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This work addresses the development of a unified approach to content-based indexing and retrieval of digital videos fromtelevision archives. The proposed approach has been designed to deal with arbitrary television genres, making it suitablefor various applications. To achieve this goal, the main steps of a content-based video retrieval system are addressed in thiswork, namely: video segmentation, key-frame extraction, content-based video indexing and the video retrieval operation itself.Video segmentation is addressed as a typical TV broadcast structuring problem, which consists in automatically determiningthe boundaries of each broadcasted program (like movies, news, among others) and inter-program (for instance, commercials).Specifically, to segment the videos, Electronic Program Guide (EPG) metadata is combined with the detection of two specialcues, namely, audio cuts (silence) and dark monochrome frames. On the other hand, a color histogram-based approach performskey-frame extraction. Video indexing and retrieval are accomplished by using hashing and k-d tree methods, while visualsignatures containing color, shape and texture information are estimated for the key-frames, by using image and frequencydomain techniques. Experimental results with the dataset of a multimedia information system especially developed for managingtelevision broadcast archives demonstrate that our approach works efficiently, retrieving videos in 0.16 seconds on average andachieving recall, precision and F1 measure values, as high as 0.76, 0.97 and 0.86 respectively.

A unified approach to content-based indexing and retrieval of digital videos from television archives