Clone project git clone https://github.com/gnocchiflette/FUSION-human-action-recognition Create virtual environment make create_environment Activate environment (do so every time you work on this repository) workon fusion (for virtual env wrapper) source activate fusion (for conda) Install requirement...
Human activity recognition is a crucial domain in computer science and artificial intelligence that involves the Detection, Classification, and Prediction of human activities using sensor data such as accelerometers, gyroscopes, etc. This field utilizes time-series signals from sensors present in smartphon...
The recognition of human actions in video streams is a challenging task in computer vision, with cardinal applications in brain–computer interfaces and surveillance, for example. Recently, deep learning has produced remarkable results, but it can be har
Human Action Recognition (HAR) is a popular area of research in computer vision due to its wide range of applications such as surveillance, health care, and gaming, etc. Action recognition based on 3D skeleton data allows simplistic, cost-efficient models to be formed making it a widely used ...
he Project is structured in 9Work Packages, which are constantly working together on the Project objectives, and cover the main specialty fields of the research conducted in the Project. 该项目由9个Work Packages组成,这些Work Packages不断地在项目目标上进行合作,并涵盖了项目中所进行研究的主要专业领域...
The main component of our human-activity recognition method is action recognition via non-parametric matching of trajectory data and instantaneous motion descriptors, fused via a Bayes net. This is split into two stages, as can be seen in the bottom and middle sections of Fig. 1 (respectively,...
Recent works on human action recognition have focused on representing and classifying articulated body motion. These methods require a detailed knowledge of the action composition both in the spatial and temporal domains, which is a difficult task, most notably under real-time conditions. As such, ...
Then, a mapping is learned by applying an adaptive discriminant analysis (ADA) method to project AEI features into a low-dimensional subspace, such that the intra-class (activities performed by the same person) variations are minimized and the interclass (activities performed by different persons) ...
Esser, P., Rombach, R. & Ommer, B. Taming transformers for high-resolution image synthesis. InProc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)12873–12883 (IEEE, 2021). Kanervisto, A., Scheller, C. & Hautamäki, V. Action space shaping in deep reinforcement...
Our main contributions are the creation of the first integrated framework combining computer-vision-based and artificial-intelligence-based action recognition techniques which is Acknowledgement This research has been partly supported by the Spanish Ministry of Economy and Competitiveness under the project ...