Video-Based Sentiment Analysis with hvnLBP-TOP Feature and bi-LSTM

No. 1: AAAI-19, IAAI-19, EAAI-20

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 33

Student Abstract Track

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.

10.1609/aaai.v33i01.33019963