A lattice structure visualization by formal concept analysis and its application to huge image database

A lattice structure visualization method by formal concept analysis with respect to huge image databases, is proposed. Furthermore, a summarization method of the huge image databases is proposed based on the obtained lattice structure. The proposed algorithm firstly generates predictive frames from the original frames and divides them to blocks with suitable size. Then, we calculate standard deviation respect to each block, and construct information table, where the objects and attributes correspond to frames and the absolute mean of pixels in the block, respectively. A concept lattice with respect to the information table can be obtained by the formal concept analysis, and it is helpful to understand the overview of the image databases. The obtained lattice includes redundant elements, and the summarized information can be obtained by eliminating the redundant elements of the concept lattice. Through the experiment using the CAVIAR (context aware vision using image-based active recognition) database, it is confirmed the effectiveness of the proposed method.