Inexpensive solution for real-time video and image stitching

Image stitching is the process of joining several images to obtain a bigger view of a scene. It is used, for example, in tourism to transmit to the viewer the sensation of being in another place. I am presenting an inexpensive solution for automatic real time video and image stitching with two web cameras as the video/image sources. The proposed solution relies on the usage of several markers in the scene as reference points for the stitching algorithm. The implemented algorithm is divided in four main steps, the marker detection, camera pose determination (in reference to the markers), video/image size and 3d transformation, and image translation. Wii remote controllers are used to support several steps in the process. The built‐in IR camera provides clean marker detection, which facilitates the camera pose determination. The only restriction in the algorithm is that markers have to be in the field of view when capturing the scene. Several tests where made to evaluate the final algorithm. The algorithm is able to perform video stitching with a frame rate between 8 and 13 fps. The joining of the two videos/images is good with minor misalignments in objects at the same depth of the marker,misalignments in the background and foreground are bigger. The capture process is simple enough so anyone can perform a stitching with a very short explanation. Although real‐time video stitching can be achieved by this affordable approach, there are few shortcomings in current version. For example, contrast inconsistency along the stitching line could be reduced by applying a color correction algorithm to every source videos. In addition, the misalignments in stitched images due to camera lens distortion could be eased by optical correction algorithm. The work was developed in Apple’s Quartz Composer, a visual programming environment. A library of extended functions was developed using Xcode tools also from Apple.

Predição da criatividade e saúde mental

A criatividade tem sido mencionada desde há muito tempo pela literatura. A forma de a conceptualizar tem dependido em muito dos investigadores e da sua visão sobre o que é criatividade, porém as suas potencialidades têm tomado cada vez mais interesse pela comunidade científica. Os seus benefícios estendem-se a diversas áreas da vida humana, como sentimentos de satisfação, bem-estar e saúde mental. A investigação aqui apresentada procura encontrar modelos preditivos de comportamentos criativos, pressupondo que estes poderão ser de grande auxílio para o desenvolvimento de um melhor bem-estar psicológico. Assim a investigação comportou o uso de quatro variáveis: a pessoa, o processo, o produto e o ambiente criativo. A amostra contou com 215 estudantes universitários e os resultados revelaram o encontro de quatro modelos preditivos de comportamentos criativos, com uma maior ênfase nas artes visuais e manuais. Conclui-se com a ideia de que a predição de produtos criativos é possível e que tal poderá ser preponderante para um bom desenvolvimento da saúde mental.

Varietal flavour compounds of four grape varieties producing Madeira wines

Boal, Malvasia, Sercial and Verdelho are the main white grape varieties used in Madeira wine production. To estimate the free fraction of varietal aroma compounds of these varieties, 39 samples of musts were analysed to determine their content of monoterpenols and C13 norisoprenoids (terpenoids), using dynamic headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry. The r-values for linearity studies of the analytical method used, varied between 0.977 (nerolidol) and 0.999 (linalool). The repeatability for each compound varied between 2.5% (citronellol) and 11.8% (β-ionone). The mean values from three vintages (1998, 1999 and 2000) confirmed that these musts have differentiated contents of terpenoids. In opposition to Verdelho musts, Malvasia showed the highest free terpenoids content. In order to establish relations between the compounds and the varieties under investigation, principal component analysis and linear discriminant analysis were applied to the data, revealing a good separation and classification power between the four groups as a function of varietal origin.