Micro-expression recognition based on SqueezeNet and C3D

Shu-hua, Liu; Ren, Yushu; Li, Lanting; Sun, Xiaoyu; Yu, Shuang; Hung, Chih‐Cheng

doi:10.1007/s00530-022-00949-z

Cited by 8 publications

(5 citation statements)

References 29 publications

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“…is model could be used in the image sequence and video recognition. (4) C3D model [27,28]. e network constructed with 3D convolution and 3D pooling could be used to extract the spatial-temporal characteristics of video data for video recognition and other fields.…”

Section: Experimental Analysis and Resultsmentioning

confidence: 99%

Research on Animated GIFs Emotion Recognition Based on ResNet-ConvGRU

Zhang

Qing-dao-er-ji

2022

Mathematical Problems in Engineering

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Animated Graphics Interchange Format (GIF) images have become an important part of network information interaction, and are one of the main characteristics of analyzing social media emotions. At present, most of the research on GIF affection recognition fails to make full use of spatial-temporal characteristics of GIF images, which limits the performance of model recognition to a certain extent. A GIF emotion recognition algorithm based on ResNet-ConvGRU is proposed in this paper. First, GIF data is preprocessed, converting its image sequences to static image format for saving. Then, the spatial features of images and the temporal features of static image sequences are extracted with ResNet and ConvGRU networks, respectively. At last, the animated GIFs data features are synthesized and the seven emotional intensities of GIF data are calculated. The GIFGIF dataset is used to verify the experiment. From the experimental results, the proposed animated GIFs emotion recognition model based on ResNet-ConvGRU, compared with the classical emotion recognition algorithms such as VGGNet-ConvGRU, ResNet3D, CNN-LSTM, and C3D, has a stronger feature extraction ability, and sentiment classification performance. This method provides a finer-grained analysis for the study of public opinion trends and a new idea for affection recognition of GIF data in social media.

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Section: Experimental Analysis and Resultsmentioning

confidence: 99%

Research on Animated GIFs Emotion Recognition Based on ResNet-ConvGRU

Zhang

Qing-dao-er-ji

2022

Mathematical Problems in Engineering

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“…This allows multiple 3D CLs to be stacked, driving the full number of parameters of the network to be correspondingly large. At the same time, the network training speed depends on the distribution of transmitted data in the CLs, but in C3D networks the CLs do not have data normalization processing, so the traditional C3D networks are not as effective for recognition in HPR [21][22]. Figure 2 In Figure 2, the stochastic gradient descent technique optimizes the training of the entire network, and an FCL is used at the network's conclusion.…”

Section: Improvement Of 3d Convolution-based C3d Networkmentioning

confidence: 99%

Improved C3D Network Model Construction and Its Posture Recognition Study in Swimming Sports

Peng,

2024

IJCAI

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“…In order to solve the problems above, the traditional pointer instrument image recognition technology usually needs to spend a lot of time for additional image preprocessing, this method is inefficient and slow, resulting in a serious waste of resources and it cannot meet the real-time requirements of industrial production [ 14 ].…”

Section: Instrument Image Features and Recognition Modelmentioning

confidence: 99%

Instrument Pointer Recognition Scheme Based on Improved CSL Algorithm

Liu

Wang

2022

Sensors

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The traditional pointer instrument recognition scheme is implemented in three steps, which is cumbersome and inefficient. So it is difficult to apply to the industrial production of real-time monitoring. Based on the improvement of the CSL coding method and the setting of the pre-cache mechanism, an intelligent reading recognition technology of the YOLOv5 pointer instrument is proposed in this paper, which realizes the rapid positioning and reading recognition of the pointer instrument. The problem of angle interaction in rotating target detection is eliminated, the complexity of image preprocessing is avoided, and the problems of poor adaptability of Hough detection are solved in this strategy. The experimental results show that compared with the traditional algorithm, the algorithm in this paper can effectively identify the angle of the pointer instrument, has high detection efficiency and strong adaptability, and has broad application prospects.

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Micro-expression recognition based on SqueezeNet and C3D

Cited by 8 publications

References 29 publications

Research on Animated GIFs Emotion Recognition Based on ResNet-ConvGRU

Research on Animated GIFs Emotion Recognition Based on ResNet-ConvGRU

Improved C3D Network Model Construction and Its Posture Recognition Study in Swimming Sports

Instrument Pointer Recognition Scheme Based on Improved CSL Algorithm

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