PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Video segmentation and shot boundary detection using self-organizing maps.
Hannes Muurinen and Jorma Laaksonen
In: 15th Scandinavian Conference on Image Analysis (SCIA 2007), 10-14 June 2007, Aalborg, Denmark.


We present a video shot boundary detection (SBD) algorithm that spots discontinuities in visual stream by monitoring video frame trajectories on Self-Organizing Maps (SOMs). The SOM mapping compensates for the probability density differences in the feature space, and consequently distances between SOM coordinates are more informative than distances between plain feature vectors. The proposed method compares two sliding best-matching unit windows instead of just measuring distances between two trajectory points, which increases the robustness of the detector. This can be seen as a variant of the adaptive threshold SBD methods. Furthermore, the robustness is increased by using a committee machine of multiple SOM-based detectors. Experimental evaluation made by NIST in the TRECVID evaluation confirms that the SOM-based SBD method works comparatively well in news video segmentation, especially in gradual transition detection.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Multimodal Integration
Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:3641
Deposited By:Jorma Laaksonen
Deposited On:14 February 2008