CN109189276A - Desktop projection holographic technique - Google Patents
Desktop projection holographic technique Download PDFInfo
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- CN109189276A CN109189276A CN201811002476.3A CN201811002476A CN109189276A CN 109189276 A CN109189276 A CN 109189276A CN 201811002476 A CN201811002476 A CN 201811002476A CN 109189276 A CN109189276 A CN 109189276A
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- Prior art keywords
- infrared
- desktop
- speed
- algorithm
- projection
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
- G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
- G06F3/042—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by opto-electronic means
- G06F3/0421—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by opto-electronic means by interrupting or reflecting a light beam, e.g. optical touch-screen
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/90—Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/30—Transforming light or analogous information into electric information
- H04N5/33—Transforming infrared radiation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/12—Picture reproducers
- H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
- H04N9/3141—Constructional details thereof
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72409—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories
Abstract
The present invention relates to desktop projection holographic techniques, handset emissions signal is imaged through projector, the illumination of laser emitter outgoing is mapped on the finger operated to projection screen, finger blocks portion of incident light, it is formed by optical signal and enters infrared camera, therefore infrared camera can obtain scene image according to the position and a variety of different gestures of identification that light signal collection touches.Mobile phone is analyzed and processed touch signal collected, is reacted on the screen of projection, and the operation to projection screen is realized according to touch signal instruction.The beneficial effects of the present invention are: establishing the personalized portrait movement manipulation model for being suitble to everyone to use, and pass through study, constantly improve suitable personal height in the knowledge base of cloud, gender, figure manipulation model, it is prefabricated for the correspondence portrait crowd that uses for the first time, and using personal characteristics supervised learning training result as the input foundation of the correspondence portrait crowd constantly refined.
Description
Technical field
The present invention relates to desktop projection holographic techniques.
Background technique
Sand table drills, Chang Youyong drawing, model two kind forms very common in occasions such as military affairs, business, meeting, study,
If but the form flexibility of drawing and model is not strong using entire desktop as touch screen, it is desirable that the hardware such as dedicated desktop are set
It is standby, it can not be in conventional tables using if only existing throwing is put in the projection interactive white board recumbency of metope, in the feelings more than people
Under condition, it is easy to block mutually, forms the blind area in some regions.
Summary of the invention
To overcome the defects of present in the prior art, the present invention provides desktop projection holographic technique, is able to solve above-mentioned skill
Art problem.
The present invention through the following technical solutions to achieve the above objectives:
Desktop projection holographic technique successively carries out as steps described below:
Step 1: four infrared cameras and projector are placed in four corners of desktop, with projector by receiving mobile phone letter
It number is imaged on the table, and the communication module on infrared camera is connect with cloud host machine；
Step 2: the LED infrared ray transmitting lamp group on the vertical both sides on infrared touch frame emits orderly infrared ray,
It is woven into the intensive infrared net of one side in infrared touch frame, forms an infrared touch area, camera first carries out people
Face identification starting, projector are that video acquisition input is set as output equipment, two common cameras (installing infrared fileter additional)
It is standby, touch area is illuminated by infrared LED, the image coordinate of finger fingertip is extracted by visual detection algorithm, and then is passed through
Two images and binocular distance measurement principle calculate the three-dimensional coordinate of finger tip, and judge whether it has touched touch desktop,
Touch control operation just blocks the infrared ray on vertical and horizontal direction when referring to the certain point for touching screen, laser emitter outgoing
Illumination is mapped on the finger operated to projection screen, and finger blocks portion of incident light, be formed by image light signals into
Enter infrared camera；
Step 3: pre-processing the picture signal in step 2, and the three-dimensional mould of object is constructed by spatial digitizer
Type, set initial boundary conditions, according to boundary condition carry out threedimensional model Region Decomposition, decomposition obtain in parallel computation always into
The equal submodel number of number of passes, using initial boundary conditions as design conditions, when boundary condition initial in calculating process occurs
Change then restarts boundary setting program, calculates again the submodel, is until boundary is stable or calculates sub- result
Constant reads in corresponding input file in current process, using Concurrent Feature curved line arithmetic to the nonlinear terms in governing equation
Linearization process is carried out, positive definite, symmetrical local linear system are obtained, if boundary condition changes and restarts boundary and set
Program is set, then is calculated, until boundary is stable or the sub- result of calculating is permanent；Every calculating for completing certain time, into
The read-write operation of output file of row；
Step 4: the electromagnetic interference during selecting Wavelet Transform Threshold method pretreated to step 3 in circuit is (i.e. high
Frequency noise) it is denoised；
Step 5: using WAVELET PACKET DECOMPOSITION, difference algorithm, from three directions of four areal pressures, (left and right, is hung down at front and back respectively
Time domain frequency domain feature directly) is extracted, is identified with SVM；
Step 6: the step extracted by the brightness and brightness uniformity combination fuzzy C-mean algorithm method that detect from step 5
Minimum wavelet packets set is selected in multiple wavelet packets of state frequency domain character, then is based on fuzzy membership with fuzzy C-mean algorithm method
Minimum wavelet packets decomposition coefficient is selected in sequence from the set picked out, and obtains minimum optimal gait frequency domain character subset,
It is combined again with gait temporal signatures, obtains fused gait feature collection, Gait Recognition is then carried out using SVM, use is non-thread
Property mapping Radial basis kernel function the lower dimensional space of linearly inseparable is mapped to the higher dimensional space of linear separability to identify modeling,
Classifier is first trained, then is identified with classifier and adds sample；
Step 7: acquiring step 2 to step 7 by mobile phone and the touch signal handled is analyzed, and reacts
Onto the screen of projection, the operation to projection screen is realized according to touch signal instruction；
Step 8: for operator constantly repeat step 1 to step 7 process, with the increase SVM of sample amount
Classifier can adaptively be continued to optimize to improve inputs new sample every time, according to cross-validation method principle, calculates SVM classifier
Discrimination carries out Fitness analysis, does not set the stop value of genetic algorithm, and termination condition is used than supreme people's court, if the knowledge of training
Rate is not higher than existing, is set as optimized parameter, otherwise, executes the operations such as selection, intersection and variation and advanced optimizes training parameter,
Implementation model it is adaptive perfect, finally formed according to personal viewing habit and motor habit for personal personalized mould
Type project based on the personalization of SVM classifier internal data by mobile phone and projector, constantly from complete according to personalized model
The touching instruction of kind different people controls projection screen.
In the present embodiment, the frequency domain character extraction in step 5 refers to that frequency domain character is comparative and classification can speed to improve
Degree: first normalizing to same value for speed dimension with linear interpolation algorithm, and speed after normalizing is gone out by first-order difference algorithm search
The trough point spent on vertical speed curve will be in speed with linear interpolation method by the carry out reference as a reference point of trough point
Left and right, front and back and vertical direction curve waveform alignment, the vertical speed curve in the speed after denoising is calculated with first-order difference
Method detects the trough point of vertical direction, as the reference point of rate curve, on the basis of reference point, with linear interpolation method to speed
Degree carries out waveform alignment, the speed after being aligned, then extracts whole frequency domain from speed with L layers of wavelet packet decomposition algorithm
Feature.
In the present embodiment, brightness refers to the luminous intensity perpendicular to unit area in direction of beam propagation, and brightness is equal
Even property refers to that the length of projected picture and wide all trisection, entire pictures are divided into nine parts, located uniformly respectively at nine on screen
It is a, the ratio between brightness maxima and minimum value.
In the present embodiment, the indicatrix algorithm in the step 3 carries out the nonlinear terms in governing equation linear
Change processing, obtains positive definite, symmetrical local linear system are as follows:
Wherein, K(i)For local stiffness matrix, U(i)For local known variables, f(i)For known localized external force vector, R(i)
The 0-1 matrix mapped between local element mark number and whole element number；
Surface freedom degree equation is as follows:
Wherein,For current area domain internal degree of freedom,Current area field surface and other region border parts are certainly
By spending；
For the corresponding outer force vector of current area domain internal degree of freedom；
For the corresponding outer force vector of current area field surface freedom degree；
Other K components are that matrix carries out corresponding matrix in block form after elementary row-column transform；It is calculated with balance fore condition iteration
Method solves surface freedom degree equation, obtainsuBLinear system will be substituted into
System, is obtained using direct method.
In the present embodiment, common camera described in step 2 adds infrared fileter.
In the present embodiment, the laser emitter is mounted on projector.
In the present embodiment, spatial digitizer described in step 3 arrives mobile phone by network connection.
The beneficial effects of the present invention are:
Present device acquires the human eye of different people, gesture motion by projector, the infrared depth of field camera of different angle,
Judge that the movement that everyone is suitble to prejudges model by deep learning, drop while the secondary projector of starting reduces time delay can be prejudged
Low-power consumption, and the personalized portrait movement manipulation for being suitble to everyone to use can be established according to human action speed, acceleration, amplitude
Model, and by study, constantly improve suitable personal height in the knowledge base of cloud, gender, figure manipulation model, for for the first time
The correspondence portrait crowd used is prefabricated.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings:
As shown in Figure 1, desktop projection holographic technique, successively carries out as steps described below:
Step 1: four infrared cameras and projector are placed in four corners of desktop, with projector by receiving mobile phone letter
It number is imaged on the table, and the communication module on infrared camera is connect with cloud host machine；
Step 2: the LED infrared ray transmitting lamp group on the vertical both sides on infrared touch frame emits orderly infrared ray,
It is woven into the intensive infrared net of one side in infrared touch frame, forms an infrared touch area, camera first carries out people
Face identification starting, projector are that video acquisition input is set as output equipment, two common cameras (installing infrared fileter additional)
It is standby, touch area is illuminated by infrared LED, the image coordinate of finger fingertip is extracted by visual detection algorithm, and then is passed through
Two images and binocular distance measurement principle calculate the three-dimensional coordinate of finger tip, and judge whether it has touched touch desktop,
Touch control operation just blocks the infrared ray on vertical and horizontal direction when referring to the certain point for touching screen, laser emitter outgoing
Illumination is mapped on the finger operated to projection screen, and finger blocks portion of incident light, be formed by image light signals into
Enter infrared camera；
Step 3: pre-processing the picture signal in step 2, and the three-dimensional mould of object is constructed by spatial digitizer
Type, set initial boundary conditions, according to boundary condition carry out threedimensional model Region Decomposition, decomposition obtain in parallel computation always into
The equal submodel number of number of passes, using initial boundary conditions as design conditions, when boundary condition initial in calculating process occurs
Change then restarts boundary setting program, calculates again the submodel, is until boundary is stable or calculates sub- result
Constant reads in corresponding input file in current process, using Concurrent Feature curved line arithmetic to the nonlinear terms in governing equation
Linearization process is carried out, positive definite, symmetrical local linear system are obtained, if boundary condition changes and restarts boundary and set
Program is set, then is calculated, until boundary is stable or the sub- result of calculating is permanent；Every calculating for completing certain time, into
The read-write operation of output file of row；
Step 4: the electromagnetic interference during selecting Wavelet Transform Threshold method pretreated to step 3 in circuit is (i.e. high
Frequency noise) it is denoised；
Step 5: using WAVELET PACKET DECOMPOSITION, difference algorithm, from three directions of four areal pressures, (left and right, is hung down at front and back respectively
Time domain frequency domain feature directly) is extracted, is identified with SVM；
Step 6: the step extracted by the brightness and brightness uniformity combination fuzzy C-mean algorithm method that detect from step 5
Minimum wavelet packets set is selected in multiple wavelet packets of state frequency domain character, then is based on fuzzy membership with fuzzy C-mean algorithm method
Minimum wavelet packets decomposition coefficient is selected in sequence from the set picked out, and obtains minimum optimal gait frequency domain character subset,
It is combined again with gait temporal signatures, obtains fused gait feature collection, Gait Recognition is then carried out using SVM, use is non-thread
Property mapping Radial basis kernel function the lower dimensional space of linearly inseparable is mapped to the higher dimensional space of linear separability to identify modeling,
Classifier is first trained, then is identified with classifier and adds sample；
Step 7: acquiring step 2 to step 7 by mobile phone and the touch signal handled is analyzed, and reacts
Onto the screen of projection, the operation to projection screen is realized according to touch signal instruction；
Step 8: for operator constantly repeat step 1 to step 7 process, with the increase SVM of sample amount
Classifier can adaptively be continued to optimize to improve inputs new sample every time, according to cross-validation method principle, calculates SVM classifier
Discrimination carries out Fitness analysis, does not set the stop value of genetic algorithm, and termination condition is used than supreme people's court, if the knowledge of training
Rate is not higher than existing, is set as optimized parameter, otherwise, executes the operations such as selection, intersection and variation and advanced optimizes training parameter,
Implementation model it is adaptive perfect, finally formed according to personal viewing habit and motor habit for personal personalized mould
Type project based on the personalization of SVM classifier internal data by mobile phone and projector, constantly from complete according to personalized model
The touching instruction of kind different people controls projection screen.
In the present embodiment, the frequency domain character extraction in step 5 refers to that frequency domain character is comparative and classification can speed to improve
Degree: first normalizing to same value for speed dimension with linear interpolation algorithm, and speed after normalizing is gone out by first-order difference algorithm search
The trough point spent on vertical speed curve will be in speed with linear interpolation method by the carry out reference as a reference point of trough point
Left and right, front and back and vertical direction curve waveform alignment, the vertical speed curve in the speed after denoising is calculated with first-order difference
Method detects the trough point of vertical direction, as the reference point of rate curve, on the basis of reference point, with linear interpolation method to speed
Degree carries out waveform alignment, the speed after being aligned, then extracts whole frequency domain from speed with L layers of wavelet packet decomposition algorithm
Feature.
In the present embodiment, brightness refers to the luminous intensity perpendicular to unit area in direction of beam propagation, and brightness is equal
Even property refers to that the length of projected picture and wide all trisection, entire pictures are divided into nine parts, located uniformly respectively at nine on screen
It is a, the ratio between brightness maxima and minimum value.
In the present embodiment, the indicatrix algorithm in the step 3 carries out the nonlinear terms in governing equation linear
Change processing, obtains positive definite, symmetrical local linear system are as follows:
Wherein, K(i)For local stiffness matrix, U(i)For local known variables, f(i)For known localized external force vector, R(i)
The 0-1 matrix mapped between local element mark number and whole element number；
Surface freedom degree equation is as follows:
Wherein,For current area domain internal degree of freedom,Current area field surface and other region border parts are certainly
By spending；
For the corresponding outer force vector of current area domain internal degree of freedom；
For the corresponding outer force vector of current area field surface freedom degree；
Other K components are that matrix carries out corresponding matrix in block form after elementary row-column transform；It is calculated with balance fore condition iteration
Method solves surface freedom degree equation, obtainsuBLinear system will be substituted into
System, is obtained using direct method.
In the present embodiment, common camera described in step 2 adds infrared fileter.
In the present embodiment, the laser emitter is mounted on projector.
In the present embodiment, spatial digitizer described in step 3 arrives mobile phone by network connection.
It should be noted last that: the above embodiments are only used to illustrate and not limit the technical solutions of the present invention, although ginseng
It is described the invention in detail according to above-described embodiment, it will be apparent to an ordinarily skilled person in the art that: it still can be to this
Invention is modified or replaced equivalently, without departing from the spirit or scope of the invention, or any substitutions,
It is intended to be within the scope of the claims of the invention.
Claims (7)
1. desktop projection holographic technique, it is characterised in that: successively carry out as steps described below:
Step 1: four infrared cameras and projector are placed in four corners of desktop, are existed with projector by receiving mobile phone signal
It is imaged on desktop, and the communication module on infrared camera is connect with cloud host machine；
Step 2: the LED infrared ray transmitting lamp group on the vertical both sides on infrared touch frame emits orderly infrared ray, infrared
It is woven into the intensive infrared net of one side in line touching box, forms an infrared touch area, camera first carries out face knowledge
Do not start, for projector as output equipment, two common cameras are video acquisition input equipment, illuminate touching by infrared LED
Region is touched, the image coordinate of finger fingertip is extracted by visual detection algorithm, and then survey by two images and binocular vision
The three-dimensional coordinate of finger tip is calculated away from principle, and judges whether it has touched touch desktop, and touch control operation is when in finger touch screen
When the certain point of curtain, just block the infrared ray on vertical and horizontal direction, the illumination of laser emitter outgoing be mapped to projection screen into
On the finger of row operation, finger blocks portion of incident light, is formed by image light signals and enters infrared camera；
Step 3: pre-processing the picture signal in step 2, and the threedimensional model of object is constructed by spatial digitizer, if
Determine initial boundary conditions, threedimensional model Region Decomposition is carried out according to boundary condition, decomposition obtains and process number total in parallel computation
Equal submodel number, using initial boundary conditions as design conditions, when boundary condition initial in calculating process changes
Boundary setting program is then restarted, the submodel is calculated again, is constant until boundary is stable or calculates sub- result,
Corresponding input file in current process is read in, line is carried out to the nonlinear terms in governing equation using Concurrent Feature curved line arithmetic
Propertyization processing, obtains positive definite, symmetrical local linear system, if boundary condition, which changes, restarts boundary setting journey
Sequence, then calculated, until boundary is stable or the sub- result of calculating is permanent；Every calculating for completing certain time, carries out one
The read-write operation of secondary output file；
Step 4: the electromagnetic interference during selecting Wavelet Transform Threshold method pretreated to step 3 in circuit (i.e. make an uproar by high frequency
Sound) it is denoised；
Step 5: using WAVELET PACKET DECOMPOSITION, difference algorithm respectively from three directions of four areal pressures (left and right, front and back, vertical)
Time domain frequency domain feature is extracted, is identified with SVM；
Step 6: the gait frequency extracted by the brightness and brightness uniformity combination fuzzy C-mean algorithm method that detect from step 5
Minimum wavelet packets set is selected in multiple wavelet packets of characteristic of field, then is sorted with fuzzy C-mean algorithm method based on fuzzy membership
Minimum wavelet packets decomposition coefficient is selected from the set picked out, and obtains minimum optimal gait frequency domain character subset, then with
The combination of gait temporal signatures, obtains fused gait feature collection, then carries out Gait Recognition using SVM, is reflected using non-linear
It penetrates Radial basis kernel function and the lower dimensional space of linearly inseparable is mapped to the higher dimensional space of linear separability to identify modeling, first instruct
Practice classifier, then is identified with classifier and add sample；
Step 7: acquiring step 2 to step 7 by mobile phone and the touch signal handled is analyzed, and is reacted to throwing
On the screen of shadow, the operation to projection screen is realized according to touch signal instruction；
Step 8: for operator constantly repeat step 1 to step 7 process, with the increase svm classifier of sample amount
Device can adaptively be continued to optimize to improve inputs new sample every time, according to cross-validation method principle, calculates SVM classifier identification
Rate carries out Fitness analysis, does not set the stop value of genetic algorithm, and termination condition is used than supreme people's court, if the discrimination of training
Higher than existing, it is set as optimized parameter, otherwise, selection is executed, intersects and the operations such as variation advanced optimize training parameter, realize
Model it is adaptive perfect, finally formed according to personal viewing habit and motor habit for personal personalized model, root
Project based on the personalization of SVM classifier internal data by mobile phone and projector according to personalized model, constantly improve certainly not
Touching instruction with people controls projection screen, and using personal characteristics supervised learning training result as pair constantly refined
Should draw a portrait the input foundation of crowd.
2. desktop projection holographic technique according to claim 1, it is characterised in that: the frequency domain character in step 5, which extracts, is
Refer to comparative with classification Energy velocity to improve frequency domain character: speed dimension first being normalized into same value with linear interpolation algorithm,
Go out the trough point after normalizing on speed vertical speed curve by first-order difference algorithm search, using trough point as reference
Point carries out reference, is aligned left and right, front and back and the vertical direction curve waveform in speed with linear interpolation method, by the speed after denoising
Vertical speed curve in degree detects the trough point of vertical direction with first-order difference algorithm, as the reference point of rate curve,
On the basis of reference point, waveform alignment is carried out to speed with linear interpolation method, the speed after being aligned, then with L layers of wavelet packet
Decomposition algorithm extracts whole frequency domain character from speed.
3. desktop projection holographic technique according to claim 1, it is characterised in that: common camera described in step 2 installs additional
There is infrared fileter.
4. desktop projection holographic technique according to claim 1, it is characterised in that: the laser emitter is mounted on projection
On instrument.
5. desktop projection holographic technique according to claim 1, it is characterised in that: spatial digitizer described in step 3 is logical
Network connection is crossed to mobile phone.
6. desktop projection holographic technique according to claim 1, it is characterised in that: brightness refers to perpendicular to beam propagation
The luminous intensity of unit area on direction, brightness uniformity refer to that the length of projected picture and wide all trisection, entire pictures are divided into
It nine parts, located uniformly respectively at nine points on screen, the ratio between brightness maxima and minimum value.
7. desktop projection holographic technique according to claim 4, it is characterised in that: the indicatrix in the step 3 is calculated
Method carries out linearization process to the nonlinear terms in governing equation, obtains positive definite, symmetrical local linear system are as follows:
Wherein, K(i)For local stiffness matrix, U(i)For local known variables, f(i)For known localized external force vector, R(i)For office
The 0-1 matrix mapped between portion's element mark number and whole element number；
Surface freedom degree equation is as follows:
Wherein,For current area domain internal degree of freedom,Current area field surface and other region border parts are free
Degree；
For the corresponding outer force vector of current area domain internal degree of freedom；
For the corresponding outer force vector of current area field surface freedom degree；
Other K components are that matrix carries out corresponding matrix in block form after elementary row-column transform；With balance pre conditioning iteration pair
Surface freedom degree equation is solved, and is obtaineduBLinear system will be substituted into, will be adopted
It is obtained with direct method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811002476.3A CN109189276A (en) | 2018-08-29 | 2018-08-29 | Desktop projection holographic technique |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811002476.3A CN109189276A (en) | 2018-08-29 | 2018-08-29 | Desktop projection holographic technique |
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| CN109189276A true CN109189276A (en) | 2019-01-11 |
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ID=64917203
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|---|---|---|---|---|
| US20030235332A1 (en) * | 2002-06-20 | 2003-12-25 | Moustafa Mohamed Nabil | System and method for pose-angle estimation |
| CN202795308U (en) * | 2012-08-31 | 2013-03-13 | 深圳市印天印象科技有限公司 | Tabletop projection touch control system |
| CN103679809A (en) * | 2013-12-24 | 2014-03-26 | 中山大学 | Data parallel treatment based virtual reality 3D simulation method and system |
| CN107102728A (en) * | 2017-03-28 | 2017-08-29 | 北京犀牛数字互动科技有限公司 | Display methods and system based on virtual reality technology |
| CN107197223A (en) * | 2017-06-15 | 2017-09-22 | 北京有初科技有限公司 | The gestural control method of micro-projection device and projector equipment |
| CN107753026A (en) * | 2017-09-28 | 2018-03-06 | 古琳达姬（厦门）股份有限公司 | For the intelligent shoe self-adaptive monitoring method of backbone leg health |
-
2018
- 2018-08-29 CN CN201811002476.3A patent/CN109189276A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030235332A1 (en) * | 2002-06-20 | 2003-12-25 | Moustafa Mohamed Nabil | System and method for pose-angle estimation |
| CN202795308U (en) * | 2012-08-31 | 2013-03-13 | 深圳市印天印象科技有限公司 | Tabletop projection touch control system |
| CN103679809A (en) * | 2013-12-24 | 2014-03-26 | 中山大学 | Data parallel treatment based virtual reality 3D simulation method and system |
| CN107102728A (en) * | 2017-03-28 | 2017-08-29 | 北京犀牛数字互动科技有限公司 | Display methods and system based on virtual reality technology |
| CN107197223A (en) * | 2017-06-15 | 2017-09-22 | 北京有初科技有限公司 | The gestural control method of micro-projection device and projector equipment |
| CN107753026A (en) * | 2017-09-28 | 2018-03-06 | 古琳达姬（厦门）股份有限公司 | For the intelligent shoe self-adaptive monitoring method of backbone leg health |
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