Determining structure in continuously recorded videos

In this paper, we present a scene detection framework on continuously recorded videos. Conventional temporal scene segmentation methods work for the videos composed of discrete shots, where shot boundaries are clearly defined. The proposed method detects scene segments by the spectral clustering technique and fuzzy analysis. The detected scenes are represented by the corresponding representative feature values of the feature clusters, rather than abrupt temporal boundaries. The feature clusters are generated using the spectral clustering technique. The video units have the fuzzy memberships to the feature clusters, which are generated using the Hyperbolic tangent fuzzy function. The scenes are collected from the candidate scenes from each cluster. The proposed method has been tested on several video sequences, and very promising results have been obtained. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing General Terms Algorit...

• Type: Conference
• Year: 2005
• Where: MM
• Authors: Yun Zhai, Mubarak Shah
• Keywords: Feature Clusters, MM 2005, Spectral Clustering, Spectral Clustering Technique