3D representation nowadays has attracted much more public attention than ever before. One of the most important techniques in this field is depth extraction. In this thesis, we first introduce a well-known stereo matching method using color segmentation and belief propagation, and make an implementation of this framework. The color-segmentation based stereo matching method performs well recently, since this method can keep the object boundaries accurate, which is very important to depth map. Based on the implemented framework of segmentation based stereo matching, we proposed a color segmentation based 2D-to-3D video conversion method using high quality motion information. In our proposed scheme, the original depth map is generated from motion parallax by optical flow calculation. After that we employ color segmentation and plane estimation to optimize the original depth map to get an improved depth map with sharp object boundaries. We also make some adjustments for optical flow calculation to improve its efficiency and accuracy. By using the motion vectors extracted from compressed video as initial values for optical flow calculation, the calculated motion vectors are more accurate within a shorter time compared with the same process without initial values. The experimental results shows that our proposed method indeed gives much more accurate depth maps with high quality edge information. Optical flow with initial values provides good original depth map, and color segmentation with plane estimation further improves the depth map by sharpening its boundaries.

Cette thèse présente un système de traitement des vidéos multi-vues plus profondeur (MVD), en utilisant le concept d'images multi-couches (LDI). Plusieurs contributions sont proposées, à la fois dans le domaine de la synthèse de vues à partir de cartes de profondeur et dans le domaine de la construction et de la compression des LDI. La méthode de synthèse de vues proposée est basée sur une nouvelle technique de projection (JPF). La projection JPF prend en entrée des données de type image plus profondeur et synthétise un nouveau point de vue quelconque ; elle est conçue pour détecter et remplir les fissures et les petits découvrements pendant la projection. Une mesure de confiance sur les pixels est introduite afin d'éviter les artéfacts fantômes au niveau des contours. Cette projection JPF est utilisée d'une part avec une technique de ré-alignement de textures lors de l'interpolation de vues intermédiaires, et d'autre part avec une nouvelle méthode de synthèse de textures lors de l'extrapolation de vues virtuelles. Afin d'encoder efficacement les séquences de LDI, un schéma de compression multi-vues (MVC/AVC) est adapté pour exploiter à la fois les redondances temporelles et inter-couche. Une construction incrémentale des LDI est proposée, qui réduit le taux de remplissage des couches additionnelles. L'efficacité de la compression est améliorée par une réorganisation des couches par objet, assurant ainsi une meilleure cohérence spatiale. Deux méthodes de rendu sont finalement proposées : la première utilise la projection JPF alors que la seconde utilise des maillages 3D pour un affichage temps réel sur un écran multi-scopiques.

Infiltration facilities are source control mechanisms that are implemented in urban developments with reduced natural permeable surfaces. Despite the development of design criteria for infiltration facilities, these systems continue to fail due to headloss development, overflow, or chemical breakthrough. The limited research on the long-term performance of these systems has emphasized the role of physical filtration mechanisms within porous media filters to address concerns surrounding system failure, namely filter clogging. A continuous macroscopic depth filtration model was developed to investigate the clogging potential of the underlying sand filter. This continuous model furthers the understanding of temporal and spatial changes in system performance for the development of more appropriate design criteria and more suitable maintenance regimes. The characterization of long-term system performance by defining three different failure modes and a probabilistic approach comprises a comprehensive methodology by considering several performance criteria rather than assuming that one criterion dictates the overall system performance.

Below-ground effects during forest fires are some of the important issues forest managers consider when conducting prescribed fire programs. Heat transfer models in soil are needed to predict temperatures in soil during forest fires. Many of the heat transfer models in soil that include the effects of moisture are complex and in most cases do not have very good predictive abilities. Researchers believe that simple heat transfer models in soil that neglect the effects of moisture could have very good predictive abilities.<p>This study presents a one-dimensional numerical model of heat transfer in dry homogenous sand. Both constant and temperature dependent thermal properties of the sand were used in order to determine which had better predictive abilities. The constant thermal properties model was also extended to a model of two-layer dry soil. A computer code written in Fortran was used to generate results from the model. A number of experiments were conducted with dry sand to validate the model. A comparison of the numerical and experimental results indicated that the temperature dependent properties model had better predictive abilities than the constant properties model. The models were found to do a good job of predicting temperature profiles and depth of lethal heat penetration at heat fluxes indicative of forest fires.<p>Experiments were also conducted to determine the effect of moisture on temperature profiles and the depth of lethal heat penetration in sand and the effect of inorganics on the spread rate of smoldering combustion in peat moss. An experimental correlation of the effects of inorganic content on the spread rate of smoldering combustion in peat moss was developed. Additionally, laboratory methods of validating models of heat transfer in soil were developed with the aim of limiting the dependence on full scale testing. Specifically the use of the cone calorimeter for validating numerical models of heat transfer in soil and the responses of forest floor soil and laboratory created soil samples to heat input were compared. The results indicated that the laboratory created soil did a very good job of mimicking the heat response of the forest floor soil with a maximum difference in lethal heat penetration of 4%.

The objective of this research project was to establish a better understanding of the mechanism(s) and route(s) by which selenium (Se) may enter an aquatic ecosystem that has been receiving treated metal mine effluent from an upstream uranium milling operation. Synchrotron based X-ray absorption spectroscopy (XAS) and X-ray fluorescence (XRF) imaging, which require little sample pre-treatment, were employed to study the speciation and distribution of Se in complex sediment and benthic invertebrates samples collected from the field. Laboratory based inductively coupled plasma mass spectrometry (ICP-MS) provided quantitative Se concentrations. Samples were taken from Fox Lake and Unknown Lakes, downstream of the mill, and Yeoung Lake as a control. The variation in Se speciation as a function of depth in intact sediment cores may provide insight into the species of Se available to the sediment dwelling benthic invertebrate communities. Therefore, a custom sample holder was designed to facilitate analysis of intact sediment cores at cryogenic temperatures. Additionally, laboratory reared chironomids were water-exposed to various Se species, to compare their Se speciation and localization to chironomids collected in the field. The successful demonstration of the custom sample holder and viable use of synchrotron XAS and XRF in studying sediment and chironomid samples have revealed that biologically relevant Se forms were present in sediment at depths accessible by the benthic invertebrate community. These Se forms included selenomethionine-like and selenite species, and to a lesser degree elemental Se; an increased proportion of reduced Se species was observed as depth increased. Other elements measured concurrently with Se included As, Zn, Cu, Ni, Fe, and Mn, providing an estimation of the redox boundary found both in Fox and Unknown Lake, as well as suggesting the presence of iron species that could aid in the reduction of Se. Field and laboratory reared chironomids showed similar Se species, and XRF imaging revealed the localization of Se in 4 distinct regions: head capsule, brain, salivary glands, and gut lining. Overall, the project has provided important insights into the interactions of Se with this aquatic ecosystem, which may have future applications in cold water systems with elevated Se concentrations.

This report investigates possible health effects due to improper disposal of waste and the awareness within a community. The aim was also to investigate what is needed for a pro-environmental behavior in a rural area (Mutomo) within a developing country (Kenya). Waste management in developing countries has been and still remains a challenge, waste is left in nature and this has the potential for negative health effects on people and animals as well as degrading land and aquatic ecosystems. The used method was qualitative and for data collection in-depth interviews were conducted with help of an interpreter, interviewing guide, and a recording device. The interviews were transcribed and analyzed using NVivo and thematic analysis. The result shows that all participants were aware of the health risks connected to waste. Much concern was raised amongst the community members, especially for the children’s health. All participants had a positive attitude towards re-collecting, re-using and recycling of waste, for the community members this was if a gain of income was obtained. Also the lack of responsibility by the general public was brought up by many participants as a social norm. To conclude if pro-environmental behavior is to be reached in Mutomo there has to be; (i) available systems for the public, (ii) a collective thought of responsibility in every community member, (iii) education on the issue in three steps (knowledge, comprehension and prevention) but most importantly (iv) the living standards has to be raised for those people that are most frequently affected.

<p>This phenomenological study explored the lived experiences of undergraduate community health nursing students at the University of the Western Cape&nbsp / who conducted a family health assessment learning task in communities during their clinical fieldwork placement.The population included the 2008&nbsp / semester two, third year undergraduate baccalaureus nursing students. These students completed their community health nursing modules at the end of the first semester. A total of nine (9) out of the eighty- nine (89) semester two students participated in this qualitative research study. The purposive and&nbsp / convenient sample consisted of those students who agreed to voluntarily participate in the research study. In-depth interviews were conducted with seven&nbsp / (7) female and two (2) male students to collect data. Field notes were taken and utilized to capture non-verbal communication of the participants. The focus&nbsp / f the researcher was to explore the lived experiences of students and not that of the family whom they interviewed. All interviews were audio recorded&nbsp / nd validated by participants after transcription, before any of the data was used for the data analysis process. The data collected was categorized into themes as guided by the systematic data analyses process according to Tesch&rsquo / s (1990) method, as cited in Creswell (2003). Saturation was tested&nbsp / after nine interviews and the researcher found that no new data emerged. The importance of the research study was to reflect on the exploration of the&nbsp / self-reported lived experiences of the third year community&nbsp / ealth nursing students while conducting the family health assessment learning task.&nbsp / </p>

This study aims to present and evaluate a new method for measuring the distribution of snow within built-up environments by differencing elevations collected by an Airborne Laser Scanner (ALS) before, and during peak snow accumulation. Few efforts have been made to study the distribution of snow within built-up environments due to the false assumption that high-intensity rainfall is the main contributor to peak yearly runoff rates. Traditional techniques for measuring snow are often difficult to replicate in built-up environments due to incompatibility of methods and barriers such as buildings, roads and private property. Light Detection and Ranging (LiDAR) technology, specifically ALSs, have previously been used to characterize the distribution of snow under forest canopy, and in remote mountain environments. This study investigates and assesses the utility of high resolution, non-intrusive ALS data for estimating the depth and distribution of snow within the town of Uxbridge, Ontario. ALS flights for this study were completed before the onset of snow accumulation, as well as near peak snow accumulation for the winters of 2010 and 2011. Pre and post snow accumulation ALS measured elevations were differenced to estimate the depth of the snowpack across the entire study area at a resolution of 0.5 m. Ground measurements of snow depth were also completed within 24 hours of each of the winter flights. The LiDAR-estimated and ground-measured snow depths were compared using Spearman's rank correlation coefficient as well as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Results from this thesis show that: 1) Snow depths estimated by differencing elevations from two ALS flights show a MAE of 3 cm and an RMSE of 10 cm when compared to ground-measured snow depths. (2) There is a strong, statistically significant relationship (ρ = 0:82, p < 0:001) between LiDAR-estimated and ground-measured snow depths. (3) An average bias of -3 cm was found for the entire dataset showing an underestimation in the LiDAR-estimated snow depths most likely caused by the effects of low lying vegetation on the fall ALS measurements. The results presented in this study demonstrate that ALSs are capable of providing high spatial resolution snow depth estimates within built-up environments. Furthermore, snow depth measurements made using an ALS can be used to increase the current body of knowledge on the distribution and re-distribution of snow within built-up environments. Snow distributions measured by an ALS could also be used for future development and verification of urban hydrological models.

Infiltration facilities are source control mechanisms that are implemented in urban developments with reduced natural permeable surfaces. Despite the development of design criteria for infiltration facilities, these systems continue to fail due to headloss development, overflow, or chemical breakthrough. The limited research on the long-term performance of these systems has emphasized the role of physical filtration mechanisms within porous media filters to address concerns surrounding system failure, namely filter clogging. A continuous macroscopic depth filtration model was developed to investigate the clogging potential of the underlying sand filter. This continuous model furthers the understanding of temporal and spatial changes in system performance for the development of more appropriate design criteria and more suitable maintenance regimes. The characterization of long-term system performance by defining three different failure modes and a probabilistic approach comprises a comprehensive methodology by considering several performance criteria rather than assuming that one criterion dictates the overall system performance.

Identification of individuals has been solved with many different solutions around the world, either using biometric data or external means of verification such as id cards or RFID tags. The advantage of using biometric measurements is that they are directly tied to the individual and are usually unalterable. Acquiring dependable measurements is however challenging when the individuals are uncooperative. A dependable system should be able to deal with this and produce reliable identifications. The system proposed in this thesis can autonomously classify uncooperative specimens from depth data. The data is acquired from a depth camera mounted in an uncontrolled environment, where it was allowed to continuously record for two weeks. This requires stable data extraction and normalization algorithms to produce good representations of the specimens. Robust descriptors can therefore be extracted from each sample of a specimen and together with different classification algorithms, the system can be trained or validated. Even with as many as 138 different classes the system achieves high recognition rates. Inspired by the research field of face recognition, the best classification algorithm, the method of fisherfaces, was able to accurately recognize 99.6% of the validation samples. Followed by two variations of the method of eigenfaces, achieving recognition rates of 98.8% and 97.9%. These results affirm that the capabilities of the system are adequate for a commercial implementation.