We present a model that automatically divides broadcast videos into coherent scenes by learning a distance measure between shots. Experiments are performed to demonstrate the effectiveness of our approach by comparing our algorithm against recent proposals for automatic scene segmentation. We also propose an improved performance measure that aims to reduce the gap between numerical evaluation and expected results, and propose and release a new benchmark dataset.
A Deep Siamese Network for Scene Detection in Broadcast Videos / Baraldi, Lorenzo; Grana, Costantino; Cucchiara, Rita. - ELETTRONICO. - (2015), pp. 1199-1202. (Intervento presentato al convegno 23rd ACM International Conference on Multimedia, MM 2015 tenutosi a Brisbane, Australia nel 26-30 October 2015) [10.1145/2733373.2806316].
A Deep Siamese Network for Scene Detection in Broadcast Videos
BARALDI, LORENZO;GRANA, Costantino;CUCCHIARA, Rita
2015
Abstract
We present a model that automatically divides broadcast videos into coherent scenes by learning a distance measure between shots. Experiments are performed to demonstrate the effectiveness of our approach by comparing our algorithm against recent proposals for automatic scene segmentation. We also propose an improved performance measure that aims to reduce the gap between numerical evaluation and expected results, and propose and release a new benchmark dataset.File | Dimensione | Formato | |
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