CN107166645A - A kind of air conditioning control method analyzed based on indoor scene - Google Patents
A kind of air conditioning control method analyzed based on indoor scene Download PDFInfo
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Abstract
The present invention sets image collecting device to gather off-the-air picture on air-conditioning, the comprehensive analysis of the position relationship of human body attitude, human body motion track and human body and furniture is carried out to the off-the-air picture of collection by smart network, to recognize indoor sleep scene, scene of having a meal, party scene, moving scene and leisure scene, according to the temperature and blowing pattern of the different scenes automatic control air conditioner identified.
Description
Technical field
The present invention relates to a kind of air conditioning control method analyzed based on indoor scene.
Background technology
Air-conditioning is a kind of electrical equipment of very common application widely, such as various wall-hanging air conditioners in daily life
And central air-conditioning.At present, the setting of the automatic mode of air-conditioning both at home and abroad on the market is the temperature set according to user, and air-conditioning is certainly
Dynamic selection refrigeration is heated, if room temperature is higher than the temperature air conditioner refrigerating that user sets, if room temperature is less than the temperature that user sets
Spend air-conditioning heating.
The shortcoming of existing air-conditioning automatic mode is the temperature to air-conditioning and can not to be blown according to the real-time activity scene of user
Wind is adjusted.Such as user is different, and empty in the temperature and cold air blast velocity required for sleep scene and scene of having a meal
The temperature and cold air blast velocity of air-conditioning can not automatically be changed according to the change of scene by adjusting.
The content of the invention
It is an object of the invention to provide a kind of air conditioning control method analyzed based on indoor scene, it can be according to different
The temperature and blowing pattern of indoor scene control control air-conditioning.
To achieve the above object, the technical solution adopted by the present invention is：
A kind of air conditioning control method analyzed based on indoor scene, its specific method is as follows：
Step 1, neural network model training
Step 1.1, the neural network model for human bioequivalence are trained
By gathering the picture and video of various human bodies indoors, human region is manually then calibrated using boundary rectangle frame,
The data demarcated are sent into depth convolutional neural networks and learnt, the neural network model for human bioequivalence is obtained；
Step 1.2, the neural network model training recognized for furniture
By gathering the picture and video of various furniture, the classification of furniture is then manually calibrated, the data demarcated are sent into
Depth convolutional neural networks are learnt, and obtain the neural network model recognized for furniture；
Step 1.3, the neural network model training recognized for moving scene
By gathering the video of common action in the various videos moved comprising indoor sport and human body room, then according to interior
Whether scene is that moving scene carries out demarcation classification, and the data demarcated feeding depth recurrent neural network is learnt, obtained
To the neural network model recognized for moving scene；
Step 2, indoor scene detection
Indoor environment image is gathered by air-conditioning camera, multiple detection identification threads is then opened up and indoor scene is examined
Survey, wherein,
First thread is used for human testing and tracking：
The neural network model for human bioequivalence for learning to obtain using step 1.1 is detected to the human body in image, is examined
When measuring human region, human region is numbered and counted, then using human region of the track algorithm to different numberings
It is tracked, the thread results in human body number, position of human body, human body attitude and human body motion track；
The human body attitude is determined according to the length-width ratio of human body boundary rectangle frame, if the length-width ratio of human body boundary rectangle frame
More than 2:1, then human body attitude is prone position；If the length-width ratio of human body boundary rectangle frame is less than 1:2, then human body attitude is stance；Its
Human body attitude is sitting posture in the case of him；
Second thread is recognized for furniture：
Using step 1.2 learning obtain be used for furniture recognize neural network model in image furniture carry out detection with
Identification classification, the thread results in position and its generic of indoor furniture, and furniture classification is furniture and the food and drink man of couching
Tool；
3rd thread is recognized for moving scene：
The neural network model for being used for moving scene identification obtained using step 1.3 learning is examined to the video collected
Classification is surveyed, the thread results in whether indoor scene is moving scene；
4th thread is used for the collection of indoor sound：
Indoor sound is gathered by setting sound pick-up indoors；
Step 3, indoor scene judge
According to the priority to indoor scene successively carry out sleep scene judge, scene of having a meal judge, moving scene judge and
Scene of meetting judges that, when indoor scene is not belonging to foregoing scene, indoor scene belongs to leisure scene；
Scene of sleeping judges
Sleep scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）An at least people is in prone position；（3）Prone position state
Human body do not move；（4）The human body of prone position state is close with the furniture that couches；（5）Indoor sound is less than 40 decibels；
When indoor scene belongs to sleep scene, air-conditioning is set to air-conditioner temperature and blowing pattern under sleep scene, works as interior
When scene is not belonging to sleep scene, scene judgement of having a meal is carried out；
Scene of having a meal judges
Scene of having a meal need to be while meet following condition：（1）An at least people is in sitting posture；（2）The people of sitting posture state does not move；
（3）The human body of sitting posture state is close with food and drink furniture position；
When indoor scene, which belongs to, has a meal scene, air-conditioning is set to have a meal air-conditioner temperature and blowing pattern under scene, works as interior
Scene be not belonging to have a meal scene when, carry out moving scene judgement；
Moving scene judges
Moving scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）At least one human body is kept in motion；（3）
The people's amount of exercise being kept in motion is big；（4）The people being kept in motion is regular motion；（5）The knot that 3rd thread is obtained
Fruit is moving scene for indoor scene；
When indoor scene belongs to moving scene, air-conditioning is set to air-conditioner temperature and blowing pattern under moving scene, works as interior
When scene is not belonging to motion, carries out party scene and judge；
Scene of meetting judges
Party scene need to meet following condition simultaneously：（1）Number is more than 3 people；（2）Owner is all in stance or sitting posture；（3）
There is human motion situation；（4）Human motion is erratic motion；（5）Indoor sound is more than 60 decibels；
When indoor scene belongs to party scene, air-conditioning is set to air-conditioner temperature and blowing pattern under party scene, works as interior
When scene is not belonging to party scene, indoor scene belongs to leisure scene, and air-conditioning is set to the air-conditioner temperature lain fallow under scene and blown
Wind pattern；
The human motion whether judgement is：In the event of any of following three kinds of situations, then it is assumed that human motion：
（1）The focus point position skew of human body rectangle frame exceedes rectangle frame width or high 1/2, is judged as transporting relative to video camera or so
It is dynamic；（2）Human body rectangle frame area change exceedes original 2 times or 1/2, is judged as moving forward and backward relative to video camera；（3）People
It is original 30% that the length-width ratio amplitude of variation of body rectangle frame, which exceedes, is judged as that original place is moved；Otherwise it is assumed that human body is not moved；
The judgement of the human body exercise amount is：When human body is kept in motion down, movement space is less than 10 seconds, then it is assumed that amount of exercise
It is larger；Otherwise it is assumed that amount of exercise is smaller；
The human motion rule is judged as：（1）When human body is relative to video camera side-to-side movement, human body rectangle frame in the unit interval
The trail change of focus point the rule of certain repeatability is presented；（2）When human body is moved forward and backward relative to video camera, the unit interval
Certain repeated rule is presented in the size variation of interior human body rectangle frame；（3）When human body original place is moved, rectangle frame in the unit interval
Length-width ratio change certain repeated rule is presented；Human body motion track is one of above-mentioned three kinds of situations, then to be regular
Motion, is otherwise erratic motion.
The present invention sets image collecting device to gather off-the-air picture on air-conditioning, by smart network to collection
Off-the-air picture carries out the comprehensive analysis of the position relationship of human body attitude, human body motion track and human body and furniture, to recognize room
Interior sleep scene, scene of having a meal, party scene, moving scene and leisure scene, is controlled automatically according to the different scenes identified
The temperature and blowing pattern of air-conditioning processed.
Brief description of the drawings
Fig. 1 is indoor scene decision flow chart of the present invention.
Embodiment
The invention discloses it is a kind of based on indoor scene analyze air conditioning control method, its by using deep learning human body
Recognizer, moving scene algorithm, furniture recognizer are handled image captured by the camera on air-conditioning, are worked as to obtain
The usage scenario of preceding user, according to the temperature of different scene automatic control air conditioners and blowing pattern.
The specific method of the present invention is as follows.
Step 1, neural network model training
Step 1.1, the neural network model for human bioequivalence are trained
By gathering the picture and video of various human bodies indoors, human region is manually then calibrated using boundary rectangle frame,
The data demarcated are sent into depth convolutional neural networks（CNN, Convolution Neural Network）It is middle to be learnt,
Obtain the neural network model for human bioequivalence.
Step 1.2, the neural network model training recognized for furniture
By gathering the picture and video of various furniture, the classification of furniture is then manually calibrated, the data demarcated are sent into
CNN is learnt, and obtains the neural network model recognized for furniture.
Step 1.3, the neural network model training recognized for moving scene
By gathering the video of common action in the various videos moved comprising indoor sport and human body room, then according to interior
Whether scene is that moving scene carries out demarcation classification, and the data demarcated are sent into depth recurrent neural network（RNN,
Recurrent Neural Network）Learnt, obtain the neural network model recognized for moving scene.
Step 2, indoor scene detection
Indoor environment image is gathered by air-conditioning camera, multiple detection identification threads is then opened up and detects following different respectively
Task：
First thread is used for human testing and tracking：
The neural network model for human bioequivalence for learning to obtain using step 1.1 is detected to the human body in image, is examined
Measure human region i.e. human body boundary rectangle frame when, human region is numbered and counted, then using track algorithm to not
Human region with numbering is tracked, and the thread results in human body number, position of human body, human body attitude and human motion
Track.
Wherein, human body attitude is determined according to the length-width ratio of human body boundary rectangle frame, if human body boundary rectangle frame
Length-width ratio is more than 2:1, then human body attitude is prone position；If the length-width ratio of human body boundary rectangle frame is less than 1:2, then human body attitude is station
Appearance；Human body attitude is sitting posture in the case of other.
Human body motion track then connects position and the size variation situation of rectangle frame in vitro for people.
Second thread is recognized for furniture：
Using step 1.2 learning obtain be used for furniture recognize neural network model in image furniture carry out detection with
Identification classification, the thread results in position and its generic of indoor furniture, and furniture classification is furniture and the food and drink man of couching
Tool, couch furniture such as bed, sofa etc., food and drink furniture such as dining table, tea table etc..
3rd thread is recognized for moving scene：
The neural network model for being used for moving scene identification obtained using step 1.3 learning is examined to the video collected
Classification is surveyed, the thread results in whether indoor scene is moving scene.
4th thread is used for the collection of indoor sound：
Indoor sound is gathered by setting sound pick-up indoors.
Step 3, indoor scene judge
With reference to the result of above-mentioned thread, current indoor scene is judged for which scene, it is specific as follows：
As shown in figure 1, judging whether indoor scene is sleep scene, scene of having a meal, moving scene successively according to the priority
With party scene, i.e., the judgement of sleep scene, scene of having a meal judgement are carried out successively, moving scene judges and party scene judges, when
When indoor scene is not belonging to foregoing scene, it is judged as indoor scene and belongs to leisure scene.
Scene of sleeping judges
Sleep scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）An at least people is in prone position；（3）Prone position state
Human body do not move；（4）The furniture that couch such as the human body of prone position state and sofa, bed are close；（5）Indoor sound is less than 40 points
Shellfish.
When indoor scene belongs to sleep scene, air-conditioning is set to air-conditioner temperature and blowing pattern under sleep scene, when
When indoor scene is not belonging to sleep scene, scene judgement of having a meal is carried out.
Scene of having a meal judges
Scene of having a meal need to be while meet following condition：（1）An at least people is in sitting posture；（2）The people of sitting posture state does not move；
（3）The food and drink furniture positions such as the human body of sitting posture state and dining table, tea table are close.
When indoor scene, which belongs to, has a meal scene, air-conditioning is set to have a meal air-conditioner temperature and blowing pattern under scene, when
Indoor scene be not belonging to have a meal scene when, carry out moving scene judgement.
Moving scene judges
Moving scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）At least one human body is kept in motion；（3）
The people's amount of exercise being kept in motion is big；（4）The people being kept in motion is regular motion；（5）The knot that 3rd thread is obtained
Fruit is moving scene for indoor scene.
When indoor scene belongs to moving scene, air-conditioning is set to air-conditioner temperature and blowing pattern under moving scene, when
When indoor scene is not belonging to motion, carries out party scene and judge.
Scene of meetting judges
Party scene need to meet following condition simultaneously：（1）Number is more than 3 people；（2）Owner is all in stance or sitting posture；（3）
There is human motion situation；（4）Human motion is erratic motion；（5）Indoor sound is more than 60 decibels.
When indoor scene belongs to party scene, air-conditioning is set to air-conditioner temperature and blowing pattern under party scene, when
When indoor scene is not belonging to party scene, indoor scene belongs to leisure scene, and air-conditioning is set to the air-conditioner temperature lain fallow under scene
With blowing pattern.
Above-mentioned human motion whether judgement is：In the event of any of following three kinds of situations, then it is assumed that human body is transported
It is dynamic：（1）The focus point position skew of human body rectangle frame exceedes rectangle frame width or high 1/2, is judged as left relative to video camera
Right motion（Hereinafter referred to as side-to-side movement）；（2）Human body rectangle frame area change exceedes original 2 times or 1/2, is judged as relative
Moved forward and backward in video camera（Hereinafter referred to as move forward and backward）；（3）It is original that the length-width ratio amplitude of variation of human body rectangle frame, which exceedes,
30%, it is judged as that original place is moved（Physical training is common in, hereinafter referred to as original place is moved）；Otherwise it is assumed that human body is not moved.
The judgement of above-mentioned human body exercise amount is：When human body is kept in motion down, movement space is less than 10 seconds, then it is assumed that fortune
Momentum is larger；Otherwise it is assumed that amount of exercise is smaller.
Above-mentioned human motion rule is judged as：（1）During side-to-side movement, the rail of the focus point of human body rectangle frame in the unit interval
The rule of certain repeatability is presented in mark change, and such as movement locus is approximately straight line and repeated back and forth；（2）It is single when moving forward and backward
Certain repeated rule is presented in the size variation of human body rectangle frame in the time of position, for example become larger or taper into and
Repeat back and forth；（3）When original place is moved, certain repeated rule is presented in the length-width ratio change of rectangle frame in the unit interval, for example
Become larger or taper into and repeat back and forth；Human body motion track is one of above-mentioned three kinds of situations, then to be regular
Motion, is otherwise erratic motion.
When automatic mode is opened, air-conditioning can go constantly to recognize current scene, then according to the scene that recognizes come
Change the setting of air-conditioner temperature and blowing pattern.When indoor scene be in having a meal, sleep, lie fallow, move, meet in some
During scene, user can change temperature and blowing pattern under the scene, and the temperature after change and blowing pattern will turn into user
In setting of the scene user to temperature and blowing pattern.
The present invention sets image collecting device to gather off-the-air picture on air-conditioning, by smart network to collection
Off-the-air picture carries out the comprehensive analysis of the position relationship of human body attitude, human body motion track and human body and furniture, to recognize room
Interior sleep scene, scene of having a meal, party scene, moving scene and leisure scene, is controlled automatically according to the different scenes identified
The temperature and blowing pattern of air-conditioning processed.
It is described above, only it is present pre-ferred embodiments, is not intended to limit the scope of the present invention, therefore
Any subtle modifications, equivalent variations and modifications that every technical spirit according to the present invention is made to above example, still belong to
In the range of technical solution of the present invention.
Claims (1)
1. a kind of air conditioning control method analyzed based on indoor scene, it is characterised in that：Specific method is as follows：
Step 1, neural network model training
Step 1.1, the neural network model for human bioequivalence are trained
By gathering the picture and video of various human bodies indoors, human region is manually then calibrated using boundary rectangle frame,
The data demarcated are sent into depth convolutional neural networks and learnt, the neural network model for human bioequivalence is obtained；
Step 1.2, the neural network model training recognized for furniture
By gathering the picture and video of various furniture, the classification of furniture is then manually calibrated, the data demarcated are sent into
Depth convolutional neural networks are learnt, and obtain the neural network model recognized for furniture；
Step 1.3, the neural network model training recognized for moving scene
By gathering the video of common action in the various videos moved comprising indoor sport and human body room, then according to interior
Whether scene is that moving scene carries out demarcation classification, and the data demarcated feeding depth recurrent neural network is learnt, obtained
To the neural network model recognized for moving scene；
Step 2, indoor scene detection
Indoor environment image is gathered by air-conditioning camera, multiple detection identification threads is then opened up and indoor scene is examined
Survey, wherein,
First thread is used for human testing and tracking：
The neural network model for human bioequivalence for learning to obtain using step 1.1 is detected to the human body in image, is examined
When measuring human region, human region is numbered and counted, then using human region of the track algorithm to different numberings
It is tracked, the thread results in human body number, position of human body, human body attitude and human body motion track；
The human body attitude is determined according to the length-width ratio of human body boundary rectangle frame, if the length-width ratio of human body boundary rectangle frame
More than 2:1, then human body attitude is prone position；If the length-width ratio of human body boundary rectangle frame is less than 1:2, then human body attitude is stance；Its
Human body attitude is sitting posture in the case of him；
Second thread is recognized for furniture：
Using step 1.2 learning obtain be used for furniture recognize neural network model in image furniture carry out detection with
Identification classification, the thread results in position and its generic of indoor furniture, and furniture classification is furniture and the food and drink man of couching
Tool；
3rd thread is recognized for moving scene：
The neural network model for being used for moving scene identification obtained using step 1.3 learning is examined to the video collected
Classification is surveyed, the thread results in whether indoor scene is moving scene；
4th thread is used for the collection of indoor sound：
Indoor sound is gathered by setting sound pick-up indoors；
Step 3, indoor scene judge
According to the priority to indoor scene successively carry out sleep scene judge, scene of having a meal judge, moving scene judge and
Scene of meetting judges that, when indoor scene is not belonging to foregoing scene, indoor scene belongs to leisure scene；
Scene of sleeping judges
Sleep scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）An at least people is in prone position；（3）Prone position state
Human body do not move；（4）The human body of prone position state is close with the furniture that couches；（5）Indoor sound is less than 40 decibels；
When indoor scene belongs to sleep scene, air-conditioning is set to air-conditioner temperature and blowing pattern under sleep scene, works as interior
When scene is not belonging to sleep scene, scene judgement of having a meal is carried out；
Scene of having a meal judges
Scene of having a meal need to be while meet following condition：（1）An at least people is in sitting posture；（2）The people of sitting posture state does not move；
（3）The human body of sitting posture state is close with food and drink furniture position；
When indoor scene, which belongs to, has a meal scene, air-conditioning is set to have a meal air-conditioner temperature and blowing pattern under scene, works as interior
Scene be not belonging to have a meal scene when, carry out moving scene judgement；
Moving scene judges
Moving scene need to meet following condition simultaneously：（1）Number is less than 5 people；（2）At least one human body is kept in motion；（3）
The people's amount of exercise being kept in motion is big；（4）The people being kept in motion is regular motion；（5）The knot that 3rd thread is obtained
Fruit is moving scene for indoor scene；
When indoor scene belongs to moving scene, air-conditioning is set to air-conditioner temperature and blowing pattern under moving scene, works as interior
When scene is not belonging to motion, carries out party scene and judge；
Scene of meetting judges
Party scene need to meet following condition simultaneously：（1）Number is more than 3 people；（2）Owner is all in stance or sitting posture；（3）
There is human motion situation；（4）Human motion is erratic motion；（5）Indoor sound is more than 60 decibels；
When indoor scene belongs to party scene, air-conditioning is set to air-conditioner temperature and blowing pattern under party scene, works as interior
When scene is not belonging to party scene, indoor scene belongs to leisure scene, and air-conditioning is set to the air-conditioner temperature lain fallow under scene and blown
Wind pattern；
The human motion whether judgement is：In the event of any of following three kinds of situations, then it is assumed that human motion：
（1）The focus point position skew of human body rectangle frame exceedes rectangle frame width or high 1/2, is judged as transporting relative to video camera or so
It is dynamic；（2）Human body rectangle frame area change exceedes original 2 times or 1/2, is judged as moving forward and backward relative to video camera；（3）People
It is original 30% that the length-width ratio amplitude of variation of body rectangle frame, which exceedes, is judged as that original place is moved；Otherwise it is assumed that human body is not moved；
The judgement of the human body exercise amount is：When human body is kept in motion down, movement space is less than 10 seconds, then it is assumed that amount of exercise
It is larger；Otherwise it is assumed that amount of exercise is smaller；
The human motion rule is judged as：（1）When human body is relative to video camera side-to-side movement, human body rectangle frame in the unit interval
The trail change of focus point the rule of certain repeatability is presented；（2）When human body is moved forward and backward relative to video camera, the unit interval
Certain repeated rule is presented in the size variation of interior human body rectangle frame；（3）When human body original place is moved, rectangle frame in the unit interval
Length-width ratio change certain repeated rule is presented；Human body motion track is one of above-mentioned three kinds of situations, then to be regular
Motion, is otherwise erratic motion.
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| CN113063217A (en) * | 2021-02-26 | 2021-07-02 | 广东申菱环境系统股份有限公司 | Air conditioner load adjusting method and system |
| CN113268004A (en) * | 2021-04-22 | 2021-08-17 | 深圳Tcl新技术有限公司 | Scene creating method and device, computer equipment and storage medium |
| CN113865015A (en) * | 2021-09-22 | 2021-12-31 | 武汉奇人制冷技术有限公司 | AI intelligent control method and system for large-scale central air conditioner |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013098613A (en) * | 2011-10-28 | 2013-05-20 | Sharp Corp | Apparatus controller, apparatus control method and program |
| CN103277869A (en) * | 2013-04-22 | 2013-09-04 | 清华大学 | Intelligent air-conditioner adjustment method and device based on indoor scene video streaming cognition |
| CN104713187A (en) * | 2013-12-11 | 2015-06-17 | 海尔集团公司 | Air conditioner control method according to picture foil scene and air conditioner |
| CN105258305A (en) * | 2014-07-15 | 2016-01-20 | 广东美的暖通设备有限公司 | Air conditioner, air conditioner system and control method for air conditioner |
| CN105276760A (en) * | 2014-07-11 | 2016-01-27 | 欧姆龙株式会社 | Room information inferring apparatus, room information inferring method, and air conditioning apparatus |
| CN106152408A (en) * | 2016-07-06 | 2016-11-23 | 北京地平线机器人技术研发有限公司 | Intelligent air conditioner controller, control method and air-conditioner |
| CN205880712U (en) * | 2016-06-21 | 2017-01-11 | 杭州鸿雁电器有限公司 | System for change indoor scene |
-
2017
- 2017-05-18 CN CN201710352253.9A patent/CN107166645B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013098613A (en) * | 2011-10-28 | 2013-05-20 | Sharp Corp | Apparatus controller, apparatus control method and program |
| CN103277869A (en) * | 2013-04-22 | 2013-09-04 | 清华大学 | Intelligent air-conditioner adjustment method and device based on indoor scene video streaming cognition |
| CN104713187A (en) * | 2013-12-11 | 2015-06-17 | 海尔集团公司 | Air conditioner control method according to picture foil scene and air conditioner |
| CN105276760A (en) * | 2014-07-11 | 2016-01-27 | 欧姆龙株式会社 | Room information inferring apparatus, room information inferring method, and air conditioning apparatus |
| CN105258305A (en) * | 2014-07-15 | 2016-01-20 | 广东美的暖通设备有限公司 | Air conditioner, air conditioner system and control method for air conditioner |
| CN205880712U (en) * | 2016-06-21 | 2017-01-11 | 杭州鸿雁电器有限公司 | System for change indoor scene |
| CN106152408A (en) * | 2016-07-06 | 2016-11-23 | 北京地平线机器人技术研发有限公司 | Intelligent air conditioner controller, control method and air-conditioner |
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| CN108224691A (en) * | 2017-12-22 | 2018-06-29 | 银河水滴科技（北京）有限公司 | A kind of air conditioner system control method and device |
| CN108279573B (en) * | 2018-02-05 | 2019-05-28 | 北京儒博科技有限公司 | Control method, device, intelligent appliance and medium based on human body detection of attribute |
| CN108279573A (en) * | 2018-02-05 | 2018-07-13 | 北京智能管家科技有限公司 | Control method, device, intelligent appliance based on human body detection of attribute and medium |
| US11346573B2 (en) | 2018-02-26 | 2022-05-31 | Midea Group Co., Ltd. | Method and system for providing air conditioning |
| CN111954784A (en) * | 2018-02-26 | 2020-11-17 | 美的集团股份有限公司 | Method and system for air conditioning |
| CN108443965A (en) * | 2018-03-29 | 2018-08-24 | 广东美的制冷设备有限公司 | Dormant detection method, device, air conditioner and readable storage medium storing program for executing |
| CN108852362A (en) * | 2018-03-29 | 2018-11-23 | 广东美的制冷设备有限公司 | Dormant detection method, device, air conditioner and readable storage medium storing program for executing |
| CN108537172A (en) * | 2018-04-09 | 2018-09-14 | 北京邦天信息技术有限公司 | A kind of method and apparatus of the behavior based on Machine Vision Recognition people |
| CN111684460B (en) * | 2018-04-27 | 2023-09-22 | 上海趋视信息科技有限公司 | System and method for detecting pose of human object |
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