Mr. Jia Li Profile

Jia Li

at Joint Research & Development Lab

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Proceedings Article | 28 January 2008 Paper

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

Jia Li, Yonghong Tian, Wen Gao

Proceedings Volume 6822, 68220F (2008) https://doi.org/10.1117/12.759571

KEYWORDS: Video, Detection and tracking algorithms, Wavelets, Video processing, Feature extraction, Semantic video, Sensors, Wavelet transforms, Image segmentation, Algorithm development

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In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

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