Search

Your search keyword '"Du, Bixuan"' showing total 9 results
Start Over Author "Du, Bixuan" Publication Year Range Last 10 years
9 results on '"Du, Bixuan"'

2. Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition

Author

Liu, Shenglan, Guo, Shuai, Qiao, Hong, Wang, Yang, Wang, Bin, Luo, Wenbo, Zhang, Mingming, Zhang, Keye, and Du, Bixuan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Human emotion recognition is an important direction in the field of biometric and information forensics. However, most existing human emotion research are based on the single RGB view. In this paper, we introduce a RGBD video-emotion dataset and a RGBD face-emotion dataset for research. To our best knowledge, this may be the first RGBD video-emotion dataset. We propose a new supervised nonlinear multi-view laplacian eigenmaps (MvLE) approach and a multihidden-layer out-of-sample network (MHON) for RGB-D humanemotion recognition. To get better representations of RGB view and depth view, MvLE is used to map the training set of both views from original space into the common subspace. As RGB view and depth view lie in different spaces, a new distance metric bag of neighbors (BON) used in MvLE can get the similar distributions of the two views. Finally, MHON is used to get the low-dimensional representations of test data and predict their labels. MvLE can deal with the cases that RGB view and depth view have different size of features, even different number of samples and classes. And our methods can be easily extended to more than two views. The experiment results indicate the effectiveness of our methods over some state-of-art methods.

Published
2018

5. Construction and validation of the Dalian emotional movement open-source set (DEMOS).

Author

Zhang, Mingming, Yu, Lu, Zhang, Keye, Du, Bixuan, Zhan, Bin, Jia, Shuxin, Chen, Shaohua, Han, Fengxu, Li, Yiwen, Liu, Shuaicheng, Yi, Xi, Liu, Shenglan, and Luo, Wenbo

Subjects
SADNESS, EMOTION recognition, AFFECTIVE computing, HUMAN mechanics, SOCIAL perception, STIMULUS & response (Psychology)
Abstract

Human body movements are important for emotion recognition and social communication and have received extensive attention from researchers. In this field, emotional biological motion stimuli, as depicted by point-light displays, are widely used. However, the number of stimuli in the existing material library is small, and there is a lack of standardized indicators, which subsequently limits experimental design and conduction. Therefore, based on our prior kinematic dataset, we constructed the Dalian Emotional Movement Open-source Set (DEMOS) using computational modeling. The DEMOS has three views (i.e., frontal 0°, left 45°, and left 90°) and in total comprises 2664 high-quality videos of emotional biological motion, each displaying happiness, sadness, anger, fear, disgust, and neutral. All stimuli were validated in terms of recognition accuracy, emotional intensity, and subjective movement. The objective movement for each expression was also calculated. The DEMOS can be downloaded for free from https://osf.io/83fst/. To our knowledge, this is the largest multi-view emotional biological motion set based on the whole body. The DEMOS can be applied in many fields, including affective computing, social cognition, and psychiatry. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results