CN100582654C - Height measuring method and its measuring device - Google Patents
Height measuring method and its measuring device Download PDFInfo
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Abstract
The embodiment of the invention discloses a body height measuring method and a measuring device thereof, wherein, the method comprises the following steps: the position of a human body is detected, the judgment of whether the position of the human body enters a preset range or not is carried out; if yes, a human body video image is collected; a human face image is detected from the human body video image, the best human face image is obtained; and the body height is determined according to the best human face image. The implementation of the embodiment of the invention carries out the measurement of the body height based on the video human face image, a certain range is preset against people groups with the specific body height in an entrance channel under the situation of not changing the prior fixed facilities of the entrance channel, thereby facilitating the accurate calculation of the body height.
Description
Technical field
The present invention relates to human body height fields of measurement, relate to a kind of method for sieving and device for carrying out said that is used for the specific height crowd on the ticket selling and checking system particularly.
Background technology
Track traffic becomes the important component part of urban passenger traffic day by day, and (Automatic Fare Collection AFC) is one of the core system of track traffic to AFC system, and gate is the important module that realizes automatic ticket checking.At present the deficiency that exists of automatic ticket checking system is to free ticket and half fare children's height measuring method preferably not, and free of charge and half fare children's the regulation of height in each city also is not quite similar.The most infiltration type photocell pickofves that adopt of existing gate detect pedestrian's height, and this method detects height following 3 restraining factors:
(1) consider complete machine cost, subway owner's demand and the factors such as smoothness that the stream of people passes through, gate complete machine height that is to say that generally below 1.1 meters the setting height(from bottom) of photoelectric tube generally is no more than 1.1 meters.
(2) even the setting height(from bottom) of photoelectric tube can be above 1.1 meters, its position is fixed, but children's average height can increase along with the raising of quality of life, regulation to child ticket height also can change with the various places rules, use photocell detection height need change the equipment configuration design and satisfy various requirement, if and the true altitude of gate is too high, can make the people in the gate passage, produce the sensation of constraining.For this reason, need a kind of need not to change existing gate exterior design, the height detection method that sensing range is adjustable.
(3) penetrate the precision that the packing density decision of photoelectric tube is measured, if want to improve the height measuring accuracy, cost can corresponding increase.
Therefore, design is a kind of detects that the method that flexible, lower-cost access road human body height detects and the pick-up unit of implementing this method have extensively and important use is worth.
Summary of the invention
Technical matters to be solved by this invention is, a kind of method of flexible, lower-cost access road human body height detection and pick-up unit of implementing this method of detecting is provided.
In order to solve the problems of the technologies described above, the embodiment of the invention has proposed a kind of height measuring method, it is characterized in that, described method comprises:
The human body position judges whether described position of human body enters preset range;
Be judged as is then to gather the human body video image;
From described human body video image, detect and the screening facial image;
Facial image by screening is determined human body height.
Correspondingly, the embodiment of the invention also provides a kind of height measurement mechanism, it is characterized in that, described device comprises:
Detecting unit is used to detect position of human body and judges whether described position of human body enters preset range;
Collecting unit is used for judged result collection and storage human body video image according to described detecting unit;
Processing unit is used for detecting and the screening facial image from the human body video image of described collecting unit storage;
Computing unit is used for calculating human body height according to the best facial image of described processing unit screening.
Implement the embodiment of the invention, because being based on the video human face image carries out the measurement of human body height, can be at the crowd of specific height in the access road, under the situation that does not change the existing access road facility of fixing, set in advance certain scope, convenient human body video image and the best facial image of screening gathered accurately, determine human body height by the position of best facial image in image, also can be in passage detects according to the purpose that people's face reaches the specific height crowd of screening in specific monitoring range image, whether occurring.Cost is measured flexibly and saved to the embodiment of the invention.
Description of drawings
In order to be illustrated more clearly in the technical scheme of the embodiment of the invention, to do to introduce simply to the accompanying drawing of required use among the embodiment below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is an embodiment schematic flow sheet of the height measuring method of the embodiment of the invention;
Fig. 2 is the particular flow sheet of the height measuring method of the embodiment of the invention;
Fig. 3 is an example structure synoptic diagram of the height measurement mechanism of the embodiment of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on embodiments of the invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that is obtained under the creative work prerequisite.
For making purpose of the present invention, technical scheme and advantage clearer, below the embodiment of the invention is further described with reference to accompanying drawing.
Fig. 1 shows an embodiment schematic flow sheet of the height measuring method of embodiment among the present invention, and with reference to Fig. 1, described height measuring method comprises:
Step S101, the human body position.Step S102 judges whether described position of human body enters preset range.In the specific implementation, by preestablishing reconnaissance range, the human body position judges whether the pedestrian enters reconnaissance range, when judging pedestrian's arrival and entering reconnaissance range, with regard to execution in step S103; When the judgement pedestrian leaves and walks out reconnaissance range, with regard to detection of end.
Step S103 gathers the human body video image when judging after described position of human body enters preset range.In the specific implementation, the pedestrian is carried out the human body video image acquisition, and the human body video image of gathering stored for you to choose call when judging after described position of human body enters preset range.During described collection human body video image, the angle on acquisition plane and plane, human body place is that 45 degree are to 90 degree.
Step S104 detects facial image and obtains best facial image from described human body video image.Specifically comprise search possibility facial image from the human body video image of gathering; Possible facial image input neural network model with described search compares output valve; Comparative result according to described output valve obtains best facial image.Output valve described in the specific implementation is that the pairing facial image of maximal value is best facial image.This is wherein a kind of method of obtaining best facial image just, can also obtain best facial image by other model or algorithm certainly.
Step S105 determines human body height by described best facial image.In the specific implementation, because access road and pedestrian's position distance relation, according to optical imaging concept, the image that the pedestrian became keeps constant geometric proportion relation.Therefore, according to the position of best facial image in entire image and the ratio of the position of standard faces image in entire image of screening, just can determine pedestrian's height.
Fig. 2 is the particular flow sheet of the height measuring method of the embodiment of the invention, and with reference to Fig. 2, described height measuring method comprises:
Step S201, neural network model is trained, and obtains the weights of neural network model.In the specific implementation, adopt a plurality of facial images that one neural network model is trained, reach best neural network performance, obtain the weights of described neural network model until described neural network model.The neural network model of present embodiment is an artificial nerve network model, comprises input layer, output layer and hidden layer.At first a plurality of facial images are converted into gray level image from coloured image, adopt following formula to realize transforming: grayValue=0.30 * redValue+0.59 * greenValue+0.11 * blueValue.Transform the back and adopt the artificial neural network classification: as the input vector of described neural network model described neural network model is trained at the corresponding image in zone by colour of skin locking.The node number of the input layer of artificial neural network is the ' locked ' zone pixel count, detection has only people's face and non-face two states and for people's face, so output layer has only one deck, when output is people's face greater than 0.5, when being non-face smaller or equal to 0.5, and output valve is big more, and input picture approaches people's face more.Extract the effect of feature and the time and the complexity of training based on hidden layer, the embodiment of the invention adopts trial and error to determine that finally the hidden unit number of present networks is 17 layers.After the number of plies of determining artificial neural network, network is trained, at first choose 30 different facial images, and then choose 20 non-face images, wherein non-face image comprises other station diagram pictures of 10 person, 10 half facial images (near half facial image that preestablishes human body height scope edge).The test neural network, the non-face image that will be recognized adult's face continues as the sample repetition training.The neural network that trains is tested, if non-face situation about misdeeming to people's face, it is joined in the non-face image measurement sample, proceed training, mode by the study while training makes described neural network model reach best neural network performance, obtain the weights of described neural network model, when network runs into the facial image input once more, can make rapidly, judge accurately and discern.
Step S202, the standard heights human body is demarcated, and obtains the standard faces image.In the specific implementation, the standard heights human body is carried out the human body video image acquisition, from the human body video image of described collection, search out facial image,, output valve is compared, obtain the standard faces image described facial image input neural network model.In the embodiment of the invention, the demarcation of standard heights human body is only at specific height scope crowd, promptly 1.1 meters～1.4 meters crowd carries out, earlier the standard heights human body is carried out the human body video image acquisition, from the human body video image of described collection, search out facial image, with described facial image input neural network model, output valve is compared, the facial image of maximum output valve correspondence is exactly the optimality criterion facial image.The standard facial image is exactly that acquisition angles becomes 90 degree with the standard heights human body in the reality, the vertical facial image of taking, and this image definition, resolution and pixel value are the highest.
Step S203, the human body position.Step S204 judges whether described position of human body enters preset range.In the specific implementation, by preestablishing reconnaissance range, the human body position judges whether the pedestrian enters reconnaissance range, when judging pedestrian's arrival and entering reconnaissance range, with regard to execution in step S205; When the judgement pedestrian leaves and walks out reconnaissance range, with regard to detection of end.
Step S205 gathers the human body video image when judging after described position of human body enters preset range.In the specific implementation, the pedestrian is carried out the human body video image acquisition, and the human body video image of gathering stored for you to choose call when judging after described position of human body enters preset range.During described collection human body video image, the angle on acquisition plane and plane, human body place is that 45 degree are to 90 degree.
Step S206 searches for facial image from the human body video image of gathering.In the specific implementation, after finishing the human body video image acquisition, each frame human body video image of the automatic analyzing stored of digital signal processing appts meeting is therefrom searched for facial image.At first confine the hunting zone of people's face, width of channel is confined hunting zone, the left and right sides, and predefined human body height scope is the up-downgoing hunting zone.In this approximate range, determine that by the face complexion formula position of people's face appears in most probable.This process is the search facial image.Wherein the face complexion formula meets most of pixels: redValue＞green Value, redValue＞blue Value, abs (green Value-blue Value)＜T (T is a threshold value).In the reality because to sell the ticket checking passage generally be a plurality of connecting together, passage camera head may be taken the photograph the crowd of a plurality of passages and cause confusion, 1.1 meters～1.4 meters crowds of screening during therefore actual the use, and channel width is generally 0.5 meter, so the scope that actual search is handled approximately is that height is 1.1 meters～1.4 meters, wide is 0.5 meter image-region,, judge that this scope zone nobody's face just can be judged and do not belong to 1.1 meters～1.4 meters crowd.Adopt this mode that the processing image area is diminished, help accelerating data processing and the requirement that reduces hardware.
Step S207 imports described neural network model with the possible facial image of described search, and output valve is compared.In the specific implementation, because described neural network model has possessed best neural network performance, the possible facial image of described search is imported described neural network model can obtain output valve rapidly and accurately, described output valve is compared, the big more approaching more best facial image of output valve.
Step S208 obtains best facial image according to the comparative result of described output valve.In the specific implementation, after the corresponding output valve of the facial image of described search compared, choose the output valve maximum, the corresponding described facial image of maximum output valve is exactly best facial image.
Step S209 determines human body height by described best facial image.In the specific implementation, because access road and pedestrian's position distance relation, according to optical imaging concept, the image that the pedestrian became keeps constant geometric proportion relation.Therefore, according to the ratio of best facial image position and standard faces image position in standard picture in image of screening, just can determine pedestrian's height.In the present embodiment, identical according to beautiful woman's face of the ratio of human body height to be measured and standard human body height and screening ratio of position and standard faces picture position in image, thereby standard pedestrian height and the best facial image of being selected position and the standard faces image ratio of position in image in image multiplied each other and just can calculate human body height to be measured.
Fig. 3 is the structural representation of the height measurement mechanism of the embodiment of the invention, and with reference to Fig. 3, described height measurement mechanism is based on the video human face image and measures human body height, is mainly used in the measurement of human body height in the access road.This installs at first human body position, gathers the human body video image according to described position of human body, detects facial image and obtain best facial image from described human body video image, determines human body height by described best facial image at last.Described device is divided according to functional module and is specifically comprised training unit 31, detecting unit 32, collecting unit 33, processing unit 34 and computing unit 35, wherein detecting unit 32, collecting unit 33, processing unit 34 and computing unit 35 link to each other successively, and training unit 31 links to each other with processing unit 34.
Detecting unit 32 is used to detect the position of human body and judges whether described position of human body enters preset range.In the specific implementation, described detecting unit 32 is measured the pedestrian and whether is entered reconnaissance range, when the pedestrian arrives and enters reconnaissance range, sends the signal triggering collecting unit and carries out the human body video image acquisition; When the pedestrian left and walk out reconnaissance range, described detecting unit 31 stopped to detect.Described detection can be photoelectric sensor or ultrasonic detector for single 31 yuan, and the embodiment of the invention is a photoelectrical position sensor.
Collecting unit 33, be used for entering preset range and gathered and stored the human body video image afterwards according to the position of human body that described detecting unit is judged, in the specific implementation, comprise the image unit 331 and the storage unit 332 that is used for the human body video image that described image unit is taken is stored that are used to take the human body video image.Collecting unit 33 carries out the human body video image acquisition to the pedestrian after receiving the trigger pip of detecting unit 32, and the human body video image of gathering is stored for you to choose call.The angle on the acquisition plane of described collecting unit and plane, human body place is that 45 degree are to 90 degree.Embodiment of the invention image unit 331 is a camera, and described camera is installed in entryway's sidewall in face of the direction that the pedestrian advances, and is level angle on the upper side, with the optimum distance of detecting unit 32 horizontal directions be more than 1 meter.
Implement the embodiment of the invention, because being based on the video human face image carries out the measurement of human body height, can be at the crowd of specific height in the access road, under the situation that does not change the existing access road facility of fixing, set in advance certain scope, convenient human body video image and the best facial image of screening gathered accurately, determine human body height by the position of best facial image in image, also can be in passage detects according to the purpose that people's face reaches the specific height crowd of screening in specific monitoring range image, whether occurring.Cost is measured flexibly and saved to the embodiment of the invention.
Above disclosed only is preferred embodiment of the present invention, can not limit the present invention's interest field certainly with this, and therefore the equivalent variations of doing according to claim of the present invention still belongs to the scope that the present invention is contained.
Claims (10)
1, a kind of height measuring method is characterized in that, described method comprises:
The human body position judges whether described position of human body enters preset range;
Be judged as is then to gather the human body video image;
From described human body video image, detect and the screening facial image;
Facial image by screening is determined human body height.
2, the method for claim 1 is characterized in that, also comprises before the described human body position:
Adopt a plurality of facial images that one neural network model is trained, reach best neural network performance, obtain the weights of described neural network model until described neural network model;
The standard heights human body is carried out the human body video image acquisition, from the human body video image of described collection, search out facial image, described facial image is imported described neural network model, and the output numerical value after described neural network model is handled compares, and obtains the standard faces image.
3, method as claimed in claim 2 is characterized in that, described detect from the human body video image and the screening facial image specifically comprises step:
Search possibility facial image from the human body video image of gathering;
The possible facial image of described search is imported described neural network model, and the output numerical value after described neural network model is handled compares;
Comparative result according to described output numerical value obtains best facial image.
4, the method for claim 1 is characterized in that, described facial image by screening determines that the step of human body height is specially:
The facial image of standard human body height and screening position and standard faces image ratio of position in entire image in entire image are multiplied each other, obtain human body height to be measured.
5, the method for claim 1 is characterized in that, during described collection human body video image, the angle on acquisition plane and plane, human body place is that 45 degree are to 90 degree.
6, a kind of height measurement mechanism is characterized in that, described device comprises:
Detecting unit is used to detect position of human body and judges whether described position of human body enters preset range;
Collecting unit is used for judged result collection and storage human body video image according to described detecting unit;
Processing unit is used for detecting and the screening facial image from the human body video image of described collecting unit storage;
Computing unit is used for calculating human body height according to the best facial image of described processing unit screening.
7, device as claimed in claim 6 is characterized in that, described device also comprises:
Training unit is used for described neural network model weights are trained and obtained to neural network model.
8, device as claimed in claim 6 is characterized in that, described collecting unit comprises:
Image unit is used to take the human body video image;
Storage unit is used for the human body video image that described image unit is taken is stored.
9, device as claimed in claim 6 is characterized in that, described processing unit comprises:
Search unit is used for carrying out the possibility face image searching according to the human body video image of described collection;
Comparing unit is used for the possible facial image of described search being imported described neural network model and the output numerical value after the described neural network model processing being compared;
Acquiring unit is used for obtaining best facial image according to the comparative result of described output numerical value.
10, device as claimed in claim 6 is characterized in that, described detecting unit is photoelectric sensor or ultrasonic detector.
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| CN102306404A (en) * | 2011-04-20 | 2012-01-04 | 铁道部运输局 | Method and device for checking tickets in safety area |
| CN102522054A (en) * | 2011-11-30 | 2012-06-27 | 苏州奇可思信息科技有限公司 | Content control method of public advertisement terminal based on body height identification |
| CN102697505A (en) * | 2012-04-19 | 2012-10-03 | 广州海特天高信息系统工程有限公司 | Height detecting instrument of automatic ticket checking machine |
| CN104257385B (en) * | 2014-10-16 | 2016-05-11 | 辽宁省颅面复原技术重点实验室 | The measuring method of Human Height in video image |
| CN104434113B (en) * | 2014-12-01 | 2016-09-21 | 江西洪都航空工业集团有限责任公司 | A kind of height measurement method |
| CN107280118B (en) * | 2016-03-30 | 2019-11-12 | 深圳市祈飞科技有限公司 | A kind of Human Height information acquisition method and the fitting cabinet system using this method |
| CN105956539B (en) * | 2016-04-27 | 2019-06-25 | 武汉大学 | A kind of Human Height measurement method of application background modeling and Binocular Vision Principle |
| CN106073786B (en) * | 2016-06-15 | 2020-12-18 | 四川谛达诺科技有限公司 | Height measuring device and measuring method |
| CN106295657A (en) * | 2016-08-04 | 2017-01-04 | 天津汉光祥云信息科技有限公司 | A kind of method extracting human height's feature during video data structure |
| CN109583276B (en) * | 2017-09-29 | 2020-12-15 | 大连恒锐科技股份有限公司 | CNN-based height determination method and system for barefoot or stocking foot footmark |
| CN108596042A (en) * | 2018-03-29 | 2018-09-28 | 青岛海尔智能技术研发有限公司 | Enabling control method and system |
| CN108596171A (en) * | 2018-03-29 | 2018-09-28 | 青岛海尔智能技术研发有限公司 | Enabling control method and system |
| CN109189226B (en) * | 2018-08-23 | 2022-03-04 | 凌宇科技（北京）有限公司 | Height calibration method and system |
| CN110895797B (en) * | 2019-04-04 | 2020-07-31 | 李雪梅 | Intelligent network transceiving platform |
| CN110672016A (en) * | 2019-09-12 | 2020-01-10 | 四川农业大学 | Cattle body size measuring system and method based on image recognition |
| CN113405505B (en) * | 2020-03-16 | 2022-09-16 | 同方威视技术股份有限公司 | Method and device for determining distance and height based on multiple sensors |
| CN111476820B (en) * | 2020-04-01 | 2023-11-03 | 深圳力维智联技术有限公司 | Method and device for positioning tracked target |
| CN115984970B (en) * | 2023-03-13 | 2023-08-18 | 浙江宇视科技有限公司 | Pedestrian height determining method and device, electronic equipment and storage medium |
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Address after: Guangdong Province, Guangzhou City, Luogang District Science City Ke Lin Lu No. 9 Patentee after: Guangdian Yuntong Financial Electronic Co., Ltd., Guangzhou Address before: Guangdong province Guangzhou city Whampoa road Xiping Yun Road No. 163 Patentee before: Guangdian Yuntong Financial Electronic Co., Ltd., Guangzhou |