Program segmentation in a television stream using acoustic cues

In a digital media asset management system, TV program segmentation is a key step for the long videos recorded from television channels to be represented in the hierarchical structure. In this paper, a novel approach based on acoustic cues for automatic segmenting television stream into individual programs is proposed. This presented method is composed of the following steps: (1) Several sets of repetitions in the audio track is detected by using silence detection and robust audio hashing; (2) The found repetitions are treated as advertisements if the range of their length is from 5 seconds to 120 seconds; (3) Programs are segmented from the recorded TV streams using the detected advertisements. Experiments on real-world TV recordings show the effectiveness of the proposed approach.