithm at each video frame based on the correlation response maps of the particles. Our framework applies different model update rules according to the calculated confidence score, reducing tracking failures caused by model drift. The benefits of each of the proposed techniques are demonstrated through experiments using publicly available benchmark datasets

Deep Convolutional Correlation Iterative Particle Filter for Visual Tracking

This work proposes a novel framework for visual tracking based on the integration of an iterative particle filter, a deep convolutional neural network, and a correlation filter. The iterative particle filter enables the particles to correct themselves and converge to the correct target position. We employ a novel strategy to assess the likelihood of the particles after the iterations by applying K-means clustering. Our approach ensures a consistent support for the posterior distribution. Thus, we do not need to perform resampling at every video frame, improving the utilization of prior distribution information. Experimental results on two different benchmark datasets show that our tracker performs favorably against state-of-the-art methods.Comment: 28 pages, 9 figures, 1 tabl

Urban form and travel behaviour in seven neighbourhoods of Mashhad/Iran

Es ist wissenschaftlich erwiesen, dass ein erhöhter Verbrauch fossiler Treibstoffe eine hohe Luftverschmutzung und damit eine Vielzahl von sozialen, gesundheitlichen und wirtschaftlichen Komplikationen insbesondere in Städten und urbanen Regionen zur Folge hatte. Diese Problematik wurde durch die ständig ansteigende Nutzung des MIV noch verstärkt. Aus diesen diversen Komplikationen heraus resultierte eine breite Bewegung mit dem Namen „New Urbanism“, welche verschiedene Lösungen wie die kompakte Stadtform und Mischnutzungen offerierte. Ein deutlicher Fokus lag darauf, Fußgänger in der Stadtgestaltung zu berücksichtigen. Diese Arbeit zeigt, wie die Stadtquartiersform das Mobilitätsverhalten eines Haushaltes beeinflusst. Anhand diverser Studien wurde bewiesen, dass die verschiedenen sozialen und wirtschaftlichen Merkmale eines Haushaltes, die Merkmale der Modal Characteristics sowie die Stadtraumtypologie das Mobilitätsverhalten beeinflussen. Allerdings besteht über die Höhe des Einflusses und die Wichtigkeit dieser Merkmale noch kein einheitlicher Konsens. In einigen Forschungsarbeiten spielen die sozialen und wirtschaftlichen Charakteristika eines Haushaltes eine größere Rolle als bei anderen. Ebenso existieren Studien, in denen die stadtraumtypologischen Eigenschaften als die einflussreichsten Merkmale auf das Mobilitätsverhalten eines Haushaltes postuliert werden. Diese unterschiedlichen Meinungen haben dazu beigetragen, dass in dieser Arbeit die Einflüsse jedes dieser Merkmale in Entwicklungsländern, wie z. B. dem Iran, näher beleuchtet werden. Um ein genaueres Verständnis von den Einflüssen dieser Merkmale auf das Mobilitätsverhalten zu erhalten, werden sowohl quantitative als auch qualitative Analysemethoden verwendet. Mit Hilfe der MLR-Methode werden die Beziehung und der Einfluss zwischen jedem dieser Merkmale auf das Mobilitätsverhalten in den sieben ausgewählten Stadtvierteln der Stadt Maschhad analysiert. Um eine bessere Darstellung des Mobilitätsverhaltens aufzuzeigen, wurden die Reisegründe in drei Kategorien, Arbeits-, Freizeit- und Einkaufswege, klassifiziert. Laut diesen Forschungsergebnissen hat die Stadtquartiersform einen erheblichen Einfluss auf das Mobilitätsverhalten der Bewohner jedes Viertels. Die Bevölkerungsdichte, die Vielfalt der Nutzungen sowie das Zentrum des Viertels können als die einflussreichsten Charakteristika der Stadtquartiersform auf das Mobilitätsverhalten herauskristallisiert werden. Auch einige soziale und wirtschaftliche Merkmale des Haushaltes, z. B. der MIV-Besitz sowie das Geschlecht, haben laut den Ergebnissen dieser Arbeit einen großen Einfluss auf die MIV-Nutzung innerhalb der Alltagsmobilität des Haushaltes.Excessive consumption of fossil fuels and consequently air pollution in cities have resulted in social and economic problems. This dire situation is strengthened by an excessive use of private cars which has led to a comprehensive movement which is known as “New Urbanism”. New Urbanism includes some solutions such as compact forms of urban neighborhoods, mixed use and more attention to pedestrians in urban design. The aim of this thesis is to clarify how different forms of urban neighborhoods can affect the travel behavior of families living in a certain neighborhood. Nowadays, it is well accepted that factors such as social and economic conditions of families, characteristics of travel modes as well as the form of urban neighborhoods can influence the travel behavior of families. However, there is not a broad agreement about the importance and the magnitude of these influencing parameters. Some studies revealed the social and economic conditions as the dominant factor affecting the mobility behavior, whereas other showed the form of urban neighborhoods as the main factor. These disagreements form the main motivation of the current study to analyze and identify the importance and the magnitude of each aforementioned influencing factors in Iran as a developing country. Qualitative-quantitative analysis was used to enable a better understanding about each of influencing factors. For this purpose, the relation between each influencing factor on travel behavior within seven neighborhoods of Mashhad city was analysed by means of multiple logistic regression -method. The travel purposes were divided into three categories including working, shopping and other travel. Results show that the form of neighborhoods has a significant influence on the travel behavior of the residents. Population density, variety of land uses and the presence of a center in a neighborhood are the main factors affecting travel behavior of people. Furthermore, the obtained results of this study confirm that some of the social and economic factors, e.g. car owning and gender of residents have a remarkable influence on the use of private cars in daily travels

Investigating the Role of Space Factors in Promoting Vitality for Designing Sports Complex

The quality of urban public space has been one of the focal points of recent design research, with the efforts to create such a public space that could satisfy citizens in different terms has been proposed as one of the main strategies for the urban design projects. As one of the factors affecting the quality of public spaces and urban environments, vitality plays an important role in such settings. On the other hand, the environmental designers are always faced with different aspects of designing public spaces and the important fact is that, among the various factors influencing the vitality, which one has the most important role. In this regard, this study intends to focus on the designing of sports complex in Bandar Anzali in order to enhance the vitality. In terms of research kind, the research is a descriptive-analytical one, in terms of methodology, it uses a survey method and it is functional based on objective. According to the data, it is a quantitative research and it is a field study in terms of implementation. In this regard, among the human-based and environmental variables related to the vitality that were extracted from the documentary and desk research, five cases were selected  as the basis of the research according to the prioritization of environmental psychology developed by the  experts from the faculty of members from the prestigious Iranian  universities. Additionally, the research tools were developed based on this prioritization. The statistical community of the present study involved two cases of the sports complexes representing Bandar Anzali. Therefore, with the determination of the community, sample size and research tools, the selected variables were tested to accept or reject the hypotheses. After analyzing the data by SPSS software, visual beauty, security, sociability, readability and user interaction and 24 hour activity were prioritized respectively. As a result, the analytical model of the research, which in fact includes the main factors affecting the vitality of sports spaces has been formulated as a public space in Anzali.  Finally, the most effective spatial strategies have been presented to promote vitality and to achieve the research goals

Control of hierarchical polymer mechanics with bioinspired metal-coordination dynamics.

In conventional polymer materials, mechanical performance is traditionally engineered via material structure, using motifs such as polymer molecular weight, polymer branching, or block copolymer design. Here, by means of a model system of 4-arm poly(ethylene glycol) hydrogels crosslinked with multiple, kinetically distinct dynamic metal-ligand coordinate complexes, we show that polymer materials with decoupled spatial structure and mechanical performance can be designed. By tuning the relative concentration of two types of metal-ligand crosslinks, we demonstrate control over the material's mechanical hierarchy of energy-dissipating modes under dynamic mechanical loading, and therefore the ability to engineer a priori the viscoelastic properties of these materials by controlling the types of crosslinks rather than by modifying the polymer itself. This strategy to decouple material mechanics from structure is general and may inform the design of soft materials for use in complex mechanical environments. Three examples that demonstrate this are provided

Deep Convolutional Particle Filter with Adaptive Correlation Maps for Visual Tracking

The robustness of the visual trackers based on the correlation maps generated from convolutional neural networks can be substantially improved if these maps are used to employed in conjunction with a particle filter. In this article, we present a particle filter that estimates the target size as well as the target position and that utilizes a new adaptive correlation filter to account for potential errors in the model generation. Thus, instead of generating one model which is highly dependent on the estimated target position and size, we generate a variable number of target models based on high likelihood particles, which increases in challenging situations and decreases in less complex scenarios. Experimental results on the Visual Tracker Benchmark vl.0 demonstrate that our proposed framework significantly outperforms state-of-the-art methods

Application of walnut tree sawdust modified with KMnO4 for removal of methylene blue from aqueous solution in batch system: Isotherm, kinetic and thermodynamic studies

In this study, the adsorption of methylene blue from aqueous solution by modifying sawdust with KMnO4 has been studied as an effective adsorbent. The surface and characteristics of the composite are studied by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The result demonstrate, that by increasing pH, the amount of methylene blue adsorption also increases, and the amount of optimum removal of this dye (96.36%) was obtained at methylene blue dye pH aqueous solution equal to 6 with initial concentration 100 mg L-1. The studies have shown that the kinetics of the adsorption process follows the pseudo-second-order model with a correlation coefficient R2>0.999, and equilibrium data conform the Langmuir isotherm model with R2>0.9982 and a maximum capacity of single layer adsorption qe equal to 100 mgg-1. Thermodynamically, the reaction is endothermic and spontaneous. Consequently, the result has shown, that the modified sawdust can be used as a quick, inexpensive and effective adsorbent in order for removal of methylene blue dye from aqueous solution