CN110569741A - Expression recognition system based on artificial intelligence - Google Patents
Expression recognition system based on artificial intelligence Download PDFInfo
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- CN110569741A CN110569741A CN201910762029.6A CN201910762029A CN110569741A CN 110569741 A CN110569741 A CN 110569741A CN 201910762029 A CN201910762029 A CN 201910762029A CN 110569741 A CN110569741 A CN 110569741A
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- 230000014509 gene expression Effects 0.000 title claims abstract description 62
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 14
- 230000008921 facial expression Effects 0.000 claims abstract description 39
- 230000008451 emotion Effects 0.000 claims abstract description 16
- 238000013528 artificial neural network Methods 0.000 claims abstract description 15
- 238000001514 detection method Methods 0.000 claims abstract description 6
- 238000000605 extraction Methods 0.000 claims abstract description 6
- 238000013527 convolutional neural network Methods 0.000 claims abstract description 4
- 230000001815 facial effect Effects 0.000 claims description 9
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
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Abstract
The invention discloses an expression recognition system based on artificial intelligence, which comprises: the expression database comprises a data information base consisting of various representative expressions; the face detection positioning module is based on a face detector of a convolutional neural network, analyzes whether each feature of a face exists through the neural network of the face detector, and then further judges whether the face is a face or not; the facial expression feature extraction module comprises a multilayer heterogeneous neural network; the facial expression emotion classification module adopts a multilayer heterogeneous neural network; the expression model matching module is used for matching the facial expression with the model; and the facial expression model establishing module is used for establishing a facial expression model. The invention can accurately give the emotion result of the tested person under stimulation in real time, and give timely and effective reference information to the investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, thereby improving the investigation quality.
Description
Technical Field
The invention relates to the field of computer vision analysis, in particular to an expression recognition system based on artificial intelligence.
background
The human facial expression is an effective expression mode for human information communication, and is used as a key technology in an emotion calculation system to enable the human facial expression to become a basis of human-computer interaction, so that the research on the human facial expression not only conforms to the development of artificial intelligence, but also conforms to the trend of era development, is beneficial to promoting the development of science and technology, and is bound to become a trend of the science and technology industry in the near future.
The facial expression of the human face has wide application, especially, in various large factories and enterprises, the safety protection problem in the working process is more and more emphasized, for example, accidents such as mines, building sites, heavy industrial areas and the like are frequent, the safety protection problem is serious, and the facial expression of the human face can provide much information for the safety protection problem. For example, in the aspect of medical monitoring, an expression monitoring system is developed, psychological changes and physiological states of a patient at the moment are analyzed by monitoring changes of the expression of the patient in real time, and if the patient is found to have pain or bad emotion, medical staff can be informed to carry out treatment in time; in the production process of a coal mine, the low emotion of underground miners, fatigue or distraction in the working process can influence the working efficiency of the underground miners, even cause accidents, and if the face expression recognition can be realized through a computer, the emotion state of the underground miners can be better mastered, so that problems can be found in time, and accident potential can be eliminated; in the driving process, the fatigue driving condition can often appear, and if the expression state of the driver can be observed in real time at the moment, the driver can be reminded in time when the fatigue expression appears on the face of the driver, so that the driver can be prevented from getting in the bud, and the traffic accident can be prevented.
Disclosure of Invention
In order to overcome the problems, the invention provides an expression recognition system based on artificial intelligence.
the technical scheme of the invention is to provide an expression recognition system based on artificial intelligence, which is characterized by comprising the following components:
the expression database comprises a data information base consisting of various representative expressions;
the face detection positioning module is based on a face detector of a convolutional neural network, analyzes whether each feature of a face exists through the neural network of the face detector, and then further judges whether the face is a face or not;
The facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the facial micro expression features are extracted by adopting the heterogeneous neural network, so that the system can learn essential features representing the micro expressions from sample data autonomously;
The facial expression emotion classification module adopts a multilayer heterogeneous neural network, each neuron of an input layer correspondingly extracts expression distribution data from an input facial image, and each neuron of an output layer correspondingly extracts seven basic expression categories;
the expression model matching module is used for matching the facial expression with the model;
And the facial expression model establishing module is used for establishing a facial expression model, and after the model is established, the real-time video stream or the local picture is accessed into the model for analysis and identification.
Furthermore, the facial expression and emotion classification module comprises a general expression classification unit and a compound expression classification unit.
further, the face detector detects five facial features of hair, eyes, nose, mouth, and beard.
Furthermore, the expression model matching module comprises a general matching unit and a composite matching unit.
The invention has the beneficial effects that: the invention relates to an artificial intelligence-based expression recognition system which comprises an expression database, a face detection and positioning module, a face expression feature extraction module, a face facial expression and emotion classification module, an expression model matching module and a facial expression model establishing module, wherein the face expression database is used for storing facial expression features; the emotion result of the tested person under the stimulation can be accurately given in real time, timely and effective reference information can be given to an investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, so that the investigation quality is improved.
Detailed Description
in order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
The invention relates to an expression recognition system based on artificial intelligence, which comprises:
The expression database comprises a data information base consisting of various representative expressions; it is the basis of human expression recognition characteristics and the research and development of an automatic expression recognition computer system. The quality of the expression database directly influences the research result and the correct recognition of the expression by the computer.
the face detection positioning module is based on a face detector of a convolutional neural network, analyzes whether each feature of a face exists through the neural network of the face detector, and then further judges whether the face is a face or not; on one hand, the whole and local information is simultaneously utilized, and the face content can be depicted from different angles, so that the face and the non-face can be better distinguished; on the other hand, the robustness of the occlusion is enhanced, and the local occlusion of the face can influence the overall expressed characteristics.
The facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the facial micro expression features are extracted by adopting the heterogeneous neural network, so that the system can learn essential features representing the micro expressions from sample data autonomously.
the facial expression emotion classification module adopts a multilayer heterogeneous neural network, each neuron of an input layer correspondingly extracts expression distribution data from an input facial image, and each neuron of an output layer correspondingly extracts seven basic expression categories.
And the expression model matching module is used for matching the facial expression with the model.
And the facial expression model establishing module is used for establishing a facial expression model, and after the model is established, the real-time video stream or the local picture is accessed into the model for analysis and identification.
In a preferred embodiment of the present invention, the facial expression and emotion classification module includes a general expression classification unit and a compound expression classification unit.
In a preferred embodiment of the present invention, the face detector detects five facial features of hair, eyes, nose, mouth, and beard.
in a preferred embodiment of the present invention, the expression model matching module includes a general matching unit and a composite matching unit.
The invention relates to an artificial intelligence-based expression recognition system which comprises an expression database, a face detection and positioning module, a face expression feature extraction module, a face facial expression and emotion classification module, an expression model matching module and a facial expression model establishing module, wherein the face expression database is used for storing facial expression features; the emotion result of the tested person under the stimulation can be accurately given in real time, timely and effective reference information can be given to an investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, so that the investigation quality is improved.
The above embodiment is only one embodiment of the present invention, and the description thereof is specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (4)
1. an expression recognition system based on artificial intelligence, comprising:
The expression database comprises a data information base consisting of various representative expressions;
The face detection positioning module is based on a face detector of a convolutional neural network, analyzes whether each feature of a face exists through the neural network of the face detector, and then further judges whether the face is a face or not;
The facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the facial micro expression features are extracted by adopting the heterogeneous neural network, so that the system can learn essential features representing the micro expressions from sample data autonomously;
The facial expression emotion classification module adopts a multilayer heterogeneous neural network, each neuron of an input layer correspondingly extracts expression distribution data from an input facial image, and each neuron of an output layer correspondingly extracts seven basic expression categories;
The expression model matching module is used for matching the facial expression with the model;
and the facial expression model establishing module is used for establishing a facial expression model, and after the model is established, the real-time video stream or the local picture is accessed into the model for analysis and identification.
2. The artificial intelligence based expression recognition system of claim 1, wherein: the facial expression and emotion classification module comprises a general expression classification unit and a compound expression classification unit.
3. The artificial intelligence based expression recognition system of claim 1, wherein: the face detector detects five facial features of hair, eyes, nose, mouth, and beard.
4. the artificial intelligence based expression recognition system of claim 1, wherein: the expression model matching module comprises a general matching unit and a composite matching unit.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103488974A (en) * | 2013-09-13 | 2014-01-01 | 南京华图信息技术有限公司 | Facial expression recognition method and system based on simulated biological vision neural network |
| CN106529494A (en) * | 2016-11-24 | 2017-03-22 | 深圳市永达电子信息股份有限公司 | Human face recognition method based on multi-camera model |
| CN107392151A (en) * | 2017-07-21 | 2017-11-24 | 竹间智能科技（上海）有限公司 | Face image various dimensions emotion judgement system and method based on neutral net |
| CN107423707A (en) * | 2017-07-25 | 2017-12-01 | 深圳帕罗人工智能科技有限公司 | A kind of face Emotion identification method based under complex environment |
| TW201839635A (en) * | 2017-04-25 | 2018-11-01 | 元智大學 | Emotion detection system and method |
| CN109820522A (en) * | 2019-01-22 | 2019-05-31 | 苏州乐轩科技有限公司 | Mood arrangement for detecting, system and method |
| CN109919006A (en) * | 2019-01-23 | 2019-06-21 | 深圳壹账通智能科技有限公司 | Expression detection method, device, electronic equipment and storage medium |
-
2019
- 2019-08-19 CN CN201910762029.6A patent/CN110569741A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103488974A (en) * | 2013-09-13 | 2014-01-01 | 南京华图信息技术有限公司 | Facial expression recognition method and system based on simulated biological vision neural network |
| CN106529494A (en) * | 2016-11-24 | 2017-03-22 | 深圳市永达电子信息股份有限公司 | Human face recognition method based on multi-camera model |
| TW201839635A (en) * | 2017-04-25 | 2018-11-01 | 元智大學 | Emotion detection system and method |
| CN107392151A (en) * | 2017-07-21 | 2017-11-24 | 竹间智能科技（上海）有限公司 | Face image various dimensions emotion judgement system and method based on neutral net |
| CN107423707A (en) * | 2017-07-25 | 2017-12-01 | 深圳帕罗人工智能科技有限公司 | A kind of face Emotion identification method based under complex environment |
| CN109820522A (en) * | 2019-01-22 | 2019-05-31 | 苏州乐轩科技有限公司 | Mood arrangement for detecting, system and method |
| CN109919006A (en) * | 2019-01-23 | 2019-06-21 | 深圳壹账通智能科技有限公司 | Expression detection method, device, electronic equipment and storage medium |
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