Semantic Integration of Heterogeneous Recognition Systems

Abstract

Computer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information from existing modules to calculate results that are more accurate and complete. The method uses semantic description of concepts and reasoning to manage syntactic differences between information returned by modules. The semantic description is based on existing real-world concepts in video recognition and ubiquitous systems. We propose helper functionalities such as: module credibility rating, confidence level declaration and selection of communication protocol. Two integration modes are defined: voting of matching concepts and aggregation of complementing concepts.