This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.

L'objectif de cette thèse est l'accélération des solveurs de Gradient Conjugué avec déflation utilisés pour la résolution de l'équation de Poisson pour la pression, dans le cas de la simulation d'écoulements à faible nombre de Mach sur des maillages non structurés. Une méthode de redémarrage basée sur une estimation de l'effet des erreurs numériques a été mise en œuvre et validée. Par la suite, une méthode à trois niveaux de maillage a été créée, et deux techniques ont dû être développées pour réduire le nombre d'itérations sur les niveaux grossiers : l'une permet la création de solutions initiales grâce à une méthode de projection adaptée, l'autre consiste en une adaptation du critère de convergence sur les niveaux grossiers. Les résultats numériques sur des simulations massivement parallèles montrent entre autres une réduction considérable du temps de calcul global. D'autres pistes de recherche sont introduites, notamment concernant l'équilibrage dynamiques de charge de calcul. / The main objective of this thesis is to accelerate deflated Conjugate Gradient solvers used for solving the pressure Poisson equation, for the simulation of low-Mach number flows on unstructured meshes. A restart method based on an estimation of the effect of numerical errors has been implemented and validated. Then, a three-level deflation method has been created, and two techniques are developed in order to reduce the number of iterations on the coarse levels : one of them is the creation of initial guesses thanks to a well-suited projection method, the other one consists in adapting the convergence criterion on the coarse grids. Numerical results on massively parallel simulations show, among others, a drastic reduction of the computational times of the solver. Other lines of research are introduced, especially regarding dynamic load balancing.

Morphogens are secreted signalling molecules that are expressed in restricted groups of cells within the developing tissue. From there, they are secreted and travel throughout the target field and form concentration gradients. These concentration profiles endow receiving cells with positional information. A number of experiments in Drosophila demonstrated that the morphogen Decapentaplegic (Dpp) forms activity gradients by inducing the expression of several target genes above distinct concentration thresholds at different distances from the source. This way, Dpp contributes to developmental fates in the target field such as the Drosophila wing disc. Although the tissue distribution as well as the actual shape and size of the Dpp morphogen concentration gradient has been visualized, the cell biological mechanisms through which the morphogen forms and maintains a gradient are still a subject of debate. Two hypotheses as to the dominant mechanism of movement have been proposed that can account for Dpp spreading throughout the Drosophila wing imaginal target tissue: extracellular diffusion and planar transcytosis, i. e. endocytosis and resecretion of the ligand that is thereby transported through the cells. Here, I present data indicating that implications of a theoreticalanalysis of Dpp spreading, where Dpp transport through the target tissue is solely based on extracellular diffusion taking into account receptor binding and subsequent internalization, are inconsistent with experimental results. By performing Fluorescence Recovery After Photobleaching (FRAP) experiments, I demonstrate a key role of Dynamin-mediated endocytosis for Dpp gradient formation. In addition, I show that most of GFP-Dpp traffics through endocytic compartments at the receiving epithelial cells, probably recycled through apical recycling endosomes (ARE). Finally, a Dpp recycling assay based on subcellular photouncage of ligand is presented to address specifically the Dpp recycling event at the receiving cells.

This thesis is interested in detection of corresponding points in images, which display the same object, eventually some of important elements and synchronizing these images. The aim of this thesis is to find, study and choose suitable algorithm for detecting interesting points in image. This algorithm will be apply at couple of images and in these images will find couples of corresponding points across these images. Functional output of this thesis will be application which will realize choosen interesting points detector, algorithm for finding correspondencies of regions and their synchronizing and joint them to one output image.

No description available.

Assembly is a process that shapes the abundance and identity of species in a community. Niche and neutral theory explain assembly processes with mechanisms driven by either species differences, or functional equivalence and stochastic dispersal. In 2017 I sampled vegetation and environmental variables at 59 sites in the Noxubee National Wildlife Refuge and Tombigbee National Forest of Mississippi to explore forest understory community assembly. I developed and assessed a framework of predictions concerning general patterns and underlying mechanism. Evidence of dispersal limitation and functional equivalence were expected under neutral theory. Local environmental characteristics, surrounding landscape variables, and fire were significant determinants of beta diversity. Dispersal was not a strong predictor of beta diversity. I found evidence of both niche complementarity and functional equivalence, as well as niche differences among common vines and an introduced vine (Lonicera japonica). Overall, the results were more congruent with predictions expected under niche theory.

This thesis implements an automated system that counts pedestrians with 85% accuracy. Two approaches have been considered and evaluated in terms of count accuracy, cost and ease of deployment. The first approach employs the Autoscope Solo Terra, a traffic camera which is widely used to monitor vehicular traffic. The Solo Terra supports an image processing-based detector that counts the number of objects crossing user-defined areas in the captured image. The count is updated based on the amount of movement across the selected regions. Therefore, a second approach has been considered that uses a histogram of oriented gradients (HoG), an advanced vision based algorithm proposed by Dalal et al. which distinguishes a pedestrian from a non-pedestrian based on an omega shape formed by the head and shoulders of a human being. The implemented detection software processes video frames that are streamed from a low-cost digital camera. The frames are divided into sub-regions which are scanned for an omega shape whenever movement is detected in those regions. It has been found that the HoG-based approach degrades in performance due to occlusion under dense pedestrian traffic conditions whereas the Solo Terra approach appears to be more robust. Undercounts and overcounts were encountered using the Solo Terra approach. To combat the disadvantages of both the approaches, they were integrated to form a single system where count is incremented predominantly using the Solo Terra. The HoG-based approach corrects the obtained count under certain conditions. A preliminary prototype of the integrated system has been verified.

Raman spectroscopy, laser-induced fluorescence, and sum-frequency generation (SFG) spectroscopy are used to investigate the behavior of compressible mobile phases and stationary phases under a variety of chromatographic conditions. Efforts to understand and optimize separations employing compressible mobile phases have been limited by a lack of understanding of the mobile phase density gradient. Mobile phase compressibility leads to gradients in linear velocity and solute retention and affects separation speed and efficiency, especially in packed columns. This work describes on-column density measurement of CO2, a common carrier fluid for SFC and SGC, in packed capillary columns using Raman microspectroscopy. On-column detection by laser-induced fluorescence is used to observe the effect of the mobile phase density gradient on separation speed and efficiency, and experimental efficiency is compared to a theoretical model. Additionally, SFG spectroscopy allows for probing the structure of model monomeric and polymeric C18 stationary phases under pressure; this provides a basis for correlating selectivity with pressure-induced structural changes in stationary phase materials. Together, this work provides a more complete understanding of the role of column pressure and fluid compressibility on the speed, efficiency, and selectivity of chemical separations.

Unmanned Aerial Vehicles (UAVs) provides a platform for many automated tasks and with an ever increasing advances in computing, these tasks can be more complex. The use of UAVs is expanded in this thesis with the goal of Search and Rescue (SAR), where a UAV can assist fast responders to search for a lost person and relay possible search areas back to SAR teams. To identify a person from an aerial perspective, low-level Histogram of Oriented Gradients (HOG) feature descriptors are used over a segmented region, provided from thermal data, to increase classification speed. This thesis also introduces a dataset to support a Bird’s-Eye-View (BEV) perspective and tests the viability of low level HOG feature descriptors on this dataset. The low-level feature descriptors are known as Boosted Histogram of Oriented Gradients (BHOG) features, which discretizes gradients over varying sized cells and blocks that are trained with a Cascaded Gentle AdaBoost Classifier using our compiled BEV dataset. The classification is supported by multiple sensing modes with color and thermal videos to increase classification speed. The thermal video is segmented to indicate any Region of Interest (ROI) that are mapped to the color video where classification occurs. The ROI decreases classification time needed for the aerial platform by eliminating a per-frame sliding window. Testing reveals that with the use of only color data iv and a classifier trained for a profile of a person, there is an average recall of 78%, while the thermal detection results with an average recall of 76%. However, there is a speed up of 2 with a video of 240x320 resolution. The BEV testing reveals that higher resolutions are favored with a recall rate of 71% using BHOG features, and 92% using Haar-Features. In the lower resolution BEV testing, the recall rates are 42% and 55%, for BHOG and Haar-Features, respectively.

No abstract provided. / Thesis / Master of Engineering (MEngr) / Scope and contents: This thesis describes the behaviour of iron ore-water suspensions under turbulent flow conditions. This work is divided into two parts. Part I deals with the regimes of transport under steady state flow conditions in circular and horizontal ducts. The heterogeneous flow regime is extensively analyzed; a sequential discrimination of models with an oriented design of experiments have permitted the determination of the best model to correlate hydraulic gradients for these suspensions. A critical discussion on the limit deposit conditions is also included. Part II describes the behaviour of clear water under oscillatory flow conditions. The study demonstrates that the quasi-steady state hypothesis, i.e., fully developed flow assumption, applied to pulsatile turbulent flow under the conditions studied. Observations on the behaviour of iron ore-water suspensions under pulsatile flow are also included. The experiments were carried out using a new air-pulsing technique.