Semantic Scholar Open Access 2016 504 sitasi

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications

C. Corneanu Marc Oliu J. Cohn Sergio Escalera

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Abstrak

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.

Topik & Kata Kunci

Medicine Computer Science

Penulis (4)

C. Corneanu

Marc Oliu

J. Cohn

Sergio Escalera

Format Sitasi

APA MLA BibTeX

Corneanu, C., Oliu, M., Cohn, J., Escalera, S. (2016). Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications. https://doi.org/10.1109/TPAMI.2016.2515606

Akses Cepat

Lihat di Sumber doi.org/10.1109/TPAMI.2016.2515606

Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Total Sitasi: 504×
Sumber Database: Semantic Scholar
DOI: 10.1109/TPAMI.2016.2515606
Akses: Open Access ✓