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Cognitive emotion recognition method based on geodesic distance and sample entropy

A geodesic distance and emotion recognition technology, applied in character and pattern recognition, acquisition/recognition of facial features, instruments, etc., can solve the problems of increasing data dimensions, low cognitive and emotional calculation and recognition accuracy, and increasing difficulty in feature extraction.

Pending Publication Date: 2021-01-29
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, different from static images, video-based data processing increases time-dimensional information and greatly increases the amount of data, sometimes even reaching millions of dimensional data. The difficulty of data processing also increases, increasing cognitive Difficulty in extracting emotional features leads to low accuracy in cognitive emotional computing and recognition
[0004] To sum up, for the continuous process of cognitive emotion computing and recognition, facial emotion feature extraction based on video data can better reflect the process of emotional expression than traditional feature extraction based on static images, but this increases the data Dimensions, resulting in a surge in the difficulty of feature extraction

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  • Cognitive emotion recognition method based on geodesic distance and sample entropy
  • Cognitive emotion recognition method based on geodesic distance and sample entropy
  • Cognitive emotion recognition method based on geodesic distance and sample entropy

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Embodiment Construction

[0091] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0092] Aiming at the need of controlling and reducing human errors in industrial engineering, and aiming at solving the problem of lack of objective and accurate technical means to measure people's cognitive emotion, the present invention proposes a cognitive emotion recognition based on geodesic distance and sample entropy method.

[0093] The technical problem to be solved by the present invention is: the human-computer interaction is close in the industrial system, and the human-machine environment is complicated in the transportation process, so accidents caused by human factors frequently occur. The identification of emotional states is the key to judging the cognitive state of people in the task circuit. However, the current affective computing theory and methods lack the correlation with the cognitive state, and it is difficult to achie...

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Abstract

The invention discloses a cognitive emotion recognition method based on geodesic distance and sample entropy, and relates to the technical field of face recognition and emotion calculation. Accordingto the method, 49 efficient facial emotion description points are proposed for four cognitive emotions influencing a person in a task loop, and facial emotion description point positioning based on anactive appearance model is achieved; secondly, a geodesic distance-based human face emotion spatial-temporal feature expression method is designed; secondly, a face emotion feature extraction methodbased on sample entropy is provided, and efficient extraction of cognitive emotion space-time features is achieved; and finally, sentiment classification and recognition are achieved by utilizing a random forest classifier. According to the method, the face cognitive emotion based on the video stream can be rapidly extracted, the cognitive emotion state of the person in the task loop can be accurately and efficiently recognized, and technical support is provided for monitoring the working state of the person and controlling the task risk.

Description

technical field [0001] The invention relates to the fields of emotion computing and face recognition, in particular to a cognitive emotion recognition method based on geodesic distance and sample entropy. Background technique [0002] Affective computing is a theory of expressing and recognizing human emotions by mining big data, and it is also a key technology for realizing advanced artificial intelligence. Psychological research shows that cognition and emotion are two important parts of human mental activities, and they are two aspects of a process organically linked. Researching the cognitive emotion of people in tasks plays an important role in discovering task risks in time and taking necessary measures. However, the current research on emotion computing and recognition mainly focuses on the analysis of the six basic emotions in daily life, ignoring the research on human cognitive emotion during the task process. [0003] Studies have shown that emotional expression ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/168G06V40/174G06V40/172G06V20/41G06F18/2135G06F18/24323G06F18/214
Inventor 陈嘉宇葛红娟
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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