Title :
Video Segmentation Using Acoustic Analysis
Author :
Zhang, Shilin ; Gu, Mei
Author_Institution :
Fac. of Comput. Sci., North China Univ. of Technol., Beijing, China
Abstract :
Video 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: Several sets of repetitions in the audio track is detected by using silence detection and robust audio hashing; The found repetitions are treated as advertisements if the range of their length is from 5 seconds to 120 seconds; 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.
Keywords :
acoustic signal processing; audio signal processing; image segmentation; television; video signal processing; acoustic analysis; acoustic cues; audio track; automatic television stream segmentation; hierarchical structure; real world TV recording; recorded TV streams; robust audio hashing; silence detection; television channels; video segmentation; Acoustics; Advertising; Arrays; Databases; Robustness; Streaming media; TV; Video Segmentation; audio hashing; video retrieval;
Conference_Titel :
Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on
Conference_Location :
Huanggang
Print_ISBN :
978-1-4244-8148-4
Electronic_ISBN :
978-0-7695-4196-9
DOI :
10.1109/IPTC.2010.134