Zobrazeno 1 - 10
of 918
pro vyhledávání: '"Li, Xiaobai"'
This paper presents VisioPhysioENet, a novel multimodal system that leverages visual cues and physiological signals to detect learner engagement. It employs a two-level approach for visual feature extraction using the Dlib library for facial landmark
Externí odkaz:
http://arxiv.org/abs/2409.16126
Remote photoplethysmography (rPPG) is a non-contact method for measuring cardiac signals from facial videos, offering a convenient alternative to contact photoplethysmography (cPPG) obtained from contact sensors. Recent studies have shown that each i
Externí odkaz:
http://arxiv.org/abs/2407.04127
Engagement analysis finds various applications in healthcare, education, advertisement, services. Deep Neural Networks, used for analysis, possess complex architecture and need large amounts of input data, computational power, inference time. These c
Externí odkaz:
http://arxiv.org/abs/2404.09474
Autor:
Vedernikov, Alexander, Sun, Zhaodong, Kykyri, Virpi-Liisa, Pohjola, Mikko, Nokia, Miriam, Li, Xiaobai
Engagement measurement finds application in healthcare, education, services. The use of physiological and behavioral features is viable, but the impracticality of traditional physiological measurement arises due to the need for contact sensors. We de
Externí odkaz:
http://arxiv.org/abs/2404.04394
Analysis of non-typical emotions, such as stress, depression and engagement is less common and more complex compared to that of frequently discussed emotions like happiness, sadness, fear, and anger. The importance of these non-typical emotions has b
Externí odkaz:
http://arxiv.org/abs/2403.08824
The ability to generate sentiment-controlled feedback in response to multimodal inputs comprising text and images addresses a critical gap in human-computer interaction. This capability allows systems to provide empathetic, accurate, and engaging res
Externí odkaz:
http://arxiv.org/abs/2402.07640
Autor:
Sun, Zhaodong, Li, Xiaobai
Video-based remote physiological measurement utilizes facial videos to measure the blood volume change signal, which is also called remote photoplethysmography (rPPG). Supervised methods for rPPG measurements have been shown to achieve good performan
Externí odkaz:
http://arxiv.org/abs/2309.06924
Autor:
Kumar, Puneet, Li, Xiaobai
This paper aims to demonstrate the importance and feasibility of fusing multimodal information for emotion recognition. It introduces a multimodal framework for emotion understanding by fusing the information from visual facial features and rPPG sign
Externí odkaz:
http://arxiv.org/abs/2306.02845
This paper proposes a multimodal emotion recognition system, VIsual Spoken Textual Additive Net (VISTANet), to classify emotions reflected by input containing image, speech, and text into discrete classes. A new interpretability technique, K-Average
Externí odkaz:
http://arxiv.org/abs/2208.11450
Contrast-Phys: Unsupervised Video-based Remote Physiological Measurement via Spatiotemporal Contrast
Autor:
Sun, Zhaodong, Li, Xiaobai
Video-based remote physiological measurement utilizes face videos to measure the blood volume change signal, which is also called remote photoplethysmography (rPPG). Supervised methods for rPPG measurements achieve state-of-the-art performance. Howev
Externí odkaz:
http://arxiv.org/abs/2208.04378