This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ...

Most Convolutional Neural Networks make use of subsampling layers to reduce dimensionality and keep only the most essential information, besides turning the model more robust to rotation and translation variations. One of ...

Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer ...

Gait é um tipo de biometria que diferencia os indivíduos pela forma como andam. Pesquisas relacionadas a essa biometria estão ganhando evidência devido à vantagem de gait ser discreto e poder ser capturado a distância, o ...

Due to their number of parameters, convolutional neural networks are known to take long training periods and extended inference time. Learning may take so much computational power that it requires a costly machine and, ...

Tensor-based representations have been widely pursued in the last years due to the increasing number of high-dimensional datasets, which might be better described by the multilinear algebra. In this paper, we introduced a ...

Gait can be described mechanically by the time series of a set of biomechanical variables, e.g. the time series of the ground reaction forces. These time series can be analyzed by their correlations with orthogonal functions, ...