PT Unknown
AU Albert Clapes
   Miguel Reyes
   Sergio Escalera
TI User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis
BT 7th Conference on Articulated Motion and Deformable Objects
PY 2012
BP 1
EP 11
VL 7378
DI 10.1007/978-3-642-31567-1_1
AB We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
ER