Title :
From video shot clustering to sequence segmentation
Author :
Veneau, Emmanuel ; Ronfard, Rémi ; Bouthemy, Patrick
Author_Institution :
Inst. Nat. de l´´Audiovisuel, Bry-sur-Marne, France
Abstract :
Segmenting video documents into sequences from elementary shots to supply an appropriate higher level description of the video is a challenging task. The 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
Keywords :
image segmentation; image sequences; pattern clustering; binary agglomerative hierarchical time-constrained shot clustering; breaking distance; cophenetic criterion; higher level description; sequence changes; sequence segmentation; two-stage method; video shot clustering; Buildings; Data mining; Feature extraction; Gunshot detection systems; Indexing; Layout; Merging; Symmetric matrices;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.902907