The KnowDPI project is to create a framework for an adaptive object detection on different types of data. For that, the framework will use the semantic technologies in order to understand the context of the detection and determine the most adapted algorithms for the processing. This processing will be created according to the type of user query, and available algorithms for this type and quality of data in order to obtain the best result. In order to realize a such framework, three main goals must be attempted. The first is the design of an automatic and adaptive processing of heterogeneous data. The second is to optimize dynamically the algorithms combination and parameterization. The third will be to create a system of learning which could improve the object detection.
The first year of this project has been composed of two main activities. The first activities has been toÂ research in the literature if some existing system of object detection use the semantic technologies in order to identify the differentÂ existing approaches. The second activity which corresponds to design theÂ framework model, begin quickly. This first step of design has conducted to the identification of the framework requirements.Â The conceptual model of the framework is composed of four modules which will interact together in order to satisfied the project goal.Â Each module has a specific role. One will content all information about data, algorithms and objects. Another will manage the algorithm execution according to the decision made by the third module. Finally, the fourth module will be a learning system.
Â Â The result of these activities is a set of concepts which will be the base for the development of this framework.Â Some of these concepts are illustrated by following pictures. Â