Human pose analysis system and method

A method for extracting human pose information from an image, comprising:

• receiving an image;
• extracting human-related image features from the image using a feature extractor, the feature extractor being connectable to a database comprising a dataset of reference images and provided with a first convolutional neural network (CNN) architecture including a first plurality of CNN layers, each convolutional layer applies convolutional operation to its input data using trained kernel weights;
• and
• determining the human pose information using at least one of the following modules:
• a 2D body skeleton detector for determining 2D body skeleton information from the human-related image features;
• a body silhouette detector for determining body silhouette information from the human-related image features;
• a hand silhouette detector for determining hand silhouette detector from the human-related image features;
• a hand skeleton detector for determining hand skeleton from the human-related image features;
• a 3D body skeleton detector for determining 3D body skeleton from the human-related image features;
• and
• a facial keypoints detector for determining facial keypoints from the human-related image features,
• wherein each one of the 2D body skeleton detector, the body silhouette detector, the hand silhouette detector, the hand skeleton detector, the 3D body skeleton detector and the facial keypoints detector is provided with a second convolutional neural network (CNN) architecture including a second plurality of CNN layers.