2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDARS-6.6
Paper Title VIDEO MEMORABILITY PREDICTION VIA LATE FUSION OF DEEP MULTI-MODAL FEATURES
Authors Roberto Leyva, Victor Sanchez, University of Warwick, United Kingdom
SessionARS-6: Image and Video Interpretation and Understanding 1
LocationArea H
Session Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Interpretation and Understanding
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Video memorability is a cornerstone in social media platform analysis, as a highly memorable video is more likely to be noticed and shared. This paper proposes a new framework to fuse multi-modal information to predict the likelihood of remembering a video. The proposed framework relies on late fusion of text, visual and motion features. Specifically, two neural networks extract features from the captions describing the video’s content; two ResNet models extract visual features from specific frames, and two 3DResNet models, combined with Fisher Vectors, extract features from the video’s motion information. The extracted features are used to compute several memorability scores via Bayesian Ridge regression, which are then fused based on a greedy search of the optimal fusion parameters. Experiments demonstrate the superiority of the proposed framework on the MediaEval2019 dataset, outperforming the state-of-the-art.