Paper
18 December 2003 Content-based video indexing and retrieval using the Radon transform and pattern matching
Mehmet Celenk, Qiang Zhou, Peng Wang
Author Affiliations +
Abstract
Content-based video indexing and retrieval exhibits many challenging problems. Methods developed for processing of video for content search can be roughly categorized into temporal segmentation, spatial segmentation, and spatio-temporal video segmentation. The temporal segmentation aims to divide video into clips or (usually) camera shots. The spatial segmentation, on the other hand, seeks for the ROI’s (regions of interests) in video frames. The spatio-temporal segmentation is, however, more general since the video data is essentially spatial and temporal domain function in nature. It is expected that spatiotemporal methods describe the video content more completely and accurately as compared to the temporal and spatial segmentation of video independently. In the presented work, we approach the video-indexing problem by means of the spatio-temporal Radon projections. Specific projections are chosen for indexing the extracted features of a video clip. Pattern matching and pattern search are also studied via these projection-based features. Experiments show promising results for our approach.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehmet Celenk, Qiang Zhou, and Peng Wang "Content-based video indexing and retrieval using the Radon transform and pattern matching", Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); https://doi.org/10.1117/12.522014
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Cited by 1 scholarly publication.
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KEYWORDS
Video

Radon transform

Image segmentation

Video surveillance

Radon

Video processing

Distance measurement

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