Hierarchical Shot Clustering for Video Summarization
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
Where Does Computational Media Aesthetics Fit?
IEEE MultiMedia
Indexing and mining audiovisual data
AM'03 Proceedings of the Second international conference on Active Mining
| Hi-index | 0.00 |
Segmenting video documents into sequences from elementary shots to supply an appropriate higher-level description of the video is a challenging task. This paper presents a two-stage method. First, we build a binary agglomerative hierarchical time-constrained shot clustering. Second, based on the cophenetic criterion, a breaking distance between shots is computed to detect sequence changes. Various options are implemented and compared. Real experiments have proved that the proposed criterion can be efficiently used to achieve appropriate segmentation into sequences.