CN107526440A - The intelligent electric appliance control method and system of gesture identification based on decision tree classification - Google Patents
The intelligent electric appliance control method and system of gesture identification based on decision tree classification Download PDFInfo
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- CN107526440A CN107526440A CN201710751092.0A CN201710751092A CN107526440A CN 107526440 A CN107526440 A CN 107526440A CN 201710751092 A CN201710751092 A CN 201710751092A CN 107526440 A CN107526440 A CN 107526440A
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- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
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Abstract
The invention discloses a kind of intelligent electric appliance control system of the gesture identification based on decision tree classification, mainly including image capturing system, gesture recognition system, control process system, display screen and voice broadcasting system, it is characterised in that：Image capturing system is converted into predefined agreement data and is sent to gesture recognition system by being acquired to user in the gesture motion that operable area is carried out；Gesture recognition system is judged incoming data by categorised decision tree；Control process system is operated accordingly to judged result, and result is fed back into user by display screen and voice broadcasting system.Present invention also offers the intelligent electric appliance control method of the gesture identification based on decision tree classification.The invention provides a kind of intelligent electric appliance control method of the gesture identification based on decision tree classification, and the data analysing method of categorised decision tree is employed on the basis of existing gesture identification, more efficiently, clearly carries out gesture identification.
Description
Technical field
The present invention relates to a kind of electrical apparatus control system of gesture identification, and in particular to a kind of gesture based on decision tree classification
The intelligent electric appliance control method and system of identification, belong to smart machine control field.
Background technology
With the popularization of smart machine, household electrical appliance realize intellectuality substantially, more convenient and quicker for people's
Service for life.But for blind person and deaf-mute, they can not realize to the Voice commands of the equipment such as intelligent air condition or
Inconvenience is controlled using touch apparatus, and the specific equipment of the needs that existing gesture recognition system has could realize have
Accuracy rate is not high, so a kind of this method of gesture identification is proposed, to lift their bodies for the control of the equipment such as intelligent air condition
Test, while the recreational of normal users can also be lifted.
Categorised decision tree, decision tree (Decision Tree) are also known as decision tree, are a kind of tree knots for applying to classification
Structure.Each internal node (internal node) therein represents the once test to some attribute, and each edge represents a survey
Test result, leaf node (leaf) represents the distribution (class distribution) of some class (class) or class, uppermost
Node is root node.Decision tree is divided into two kinds of classification tree and regression tree, and classification tree does decision tree to discrete variable, and regression tree is to even
Continuous variable does decision tree.Decision Tree algorithms have a benefit, that is, it can produce the rule that people can directly understand, this is shellfish
Ye Si, neutral net scheduling algorithm without characteristic；The accuracy rate of decision tree is also higher, and be not required to it is to be understood that background knowledge just
It can be classified, be a very effective algorithm.Decision Tree algorithms have many mutation, including ID3, C4.5, C5.0, CART
Deng, but its basis is all similar.
The content of the invention
It is an object of the invention to provide a kind of speed is fast, the intelligence of the high gesture identification based on decision tree classification of accuracy
Can electric control method and system.
What the present invention was realized in：
A kind of intelligent electric appliance control system of the gesture identification based on decision tree classification, mainly including image capturing system,
Gesture recognition system, control process system, display screen and voice broadcasting system, image capturing system by user operable
The gesture motion that region is carried out is acquired, and is converted into predefined agreement data and is sent to gesture recognition system；Hand
Gesture identifying system is judged incoming data by categorised decision tree；Control process system carries out corresponding to judged result
Operation, and result is fed back to by user by display screen and voice broadcasting system.
Further scheme is：
The gesture recognition system gathers people's habituation operating gesture generation training set first with big data, recycles instruction
Practice collection generation categorised decision tree, then decision tree is verified, finds out classic decision tree and is used for actual production.
Further scheme is：
Described image acquisition system includes obtaining the picture pick-up device of gesture information.
Further scheme is：
The decision-tree model generates by the following method：
Step 11, make thorough investigation and study, the gesture motion of people is collected, obtain largely being used for implementing control, people
Habitually gesture data；
Step 12, the data obtained in step 11 are counted, and manual sort are carried out to data, define threshold value,
And a small number of rule progress dirty data cleaning treatments is obeyed according to most, obtain relatively most representational training set and test number
According to collection；
Step 13, grader is trained using the training set obtained in step 12, and gained is trained with test data set pair
Grader is tested, and obtains a categorised decision tree；
Step 14, carry out beta pruning with reference to the categorised decision tree that actual conditions obtain to step 13 and optimize, be suitable for
The decision-tree model of gesture identification.
It is another object of the present invention to also provide a kind of intelligent electric appliance control of the gesture identification based on decision tree classification
Method processed, control method of the invention are the intelligent electric appliance controls based on the gesture identification provided by the invention based on decision tree classification
System processed, and specifically comprise the following steps：
Step 21, the operation information by image capturing system acquisition user, and be translated into predefined corresponding
Operation data；
The data obtained in step 22, processing step 21, data consistency is checked, handle invalid value and missing values；
Step 23, data conversion is carried out to the valid data arrived in step 22, obtained one by one with individually operated
The data of property；
Step 24, it will be classified in the decision-tree model in the data input after generalization to gesture recognition system；
Step 25, the operation according to corresponding to the classification results of step 24 are carried out to equipment, and display screen and voice broadcast system
Unite and fed back to user.
The invention provides a kind of intelligent electric appliance control method of the gesture identification based on decision tree classification, in existing hand
The data analysing method of categorised decision tree is employed on the basis of gesture identification, more efficiently, clearly carries out gesture identification.So as to one
Determine to improve recognition accuracy and Consumer's Experience in degree.The present invention uses the categorised decision tree algorithm in data mining technology
As core, decision tree has the characteristics of speed is fast, accuracy is high, so as to improve the efficiency of gesture identification and the degree of accuracy.
Brief description of the drawings
Fig. 1 is to obtain the flow chart being identified after data by categorised decision tree；
Fig. 2 is the categorised decision tree schematic diagram for gesture identification；
Fig. 3 is present invention specific implementation flow chart.
Embodiment
The present invention is further illustrated with specific embodiment below in conjunction with the accompanying drawings.
As shown in Figure 1, a kind of intelligent electric appliance control system of the gesture identification based on decision tree classification, it is main to include figure
As acquisition system, gesture recognition system, control process system, display screen and voice broadcasting system, it is right that image capturing system passes through
User is acquired in the gesture motion that operable area is carried out, and is converted into predefined agreement data and is sent to gesture
Identifying system；Gesture recognition system is judged incoming data by categorised decision tree；Control process system is to judging to tie
Fruit is operated accordingly, and result is fed back into user by display screen and voice broadcasting system.
Wherein, image capturing system includes the major-minor picture pick-up device and auxiliary equipment for obtaining gesture information；Control process
System and display broadcasting system are used to feed back recognition result.
The gesture recognition system gathers people's habituation operating gesture generation training set first with big data, recycles instruction
Practice collection generation categorised decision tree, then decision tree is verified, finds out classic decision tree and is used for actual production.
The gesture recognition system of the present invention uses categorised decision tree as core, as shown in Fig. 2 being exactly one is used for gesture knowledge
Other categorised decision tree-model.We need to gather the substantial amounts of hand for being habitually used to identify smart machine associative operation in advance
The data generation training set of gesture, is then established and a decision tree of refining using training set, establishes decision-tree model (this process
Actually one obtains knowledge from data, carries out the process of machine learning).Then finished in system work using generation
Decision tree to by image capture device obtain property value of the gesture data from root node successively test record, until reaching certain
Individual leaf node, so as to find the class where the record, and make corresponding processing.
The intelligent electric appliance control method of the gesture identification based on decision tree classification of the present invention, specific implementation are divided into two
Point, as shown in Figure 3, Part I is the generation of categorised decision tree-model：
Step S0401, make thorough investigation and study, the gesture motion of people be collected, obtain it is substantial amounts of be used for implementing control,
People's habitually gesture data；
Step S0402, the data obtained in S0401 are counted, and manual sort is carried out to data, define threshold
Value, and dirty data cleaning treatment is carried out according to most rules for obeying minority, obtain relatively most representational training set and survey
Try data set；
Step S0403, grader is trained using the training set obtained in S0402, and gained is trained with test data set pair
Grader tested, obtain a categorised decision tree；
Step S0404, beta pruning and optimization are carried out with reference to the categorised decision tree that actual conditions obtain to S0403, is adapted to
In the decision-tree model of gesture identification.
Part II is the application in real work：
Step S01, the operation information of user is obtained by image capturing system, and is translated into predefined corresponding
Operation data；
Step S02, the data obtained in S01 are handled, check data consistency, handle invalid value and missing values；
Step S03, data conversion is carried out to the valid data arrived in S02, obtains that there is individually operated property one by one
Data；
Step S04, the data input after generalization is classified into decision-tree model；
Step S05, operation corresponding to being carried out according to S04 classification results to equipment, and fed back to user.
Although reference be made herein to invention has been described for explanatory embodiment of the invention, and above-described embodiment is only this hair
Bright preferable embodiment, embodiments of the present invention are simultaneously not restricted to the described embodiments, it should be appreciated that people in the art
Member can be designed that a lot of other modifications and embodiment, and these modifications and embodiment will fall in principle disclosed in the present application
Within scope and spirit.
Claims (5)
- A kind of 1. intelligent electric appliance control system of the gesture identification based on decision tree classification, mainly including image capturing system, hand Gesture identifying system, control process system, display screen and voice broadcasting system, it is characterised in that：Image capturing system by Family is acquired in the gesture motion that operable area is carried out, and is converted into predefined agreement data and is sent to gesture knowledge Other system；Gesture recognition system is judged incoming data by categorised decision tree；Control process system is to judged result Operated accordingly, and result is fed back to by user by display screen and voice broadcasting system.
- 2. the intelligent electric appliance control system of the gesture identification based on decision tree classification according to claim 1, it is characterised in that：The gesture recognition system gathers people's habituation operating gesture generation training set first with big data, recycles training set Categorised decision tree is generated, then decision tree is verified, finds out classic decision tree and is used for actual production.
- 3. the intelligent electric appliance control system of the gesture identification based on decision tree classification according to claim 1, it is characterised in that：Described image acquisition system includes obtaining the picture pick-up device of gesture information.
- 4. according to the intelligent electric appliance control system of the gesture identification based on decision tree classification described in claim 1 or 2 or 3, it is special Sign is：The decision-tree model generates by the following method：Step 11, make thorough investigation and study, the gesture motion of people is collected, obtain largely being used for implementing control, people's habit The gesture data of inertia；Step 12, the data obtained in step 11 are counted, and manual sort is carried out to data, define threshold value, and root A small number of rule progress dirty data cleaning treatments is obeyed according to most, obtains relatively most representational training set and test data Collection；Step 13, grader is trained using the training set obtained in step 12, and the classification of gained is trained with test data set pair Device is tested, and obtains a categorised decision tree；Step 14, carry out beta pruning with reference to the categorised decision tree that actual conditions obtain to step 13 and optimize, obtain being suitable for gesture The decision-tree model of identification.
- 5. the intelligent electric appliance control method of the gesture identification based on decision tree classification, it is characterised in that：Employ claim 1 to The intelligent electric appliance control system of the gesture identification based on decision tree classification described in 4 any claims, and specifically include as follows Step：Step 21, the operation information by image capturing system acquisition user, and it is translated into predefined corresponding operation Data；The data obtained in step 22, processing step 21, data consistency is checked, handle invalid value and missing values；Step 23, data conversion is carried out to the valid data arrived in step 22, obtain that there is individually operated property one by one Data；Step 24, it will be classified in the decision-tree model in the data input after generalization to gesture recognition system；Step 25, according to the classification results of step 24 equipment is carried out corresponding to operate, and display screen and voice broadcasting system to User is fed back.
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| CN109376795A (en) * | 2018-11-19 | 2019-02-22 | 四川长虹电器股份有限公司 | Air conditioner intelligent temperature control method based on Decision Tree Algorithm |
| CN109886070A (en) * | 2018-12-24 | 2019-06-14 | 珠海格力电器股份有限公司 | Equipment control method and device, storage medium and equipment |
| CN110275614A (en) * | 2019-05-30 | 2019-09-24 | 福建工程学院 | A kind of non-contact gesture identification device and its method |
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Application publication date: 20171229 |