Easy access to multimedia information is important as the amount of information is exponentially growing. Content-based retrieval is a viable approach. Extensibility and flexibility of data models is another important issue as the field is constantly evolving. The ADMIRE framework applied in this paper satisfies both criteria. This we show in two practical cases, one in the field of clinical assessments of measurement data, the other in the field of video directory services. ADMIRE offers a uniform solution for structuring these data. Content disclosure is supported by labelling of these data structures. This is done by automatic, semi-automatic or manual labelling.
This paper describes the results of an ongoing collaborative project between KPN Research and the Telematics Institute on multimedia information handling. The focus of the paper is the modelling and retrieval of audiovisual information. The paper presents a general framework for modeling multimedia information (ADMIRE) and discusses the application of this framework to the specific area of soccer video clips. The core of the paper is the integration of feature extraction and concept inference in a general framework for representing audio visual data. The work on feature extraction is built on existing feature extraction algorithms. The work on concept inference introduces a new approach to assigning semantics to collections of features in order to support concept-based retrieval, rather than feature-based retrieval. Finally, the paper describes our experiences with the implementation of the methods and techniques within the ADMIRE framework using a collection of commercially available tools. The latter is done by implementing a soccer video clip annotation and query tool.
Easy access to multimedia information is important as the amount of information is exponentially growing. Content-based retrieval is a viable approach. Extensibility and flexibility of data models is another important issue as the field is constantly evolving. The ADMIRE framework applied in this paper satisfies both criteria. This we show in two practical cases, one in the field of clinical assessments of measurement data, the other in the field of video directory services. ADMIRE offers a uniform solution for structuring these data. Content disclosure is supported by labelling of these data structures. This is done by automatic, semi-automatic or manual labelling.
