Video-Based Sentiment Analysis with hvnLBP-TOP Feature and bi-LSTM
Haoran Li, Hua Xu · Proceedings of the AAAI Conference on Artificial Intelligence · 2019
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.