Monitoring Application-driven Continuous Affect Recognition From Video Frames

Author:

Hwooi Stephen Khor Wen1ORCID,Othmani Alice2ORCID,Sabri Aznul Qalid Md1ORCID

Affiliation:

1. Department of Artificial Intelligence, University of Malaya, Malaysia

2. Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Universite Paris-Est Creteil, France

Funder

MATCH2021: Malaysia France Bilateral Research Grant

Publisher

ACM

Reference28 articles.

1. 2016. Microsoft cognitive services - emotion api . Retrieved January 12, 2016 from https://www.microsoft.com/cognitive-services/en-us/emotion-api 2016. Microsoft cognitive services - emotion api. Retrieved January 12, 2016 from https://www.microsoft.com/cognitive-services/en-us/emotion-api

2. Gediminas Adomavicius and Alexander Tuzhilin . 2005. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions . IEEE transactions on knowledge and data engineering 17, 6 ( 2005 ), 734–749. Gediminas Adomavicius and Alexander Tuzhilin. 2005. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering 17, 6 (2005), 734–749.

3. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video

4. Wen-Sheng Chu , Fernando De la Torre , and Jeffrey  F. Cohn . 2016. Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection. ArXiv abs/1608.00911 ( 2016 ). Wen-Sheng Chu, Fernando De la Torre, and Jeffrey F. Cohn. 2016. Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection. ArXiv abs/1608.00911 (2016).

5. Corinna Cortes and Vladimir Vapnik . 1995. Support-vector networks. Machine learning 20, 3 ( 1995 ), 273–297. Corinna Cortes and Vladimir Vapnik. 1995. Support-vector networks. Machine learning 20, 3 (1995), 273–297.

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