The image of a planar mirror reflection (IPMR) can be interpreted as a virtual view of the scene, acquired by a camera with a pose symmetric to the pose of the real camera with respect to the mirror plane. The epipolar geometry of virtual views associated with different IPMRs is well understood, and it is possible to recover the camera motion and perform 3D scene reconstruction by applying standard structure-from-motion methods that use image correspondences as input. In this article we address the problem of estimating the pose of the real camera, as well as the positions of the mirror plane, by assuming that the rigid motion between N virtual views induced by planar mirror reflections is known. The solution of this problem enables the registration of objects lying outside the camera field-of-view, which can have important applications in domains like non-overlapping camera network calibration and robot vision. We show that the positions of the mirror planes can be uniquely determined by solving a system of linear equations. This enables to estimate the pose of the real camera in a straightforward closed-form manner using a minimum of N = 3 virtual views. Both synthetic tests and real experiments show the superiority of our approach with respect to current state-of-the-art methods.

Brazil is responsible for 27% of the world production of soybeans and 7% of maize. Mato Grosso and Para states in Brazil are among the largest producer. The viability to the cultivation of maize (Zea mays) and soybeans (Glycine max), for future climate scenarios (2070-2100, GHG) is evaluated based on crop modeling (DSSAT) forced by observational data and regional climate simulations (HadRM3). The results demonstrated that a substantial reduction in the yield in particular for maize may be expected for the end of the 21 st century. Distinct results are found for soybeans. By applying the A2 climate changes scenario, soybean yield rises by up top 60% assuming optimum soil treatment and no water stress. However, by analyzing the inter-annual variability of crop yields for both maize and soybean, could be demonstrated larger year-to-year fluctuations under greenhouse warming conditions as compared to current conditions, leading to very low productivity by the end of the 21 st century. Therefore, these Brazilian states do not appear to be economically suitable for a future cultivation of maize and soybeans. Improved adaptation measures and soil management may however partially alleviate the negative climate change effect.

The present study aims (a) to translate and adapt the Igroup Presence Questionnaire (IPQ) to the Portuguese context (semantic equivalence/ conceptual and content validity) and (b) to examine its psychometric properties (reliability and factorial validity). The sample consisted of 478 subjects (285 males and 193 females). The fidelity of the factors varied between 0.53 and 0.83. The confirmatory factor analysis results produced a 14-item version of IPQ-PT, accepting covariance between residual errors of some items of the instrument, as the best structural representation of the data analyzed. The CFA was conducted based on a three-variable model. The fit indexes obtained were X2/df = 2.647, GFI = .948, CFI = .941, RSMEA = .059, and AIC = 254. These values demonstrate that the proposed Portuguese translation of the IPQ maintains its original validity, demonstrating it to be a robust questionnaire to measure the sense of presence in virtual reality studies. It is therefore recommended for use in presence research when using Portuguese samples.