2017 |
A Zlatintsi, P Koutras, G Evangelopoulos, N Malandrakis, N Efthymiou, K Pastra, A Potamianos, P Maragos COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization Journal Article EURASIP Journal on Image and Video Processing, 54 , pp. 1–24, 2017. Abstract | BibTeX | Links: [PDF] @article{ZKE+17, title = {COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization}, author = {A Zlatintsi and P Koutras and G Evangelopoulos and N Malandrakis and N Efthymiou and K Pastra and A Potamianos and P Maragos}, url = {http://robotics.ntua.gr/wp-content/publications/Zlatintsi+_COGNIMUSEdb_EURASIP_JIVP-2017.pdf}, doi = {doi 10.1186/s13640-017-0194}, year = {2017}, date = {2017-01-01}, journal = {EURASIP Journal on Image and Video Processing}, volume = {54}, pages = {1--24}, abstract = {Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video database, namely COGNIMUSE, annotated with sensory and semantic saliency, events, cross-media semantics, and emotion. The purpose of this database is manifold; it can be used for training and evaluation of event detection and summarization algorithms, for classification and recognition of audio-visual and cross-media events, as well as for emotion tracking. In order to enable comparisons with other computational models, we propose state-of-the-art algorithms, specifically a unified energy-based audio-visual framework and a method for text saliency computation, for the detection of perceptually salient events from videos. Additionally, a movie summarization system for the automatic production of summaries is presented. Two kinds of evaluation were performed, an objective based on the saliency annotation of the database and an extensive qualitative human evaluation of the automatically produced summaries, where we investigated what composes high-quality movie summaries, where both methods verified the appropriateness of the proposed methods. The annotation of the database and the code for the summarization system can be found at http://cognimuse.cs.ntua.gr/database.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video database, namely COGNIMUSE, annotated with sensory and semantic saliency, events, cross-media semantics, and emotion. The purpose of this database is manifold; it can be used for training and evaluation of event detection and summarization algorithms, for classification and recognition of audio-visual and cross-media events, as well as for emotion tracking. In order to enable comparisons with other computational models, we propose state-of-the-art algorithms, specifically a unified energy-based audio-visual framework and a method for text saliency computation, for the detection of perceptually salient events from videos. Additionally, a movie summarization system for the automatic production of summaries is presented. Two kinds of evaluation were performed, an objective based on the saliency annotation of the database and an extensive qualitative human evaluation of the automatically produced summaries, where we investigated what composes high-quality movie summaries, where both methods verified the appropriateness of the proposed methods. The annotation of the database and the code for the summarization system can be found at http://cognimuse.cs.ntua.gr/database. |
2007 |
Konstantinos Rapantzikos, Georgios Evangelopoulos, Petros Maragos, Yannis Avrithis An audio-visual saliency model for movie summarization Conference 2007 IEEE 9Th International Workshop on Multimedia Signal Processing, MMSP 2007 - Proceedings, 2007, ISBN: 1424412749. Abstract | BibTeX | Links: [PDF] @conference{219, title = {An audio-visual saliency model for movie summarization}, author = { Konstantinos Rapantzikos and Georgios Evangelopoulos and Petros Maragos and Yannis Avrithis}, url = {http://robotics.ntua.gr/wp-content/uploads/publications/RapantzikosEvangelopoulosMaragosEtAl_AVSaliencyDetectionSummarization_mmsp07.pdf}, doi = {10.1109/MMSP.2007.4412882}, isbn = {1424412749}, year = {2007}, date = {2007-01-01}, booktitle = {2007 IEEE 9Th International Workshop on Multimedia Signal Processing, MMSP 2007 - Proceedings}, pages = {320--323}, abstract = {A saliency-based method for generating video summaries is presented, which exploits coupled audiovisual information from both media streams. Efficient and advanced speech and image processing algorithms to detect key frames that are acoustically and visually salient are used. Promising results are shown from experiments on a movie database.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } A saliency-based method for generating video summaries is presented, which exploits coupled audiovisual information from both media streams. Efficient and advanced speech and image processing algorithms to detect key frames that are acoustically and visually salient are used. Promising results are shown from experiments on a movie database. |
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