Carvalho, Bruno Motta deGomes Neto, Severino Paulo2014-12-172014-09-162014-12-172014-02-27GOMES NETO, Severino Paulo. Melhorando a estimação de pose com o RANSAC preemptivo generalizado e múltiplos geradores de hipóteses. 2014. 100 f. Tese (Doutorado em Ciência da Computação) - Universidade Federal do Rio Grande do Norte, Natal, 2014.https://repositorio.ufrn.br/jspui/handle/123456789/17958The camera motion estimation represents one of the fundamental problems in Computer Vision and it may be solved by several methods. Preemptive RANSAC is one of them, which in spite of its robustness and speed possesses a lack of flexibility related to the requirements of applications and hardware platforms using it. In this work, we propose an improvement to the structure of Preemptive RANSAC in order to overcome such limitations and make it feasible to execute on devices with heterogeneous resources (specially low budget systems) under tighter time and accuracy constraints. We derived a function called BRUMA from Preemptive RANSAC, which is able to generalize several preemption schemes, allowing previously fixed parameters (block size and elimination factor) to be changed according the applications constraints. We also propose the Generalized Preemptive RANSAC method, which allows to determine the maximum number of hipotheses an algorithm may generate. The experiments performed show the superiority of our method in the expected scenarios. Moreover, additional experiments show that the multimethod hypotheses generation achieved more robust results related to the variability in the set of evaluated motion directionsapplication/pdfAcesso AbertoVisão computacional. Estimação de pose. RANSAC preemptivo. GPRComputer Vision. Pose estimation. Preemptive RANSAC. GPRdoctoralThesisCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO