A Framework For Video Data Indexing Using Data Mining

The amount of information produced every year is rapidly growing due to many factors. Among all media, video is a particular media embedding visual, motion, audio and textual information. Given this huge amount of information the researchers need general framework for video data mining to be applied to the raw videos (surveillance videos, news reading, Person reading books in library etc.). The first step of our framework for mining raw video data is grouping input frames to a set of basic units which are relevant to the structure of the video. The second step is charactering the unit to cluster of similar groups, to detect interesting patterns. To do this we extract some features (object, colors etc.) from the unit. A histogram based color descriptors also introduced to reliably capture and represent the color properties of multiple images. The preliminary experimental studies indicate that the proposed framework is promising.