Video-Based Sentiment Analysis with hvnLBP-TOP Feature and bi-LSTM
DOI:
https://doi.org/10.1609/aaai.v33i01.33019963Abstract
In this paper, we propose a new feature extraction method called hvnLBP-TOP for video-based sentiment analysis. Furthermore, we use principal component analysis (PCA) and bidirectional long short term memory (bi-LSTM) for dimensionality reduction and classification. We achieved an average recognition accuracy of 71.1% on the MOUD dataset and 63.9% on the CMU-MOSI dataset.
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Published
2019-07-17
How to Cite
Li, H., & Xu, H. (2019). Video-Based Sentiment Analysis with hvnLBP-TOP Feature and bi-LSTM. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9963-9964. https://doi.org/10.1609/aaai.v33i01.33019963
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Student Abstract Track