Abstract
Continuous emotion regression estimates moment-to-moment valence and arousal while a viewer watches a video. In familiar-video deployment, responses fron training participant-specific estimate, and prior-dominating fixed fusion tests whether physiology adds residual correction. In five-fold subject-held-out evaluation on 24was within 0.05 and 0.32 MAE of fusion in the internal and external evaluations, respectively. Source-explicit ablations showed that video identity and within-video tine accounted for most of the reduction, while EG-FNIRS gains were smaller and varied across participants and videos. These results identify the video-time prior as a strong, low-cost baseline and position EEG-fNIRS as an optional residual signal for familiar-video emotion regression.
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Cite this article
APA 7
Kong, M., Chen, J., Gao, Y., Meng, X., & Wang, R. (2026). Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos. https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos
MLA 9
Kong, Minghao, et al. "Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos." https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos.
Chicago (author–date)
Kong, Minghao, Jiurun Chen, Ying Gao, Xiangbin Meng, and Rongjie Wang. 2026. "Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos." https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos.
Harvard
Kong, M., Chen, J., Gao, Y., Meng, X. and Wang, R. (2026) 'Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos', Available at: https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos.
Vancouver
Kong M, Chen J, Gao Y, Meng X, Wang R. Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos. https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos
IEEE
M. Kong, J. Chen, Y. Gao, X. Meng, and R. Wang, "Low-Cost Video--Time Priors as a Strong Baseline for EEG--fNIRS Emotion Regression on Familiar Videos," https://omanscience.com/en/articles/low-cost-video-time-priors-as-a-strong-baseline-for-eeg-fnirs-emotion-regression-on-familiar-videos.