CN103240746B - A kind of finger-guessing game robot and finger-guessing game gesture identification method with image identification system - Google Patents
A kind of finger-guessing game robot and finger-guessing game gesture identification method with image identification system Download PDFInfo
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Abstract
The invention discloses a kind of finger-guessing game robot and the finger-guessing game gesture identification method with image identification system, comprise pedestal, it is characterized in that: also comprise ultrasonic sensor, camera, Systematical control main frame and finger-guessing game robot body, pedestal is provided with finger-guessing game robot body, pedestal is provided with punch district, the punch arm of finger-guessing game robot body extend into punch district, finger-guessing game robot is provided with camera, pedestal is provided with the ultrasonic sensor whether detection has punch people, described ultrasonic sensor is connected with Systematical control main frame with camera.The invention solves finger-guessing game robot effectively to identify the finger-guessing game action of irregular finger-guessing game action and conversion gesture, recognition speed is slow, discrimination is low, the problem of normal recreation cannot be carried out, provide one and quick and precisely can identify user's finger-guessing game gesture, make the finger-guessing game process finger-guessing game robot with image identification system of vivid and interesting and finger-guessing game gesture identification method more.
Description
Technical field
The present invention relates to a kind of identifying processing operating system, particularly a kind of finger-guessing game robot and finger-guessing game gesture identification method with image identification system.
Background technology
Current finger-guessing game system simply has image recognition technology identification images of gestures and carries out finger-guessing game interaction, and it does not combine with robot, vivid not, and it is stiff to show.Simultaneously because user's punch gesture is different, finger-guessing game robot effectively cannot be identified the finger-guessing game action of irregular finger-guessing game action and conversion gesture, and recognition speed is slow, and discrimination is low, cannot carry out normal recreation.
Summary of the invention
Effectively cannot identify the finger-guessing game action of irregular finger-guessing game action and conversion gesture to solve finger-guessing game robot in prior art, recognition speed is slow, discrimination is low, the problem of normal recreation cannot be carried out, the invention provides one and quick and precisely can identify user's finger-guessing game gesture, make the finger-guessing game process finger-guessing game robot with image identification system of vivid and interesting and finger-guessing game gesture identification method more.
In order to solve the problem, the technical solution used in the present invention is:
A kind of finger-guessing game robot with image identification system, comprise pedestal, it is characterized in that: also comprise ultrasonic sensor, camera, Systematical control main frame and finger-guessing game robot body, pedestal is provided with finger-guessing game robot body, pedestal is provided with punch district, the punch arm of finger-guessing game robot body extend into punch district, finger-guessing game robot is provided with the camera of shooting punch people punch gesture, pedestal is provided with the ultrasonic sensor whether detection has punch people, and described ultrasonic sensor is connected with Systematical control main frame with camera.
Aforesaid a kind of finger-guessing game robot with image identification system, is characterized in that: also comprise illuminating lamp, is provided with the illuminating lamp providing illumination to punch district in finger-guessing game robot.
Aforesaid a kind of finger-guessing game robot with image identification system, it is characterized in that: also comprise sound equipment and touch display screen, described sound equipment and touch display screen are connected with Systematical control main frame respectively.
Aforesaid a kind of finger-guessing game robot with image identification system, it is characterized in that: described punch arm comprises finger, finger pull bar, arm bar, steering wheel, steering wheel and motor, described motor is connected with steering wheel by arm bar, described servos control steering wheel drives the motion of finger pull bar, and described finger pull bar end is connected with finger.
Aforesaid a kind of finger-guessing game robot with image identification system, it is characterized in that: also comprise motor cabinet, steering wheel installing plate and base plate, on described motor mounted motor seat, described motor cabinet is bolted and is fixed on base plate, and steering wheel installing plate is provided with steering wheel.
Aforesaid a kind of finger-guessing game robot with image identification system, it is characterized in that: described arm bar comprises arm rocking bar, arm link and drive crank, motor cabinet is provided with arm rocking bar, arm rocking bar by arm link and drive crank one section hinged, described motor is connected with the drive crank other end.
A kind of punch people finger-guessing game gesture identification method, is characterized in that: comprise the following steps:
(1), camera catches the random finger-guessing game action of punch people,
(2), punch people finger-guessing game motion images is sent to the message handler in Systematical control main frame by image processing platform, message handler is by inner image recognition technology, extract staff region, then analyze this region further, finger-guessing game action is identified;
Aforesaid a kind of punch people finger-guessing game gesture identification method, it is characterized in that: in step 1, camera is caught in the course of action of punch people to comprise and is repeatedly caught and identification, the error rate of identification can be reduced by this method, and effectively can identify the cheating of Fast transforms gesture in the punch people short time, increase the intelligent and interesting of system.
Aforesaid a kind of punch people finger-guessing game gesture identification method, is characterized in that: further comprising the steps of: between step (1) and step (2), be provided with step:
Finger-guessing game robot produces finger-guessing game action at random;
Step is provided with successively after step (2):
Message handler, by the finger-guessing game action of the punch people finger-guessing game action that identifies and robot, draws finger-guessing game result;
Systematical control main frame, by the finger-guessing game result of message handler, controls sound equipment and carries out robot sounding, carry out finger-guessing game interaction, increase recreational and interesting with the punch human world.
Aforesaid a kind of punch people finger-guessing game gesture identification method, is characterized in that: the finger-guessing game action of described step (2) to punch people is carried out identification and be divided into two steps:
The first step, from image, determine the position of palm.
In the image information obtained by step (1), we, by analyzing the colouring information of human skin, determine the position of staff and extract, doing binary conversion treatment, are convenient to next step and analyze.Then by the angle of the geological information determination finger-guessing game palm of staff.Then according to the angle obtained, image is rotated, makes just in the staff image maintenance level of punch,
Second step, the palm image after binaryzation to be analyzed, draws gesture identification result:
Comprise following two kinds of methods:
A kind of punch people finger-guessing game gesture identification method stated, is characterized in that: the finger-guessing game action of described step (2) to punch people is carried out identification and comprised following two kinds of methods:
One, judged according to the position of finger and quantity by Bezier;
1), Bezier expression formula is such as formula (1):,
B(t)＝(1-t)[(1-t)P
0+tP
1]+t[(1-t)P
1+tP
2],t∈[0,1]（1）
In formula (1), t represents process parameter, controls node from starting point P
0to terminal P
2motion, this formula generates the curve of a continuously smooth, and this curve is from P
0point starts, to P
1point motion, finally arrives P
2point, P
0, P
1, P
2represent three characteristic points,
2), have employed second order Bezier, expression formula is such as formula (2):,
B(t)＝(1-t)
2P
0+2(1-t)tP
1+t
2P
2,t∈[0,1]
（2）
In formula (2), t represents process parameter, controls node from starting point P
0to terminal P
2motion, P
0, P
1, P
2represent three characteristic points, Bezier is determined by these characteristic points;
3), the choosing of Bezier characteristic point, according to coordinate position selected characteristic point, round the point near staff, use P respectively
0, P
1, P
2and P
2, P
3, P
4as the characteristic point of Bezier, draw out two second order Beziers; Coordinate position is P
0for
p
1for
p
2for
p
3for
p
4for
w: images of gestures wide, L: the length of images of gestures,
Article two, Bezier is at a P
2intersect, form a complete curve, by increase and the parameter n of process parametric t, the point on controlling curve is from P
0to P
4mobile, Detection curve equation as shown in Equation (3):
（3）
Step-length is set to several sampled points, and when the pixel point value on sampled point is not equal to 0, we think that this pixel is effective, and we are by counter+1, continue to detect next sampled point; When this pixel equals 0, counter O reset, continues to detect next sampled point;
In the process of sampling, if Counter Value count ∈ [50,200), just think and recognized a finger; If during Counter Value count >=200, we just think and have recognized palm; According to this method, if we have recognized 2 fingers, we have just thought that gesture is scissors; If recognize the finger of more than 4, we just think that gesture is cloth; If recognize palm and do not point, we just think that gesture is fist, and other situations be can not determine, we will use robotics and the method for coupling carries out secondary judgement, conclude.
Two, Systematical control main frame uses pre-prepd 100 groups of data to train, and then the hand-type obtained by image processing platform and training result are compared, and draw judgement.
The invention has the beneficial effects as follows:
The present invention is based on the optimization existing finger-guessing game base game adding algorithm, effectively can identify the finger-guessing game gesture of irregular finger-guessing game gesture and conversion action.Finger-guessing game algorithm after optimization effectively combines with robot by the present invention simultaneously, and robot can pass through mechanical arm punch, makes finger-guessing game process vivid and interesting more.
Accompanying drawing explanation
Fig. 1 is that the present invention carries out finger-guessing game interactive process flow chart.
Fig. 2 is the finger-guessing game robot architecture schematic diagram that the present invention has image identification system.
Fig. 3 is punch arm configuration schematic diagram of the present invention.
Fig. 4 is that gesture of the present invention extracts binary conversion treatment schematic diagram.
Fig. 5 is the present invention three rank Bezier schematic diagrames.
Fig. 6 is Bezier characteristic point chosen position schematic diagram of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing, the invention will be further described.
As Figure 1-Figure 2, a kind of finger-guessing game robot with image identification system, comprise Systematical control main frame 12, ultrasonic sensor 13, illuminating lamp 15, camera 16, sound equipment 17, touch display screen 18, finger-guessing game robot body 19 and pedestal 20, pedestal 20 is provided with finger-guessing game robot body 19, on pedestal, 20 are provided with punch district 14, the punch arm of finger-guessing game robot body 19 extend into punch district 14, the camera 16 of shooting punch people punch gesture is provided with in side, punch district 1, pedestal 20 is provided with the ultrasonic sensor 13 whether detection has punch people, described ultrasonic sensor 13 is connected with Systematical control main frame 12 with camera 16.The illuminating lamp 15 that illumination is provided to punch district 14 is provided with in finger-guessing game robot.Described sound equipment 17 is connected with Systematical control main frame 12 respectively with touch display screen 18.
There is the finger-guessing game machine man-hour of image identification system, whether ultrasonic sensor 13 detects has spectators to occur, occur if any spectators, control program uses voice automatically to invite spectators to participate in science popularization interaction by sound equipment 17, uses touch display screen 18 that spectators can be allowed to carry out about the scientific knowledge of finger-guessing game is explained.The various gestures that system is appeared in punch district 14 by camera 16 collection, and provide reliable illumination by illuminating lamp 15.Whole operating process is reliably controlled by Systematical control main frame 12.
As shown in Figure 3, punch arm comprises motor cabinet 1, arm rocking bar 2, finger 3, finger pull bar 4, steering wheel 5, steering wheel 6, steering wheel installing plate 7, base plate 8, arm link 9, drive crank 10 and motor 11.On motor 11 mounted motor seat 1, motor cabinet 1 is bolted and is fixed on base plate 8, and base plate 8 plays a supportive role to whole mechanical arm.Motor cabinet 1 is provided with arm rocking bar 2, and arm rocking bar 2 is hinged by arm link 9 and drive crank 10 1 sections, and described motor 11 is connected with drive crank 10 other end.Arm rocking bar 2 is provided with steering wheel installing plate 7, steering wheel installing plate 7 is provided with steering wheel 6, steering wheel 6 and steering wheel 5 connection control steering wheel 5 drive to be pointed pull bar 4 and moves, and described finger pull bar 4 end is connected with finger 3.
Punch people finger-guessing game gesture identification method of the present invention, comprises the following steps:
Step S1, camera catches the random finger-guessing game action of user.
Step S2, finger-guessing game robot produces finger-guessing game action at random.
Step S3, user's finger-guessing game motion images is sent to the message handler in Systematical control main frame by image processing platform, and message handler, by inner image recognition technology, identifies the finger-guessing game action of user.Resolving Algorithm is guessed in the finger-guessing game action that with the addition of optimization in this step, effectively can identify irregular finger-guessing game action to a certain degree and the finger-guessing game action converting gesture.
New finger-guessing game gesture identification method is divided into two steps carrying out identification:
The first step, from image, determine the position of palm.
In the image information obtained by step S1, we, by analyzing the colouring information of human skin, determine the position of staff and extract, doing binary conversion treatment, are convenient to next step and analyze.Then by the angle of the geological information determination finger-guessing game palm of staff, these information comprise the Aspect Ratio of palm, the direction of forearm and the direction etc. of finger.Then according to the angle obtained, image is rotated, make just in the staff image maintenance level of punch, as shown in Figure 4.
Second step, the palm image after binaryzation to be analyzed, draws gesture identification result:
In new Gesture Recognition Algorithm, apply two kinds of recognizers, they work respectively, result are merged subsequently, draw last hand-type conclusion.These two kinds of recognizers are a kind of is judge according to the position pointed and quantity, it applies Bezier (B é zier curve); Second method employs the method for machine learning.Before making a determination, system uses pre-prepd 100 groups of data to train, and then the hand-type obtained and training result is compared, and draws judgement.
For the method for information fusion, we adopt and use Bezier method to be master, the mode that machine learning method is assisted.When in the reliable not situation of conclusion that first method draws, we carry out auxiliary judgment with reference to second method.Because new algorithm has incorporated two kinds of recognizers, and organically combined, new system greatly strengthens in identification certainty.
Bezier expression formula is such as formula (1):,
B(t)＝(1-t)[(1-t)P
0+tP
1]+t[(1-t)P
1+tP
2],t∈[0,1]
（1）
In formula (1), t represents process parameter, controls node from starting point P
0to terminal P
2motion, this formula generates the curve of a continuously smooth, and this curve is from P
0point starts, to P
1point motion, finally arrives P
2point.P
0, P
1, P
2represent three characteristic points.
In this application, we have employed second order Bezier, as shown in Figure 4,
B(t)＝(1-t)
2P
0+2(1-t)tP
1+t
2P
2,t∈[0,1]
（2）
In formula (2), t represents process parameter, controls node from starting point P
0to terminal P
2motion, P
0, P
1, P
2represent three characteristic points, Bezier is determined by these characteristic points.Through appropriate selected characteristic point, draw out gratifying Bezier, be looped around around palm, judge the state of finger, thus correct identification hand-type.
Choosing of Bezier characteristic point, as shown in Figure 4, through skin color identification and binary conversion treatment, we extract staff image and are full of whole picture.Once successfully be extracted hand-type, we just can according to the coordinate position selected characteristic point shown in table 1, and as shown in Fig. 6 Bezier characteristic point chosen position schematic diagram, round the point near staff, we use P respectively
0, P
1, P
2and P
2, P
3, P
4as the characteristic point of Bezier, draw out two second order Beziers.
Table 1. characteristic point position table
These two Beziers are at a P
2intersect, form a complete curve.Because image has been binary image, only have the pixel of palm effective, the value of other point is 0, and we can by the increase of process parametric t and parameter n, and the point on controlling curve is from P
0to P
4mobile, Detection curve equation as shown in Equation (3):
In actual applications, we are set to 1000 step-length, that is sample each time, and process parametric t increases by 0.02, t ∈ [0,1], and two Beziers altogether, come to 1000 sampled points.When the pixel point value on sampled point is not equal to 0, we think that this pixel is effective, and we are by counter+1, continue to detect next sampled point; When this pixel equals 0, counter O reset, continues to detect next sampled point.In the process of sampling, if Counter Value count ∈ [50,200), we just think and have recognized a finger; If during Counter Value count >=200, we just think and have recognized palm.According to this method, if we have recognized 2 fingers, we have just thought that gesture is scissors; If recognize the finger of more than 4, we just think that gesture is cloth; If recognize palm and do not point, we just think that gesture is fist; Other situations be can not determine, we will use robotics and the method for coupling carries out secondary judgement, conclude.
Step S4, message handler, by the finger-guessing game action of user's finger-guessing game action of identifying and robot, draws finger-guessing game result.
Step S5, Systematical control main frame, by the finger-guessing game result of message handler, controls sound-producing device and carries out robot sounding, and carry out finger-guessing game interaction between user, increase recreational and interesting.More than show and describe general principle of the present invention, principal character and advantage.The technical staff of the industry should understand; the present invention is not restricted to the described embodiments; what describe in above-described embodiment and description just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements all fall in the claimed scope of the invention.Application claims protection domain is defined by appending claims and equivalent thereof.
Claims (2)
1. one kind has the finger-guessing game robot of image identification system, comprise pedestal, ultrasonic sensor, camera, sound equipment, touch display screen, motor cabinet, steering wheel installing plate and base plate, Systematical control main frame and finger-guessing game robot body, pedestal is provided with finger-guessing game robot body, it is characterized in that: on pedestal, be provided with punch district, the punch arm of finger-guessing game robot body extend into punch district, finger-guessing game robot is provided with the camera of shooting punch people punch gesture, pedestal is provided with the ultrasonic sensor whether detection has punch people, described ultrasonic sensor is connected with Systematical control main frame with camera, the illuminating lamp that illumination is provided to punch district is provided with in finger-guessing game robot, described sound equipment and touch display screen are connected with Systematical control main frame respectively, described punch arm comprises finger, finger pull bar, arm bar, steering wheel, steering wheel and motor, described motor is connected with steering wheel by arm bar, described servos control steering wheel drives the motion of finger pull bar, described finger pull bar end is connected with finger, on described motor mounted motor seat, described motor cabinet is bolted and is fixed on base plate, steering wheel installing plate is provided with steering wheel, described arm bar comprises arm rocking bar, arm link and drive crank, motor cabinet is provided with arm rocking bar, arm rocking bar by arm link and drive crank one section hinged, described motor is connected with the drive crank other end.
2. a punch people finger-guessing game gesture identification method, is characterized in that: comprise the following steps:
(1), camera catches the random finger-guessing game action of punch people, and finger-guessing game robot produces finger-guessing game action at random;
(2), punch people finger-guessing game motion images is sent to the message handler in Systematical control main frame by image processing platform, message handler is by inner image recognition technology, the finger-guessing game action of punch people is identified, message handler, by the finger-guessing game action of the punch people finger-guessing game action that identifies and robot, draws finger-guessing game result; Systematical control main frame, by the finger-guessing game result of message handler, controls sound equipment and carries out robot sounding, carry out finger-guessing game interaction with the punch human world;
The finger-guessing game action of described step (2) to punch people is carried out identification and is comprised following two kinds of methods:
One, judged according to the position of finger and quantity by Bezier;
1), Bezier expression formula is such as formula (1):,
B(t)＝(1-t)[(1-t)P
0+tP
1]+t[(1-t)P
1+tP
2],t∈[0,1] (1)
In formula (1), t represents process parameter, controls node from starting point P
0to terminal P
2motion, this formula generates the curve of a continuously smooth, and this curve is from P
0point starts, to P
1point motion, finally arrives P
2point, P
0, P
1, P
2represent three characteristic points,
2), have employed second order Bezier, expression formula is such as formula (2):,
B(t)＝(1-t)
2P
0+2(1-t)tP
1+t
2P
2,t∈[0,1] (2)
In formula (2), t represents process parameter, controls node from starting point P
0to terminal P
2motion, P
0, P
1, P
2represent three characteristic points, Bezier is determined by these characteristic points;
3), the choosing of Bezier characteristic point, according to coordinate position selected characteristic point, round the point near staff, use P respectively
0, P
1, P
2and P
2, P
3, P
4as the characteristic point of Bezier, draw out two second order Beziers; Coordinate position is P
0for
p
1for
p
2for
p
3for
p
4for
w: images of gestures wide, L: the length of images of gestures,
Article two, Bezier is at a P
2intersect, form a complete curve, by increase and the parameter n of process parametric t, the point on controlling curve is from P
0to P
4mobile, Detection curve equation is as shown in formula (3):
Step-length is set to several sampled points, and when the pixel point value on sampled point is not equal to 0, we think that this pixel is effective, and we are by counter+1, continue to detect next sampled point; When this pixel equals 0, counter O reset, continues to detect next sampled point;
In the process of sampling, if Counter Value count ∈ [50,200), just think and recognized a finger; If during Counter Value count >=200, we just think and have recognized palm; According to this method, if we have recognized 2 fingers, we have just thought that gesture is scissors; If recognize the finger of more than 4, we just think that gesture is cloth; If recognize palm and do not point, we just think that gesture is fist;
Two, Systematical control main frame uses pre-prepd 100 groups of data to train, and then the hand-type obtained by image processing platform and training result are compared, and draw judgement.
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| CN104524779A (en) * | 2014-12-08 | 2015-04-22 | 徐存然 | Robot arm for robot toy |
| CN105034006B (en) * | 2015-08-28 | 2017-03-22 | 昆山塔米机器人有限公司 | Finger-guessing game robot based on LeapMotion apparatus and finger-guessing game gesture recognition method |
| CN107329564B (en) * | 2017-06-09 | 2020-05-29 | 济南大学 | Man-machine finger guessing method based on gesture intelligent perception and man-machine cooperation mechanism |
| CN108491767B (en) * | 2018-03-06 | 2022-08-09 | 北京因时机器人科技有限公司 | Autonomous rolling response method and system based on online video perception and manipulator |
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