Content-based Segmentation for Audio-Visual Information Retrieval
Speaker:
Petra Galuščáková
Abstract:
In this talk we deal with Information Retrieval from audio-visual
recordings. Such recordings are often long and a user may want to know the exact
relevant passage of the recording. Therefore, the recordings are automatically
divided into smaller parts, on which we apply standard retrieval techniques. We
experiment with various methods for segmentation of the recordings into shorter
segments which are then used in a standard retrieval setup to search for
relevant passages. The main focus will be on machine-learning based approaches
utilizing the content of the recordings. We will describe experiments performed
in two shared tasks of MediaEval Benchmark: Similar Segments in Social Speech
and Search and Hyperlinking.