Nina S. T. Hirata

TL;DR: This work characterize the input data space, projection techniques, and the quality of projections, by several quantitative metrics, and samples these three spaces according to these metrics, aiming at good coverage with bounded effort.

TL;DR: De Oliveira et al. as discussed by the authors, C. Mendes, C. de Oliveira, and C. Pereira, 2013. Universidade do Sao Paulo. Instituto de Astronomia, Geofisica e Ciencias Atmosfericas; Brasil

TL;DR: This work employs Viola-Jones rapid object detection framework to address the problem of finding QR codes in arbitrarily acquired images and proposes a post-processing algorithm that aggregates the results of the first step and decides if the detected finder patterns are part of QR code symbols.

TL;DR: This work presents the central ideas of an approach based on the representation of transformations by collections of observed-ideal pairs of images and the estimation of suitable operators from these data based on statistical optimization or, equivalently, on a branch of Machine Learning Theory known as PAC Learning.