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 final output is collected from the candidate scenes from all clusters. The proposed method has been tested on several video sequences, and very promising results have been obtained.
['Yun Zhai', 'Mubarak Shah']
Determining structure in continuously recorded videos