One of the challenges in the development of content-based multimedia indexing and retrieval application is to achieve an efficient retrieval scheme. The developers and users who are accustomed to making queries and thus retrieving any multimedia item from a large scale database can be frustrated by the long query times and memory and minimum system requirements. This paper presents a novel retrieval technique, which is designed to bring an effective solution especially for queries on large-scale multimedia databases and furthermore to provide instantaneous query retrievals along with the ongoing query process. In this way it achieves a series of sub-query results that will finally be converging to the fullscale search retrieval in a faster and significantly lower memory with no minimum system requirements. Experimental progressive query retrieval results show that the intermediate sub-query retrieval results might achieve such a retrieval performance that requires no further query processing time. 1.

MUVIS is a series of CBIR systems. The first one has been developed in late 90s to support indexing and retrieval in large image databases using visual and semantic features such as color, texture and shape. During recent years. MUVIS has been reformed to become a PC-based framework, which supports indexing, browsing and querying of various multimedia types such as audio. video, audiohideo interlaced and several image formats. MUVIS system allows real-time audio and video capturing, encoding by last generation codecs such as MPEG-4. H.263+. MP3 and AAC. It supports several audiohideo file format such as AVI, MP4, MP3 and AAC. Furthermore. MWIS system provides a well-defined interface for third parties to integrate their own feature extraction algorithms into the framework and for this reason it has recently been adopted by COST 21 lquat as COST framework for CBR. In this paper. we describe the general system features with underlying applications and outline the main philosophy. 1.

First MUVIS system has been developed three years ago, supporting image indexing and means to retrieve images from large image databases using image visual and semantic features such as color, texture and shape. Recently, MUVIS project has been reformed to become a PC-based system, which supports indexing, browsing and querying on various multimedia types such as audio, video and image. Furthermore the system allows real-time audio and video capturing, encoding by last generation codecs such as MPEG-4 or H.263+ if requested, recording while indexing into a database in such a way that they can be retrieved efficiently. In this paper, we describe the system features with underlying applications and outline the mean philosophy. Query and browsing capabilities of the MUVIS technology will be demonstrated during the conference. 1.