A semi-automatic toolbox for markerless effective semantic feature extraction

Abstract

VisionTool is an open-source python toolbox for semantic features extraction, capable to provide accurate features detectors for different applications, including motion analysis, markerless pose estimation, face recognition and biological cell tracking. VisionTool leverages transfer-learning with a large variety of deep neural networks allowing high-accuracy features detection with few training data. The toolbox offers a friendly graphical user interface, efficiently guiding the user through the entire process of features extraction. To facilitate broad usage and scientific community contribution, the code and a user guide are available at https://github.com/Malga-Vision/VisionTool.git.

Automatic video analysis and classification of sleep‐related hypermotor seizures and disorders of arousal

“…This option was made possible by the increasing progress—in terms of accuracy and performance—of deep learning algorithms in addressing video analysis 23 . Nowadays, video analysis has been exploited to quantitatively analyze human motion 24,25 with promising results in many fields, including the medical domain (e.g., physical rehabilitation 26,27 ). However, few studies up to now have been performed in the epilepsy field 28–30 …”