Hello, In this post I will give a brief presentation of the software HandGenerator, that I created to generate the synthetic dataset used in the publication (A.Memo, L. Minto and P. Zanuttigh, “Exploiting Silhouette Descriptors and Synthetic Data for Hand Gesture Recognition”, STAG: Smart Tools & Apps for Graphics .

To download and test the library, to see it’s capabilities, please follow this link to the LTTM Laboratory at the University of Padua, HandGenerator@LTTM.

The library enables the user to have an intuitive GUI to set up the hand pose, and then recursively generate a large dataset with its parameters. The possibility for customization allow for a wide field of usage, from color-based datasets to depth-based (as the one used in the paper above): this is done exploiting the possibility of using custom shaders for the OpenGL pipeline that render the 3D model, and in this case the results are shown below.