User identification and object recognition in clutter scenes based on RGB-depth analysis

Authors:
Albert Clapés;Miguel Reyes;Sergio Escalera
Affiliations:
Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain, Computer Vision Center, Bellaterra, Spain;Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain, Computer Vision Center, Bellaterra, Spain;Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona, Spain, Computer Vision Center, Bellaterra, Spain
Venue:
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
Year:
2012

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Abstract

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.