Insignificance and Minor Architecture

The fragmented condition of our everyday brings us closer to the risks of hyper-expression. Against it two positions unfold to help us face a world that escapes our capacities: familiarity and poetic recognition. In the latter it is crucial the role of the insignificant as dynamic and relational instigator of a conscious threading of reality through the actions of the Poeta Faber and his careful look onto the world. / The production of the common as the material and symbolic fabric of the city, unstable reality in a perpetual becoming, leads us to a new and much needed reconsideration of the public/private division born from the modern state. Immersed in the confusion between public and common, we have not perceived that through the expropriation of the first we have been prepared for the willing surrendering of the second. / From insignificance to rebellion as affirmative going into action related to the idea of minor architecture as common and intensely political production, born from the inside of a society that has no more outsides.

Joint 4-D variational stereo reconstruction and camera calibration refinement for oceanic sea state measurements

Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true ?4-D reconstruction.? However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.