A technique for building databases of annotated and realistic human silhouettes based on an avatar

The real-time interpretation of video scenes and human motion is a research field with a lot of applications. Awidely used pre-processing step is the background subtraction, which highlights silhouettes. In addition, example-based and learning-based approaches are attractive for the interpretation of complex scenes. But to be effective, such techniques need to be trained on samples of realistic human silhouettes.
This paper presents a method to automatically build databases of artificial, realistic, and annotated human silhouettes. Our method, based on a 3D human avatar, allows to save additional data with the silhouettes, and to highlight the different body parts. These supplementary data may be application-driven. To help in evaluating the relevance of automatically generated databases, we suggest some practical solutions based on a visual
signature of the databases.