Paper
27 February 2015 Shot boundary detection and label propagation for spatio-temporal video segmentation
Author Affiliations +
Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 94050D (2015) https://doi.org/10.1117/12.2076661
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
This paper proposes a two stage algorithm for streaming video segmentation. In the first stage, shot boundaries are detected within a window of frames by comparing dissimilarity between 2-D segmentations of each frame. In the second stage, the 2-D segments are propagated across the window of frames in both spatial and temporal direction. The window is moved across the video to find all shot transitions and obtain spatio-temporal segments simultaneously. As opposed to techniques that operate on entire video, the proposed approach consumes significantly less memory and enables segmentation of lengthy videos. We tested our segmentation based shot detection method on the TRECVID 2007 video dataset and compared it with block-based technique. Cut detection results on the TRECVID 2007 dataset indicate that our algorithm has comparable results to the best of the block-based methods. The streaming video segmentation routine also achieves promising results on a challenging video segmentation benchmark database.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sankaranaryanan Piramanayagam, Eli Saber, Nathan D. Cahill, and David Messinger "Shot boundary detection and label propagation for spatio-temporal video segmentation", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050D (27 February 2015); https://doi.org/10.1117/12.2076661
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Cited by 6 scholarly publications.
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KEYWORDS
Image segmentation

Video

Detection and tracking algorithms

3D video streaming

Algorithm development

Image processing

Precision measurement

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