Placement of virtual objects in Augmented Reality is often done without regarding the artifacts in the physical environment. This thesis investigates how placement can be done with the artifacts included. It only considers placement of wall mounted objects. Through the development of two prototypes, using detected edges in RGB-images in combination with volumetric properties to identify the artifacts, arreas will be suggested for placement of virtual objects. The first prototype analyze each triangle in the model, which is an intensive and with low precision on the localization of the physical artifacts. The second prototype analyzed the detected RGB-edges in world space, which proved to detect the features with precise localization and a reduce calculation time. The second prototype manages this in a controlled setting. However, a more challenging environment would possibly pose other issues. In conclusion, placement in relation to volumetric and edge information from images in the environment is possible and could enhance the experience of being in a mixed reality, where physical and virtual objects coexist in the same world. / Placering av virtuella objekt i Augumented Reality görs ofta utan att ta hänsyn till objekt i den fysiska miljön. Den här studien utreder hur placering kan göras med hänsyn till den fysiska miljön och dess objekt. Den behandlar enbart placering av objekt på vertikala ytor. För undersökningen utvecklas två prototyper som använder sig av kantigenkänning i foton samt en volymmetrisk representation av den fysiska miljön. I denna miljö föreslår prototyperna var placering av objekt kan ske. Den första prototypen analyserar varje triangel i den volymmetriska representationen av rummet, vilket visade sig vara krävande och med låg precision av lokaliseringen av objekt i miljön. Den andra prototypen analyserar de detekterade kanterna i fotona och projicerar dem till deras positioner i miljön. Vilket var något som visade sig hitta objekt i rummet med god precision samt snabbare än den första prototypen. Den andra prototypen lyckas med detta i en kontrollerad miljö. I en mer komplex och utmanande miljö kan problem uppstå. Placering av objekt i Augumented Reality med hänsyn till både en volymmetrisk och texturerad representation av en miljö kan uppnås. Placeringen kan då ske på ett mer naturligt sätt och därmed förstärka upplevelsen av att virtuella och verkliga objekt befinner sig i samma värld.

This thesis examines the rapid, non-genomic effects of estrogens on neural plasticity and learning. Estrogens are classically known to affect gene transcription events, however they have more recently been found to also rapidly activate second messenger systems within 1hr of administration. Therefore, we first examined the rapid effects of 17β-estradiol, and an estrogen receptor (ER) α and ERβ agonist on three different learning paradigms: object placement, object recognition, and social recognition. We found that both systemic injections and intrahippocampal delivery of 17β-estradiol and the ERα agonist improved performance on all 3 learning paradigms within 40min of hormone administration. However, the ERβ agonist administered systemically or intrahippocampally, improved performance only on the object placement learning paradigm, while having no effect on object recognition, and impairing social recognition at high doses. To elucidate how estrogens might rapidly affect learning, we examined how estrogens rapidly affect the neural plasticity of CA1 hippocampal neurons. We found that 17β-estradiol and the ERα agonist increased dendritic spine density in CA1 hippocampal neurons within 40min of administration, suggesting that estrogens rapidly increase the density of synapses within this brain region. Conversely, the ERβ agonist did not affect spine density, or decreased spine density. In addition, by using whole-cell patch clamp recordings of CA1 pyramidal neurons, we were able to determine that 17β-estradiol and the ERα agonist rapidly reduced AMPA receptor (but not NMDA receptor) mediated membrane depolarizations after 15min of hormone application. Similar to above, the ERβ agonist had no effect on AMPA or NMDA receptor mediated membrane depolarizations. These data suggest that estrogens rapidly promote the development of immature synapses (which contain low levels of synaptic AMPA receptors) within the CA1 hippocampus. Immature spines provide synaptic sites at which new memories can be stored and are thought of as “learning spines” (Kasai et al, 2003). Therefore, estrogens (through ERα) may rapidly induce the formation of hippocampal immature spines to promote learning. / Funded by NSERC