CN109357679B - Indoor positioning method based on significance characteristic recognition - Google Patents
Indoor positioning method based on significance characteristic recognition Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
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Abstract
The invention provides an indoor positioning method based on saliency feature recognition, and relates to the technical field of saliency target detection, deep learning and indoor positioning. The problem that indoor GPS positioning signals are weak is solved, the influence caused by the motion of dynamic objects is eliminated, the real-time performance of a live-action image scene is guaranteed, the accuracy of image recognition is improved, and the accuracy of indoor positioning is improved.
Description
Technical Field
The invention relates to a saliency target detection, deep learning and indoor positioning technology, in particular to an indoor positioning method based on saliency feature recognition.
Background
With the development of strong applications such as accurate marketing and indoor navigation services, indoor positioning is more and more concerned, and a large number of application cases are available in various indoor scenes such as airports, railway stations, shopping malls, factories and schools. Indoor location refers to the position location in indoor environment, owing to receive the restriction of environment, utilizes the realization location that GPS sensor can relax at outdoor smart mobile phone, but gets into indoorly, and smart machine often just can't receive the GPS signal, hardly realizes accurate location.
At present, the traditional indoor mode in the industry adopts indoor wireless communication technologies such as WiFi, Bluetooth and RFID, the relative position is calculated by utilizing the base station for positioning and the signal intensity collected by a plurality of wireless transmitters, and finally the positioning of personnel or objects in the indoor space is realized. The construction that depends on infrastructure that traditional mode is very big, and the stability requirement to wiFi or bluetooth signal transmitter's signal strength is higher, especially in the intensive district of personnel's flow or the scene that dynamic object is more, can't guarantee the stability of its signal, causes the precision of indoor location and actual position to have very big deviation, can't satisfy actual application demand.
In recent years, with the development of deep learning and computer vision technology, the accuracy and speed of machine recognition images are greatly improved, and position location by analyzing live-action shot images becomes possible. Under the circumstances, how to effectively utilize the computer vision technology and combine a plurality of sensing technologies to realize accurate indoor positioning becomes a problem which needs to be solved urgently.
Disclosure of Invention
In order to solve the technical problems, the invention provides an indoor positioning method based on significance characteristic identification, which solves the problem of weak indoor GPS positioning signals and improves the indoor positioning precision.
The technical scheme of the invention is as follows:
an indoor positioning method based on saliency feature recognition is characterized by firstly completing indoor panoramic map modeling, extracting image saliency features by utilizing a computer vision technology, training, correcting and processing a large number of live-action images to form a model, and finally performing image matching by live-action shooting through intelligent equipment to extract spatial structure data so as to realize accurate positioning.
Acquiring an indoor panoramic image by using a high-definition camera, completing ranging by matching with point cloud data of a laser radar, performing salient feature recognition and image segmentation based on a panoramic map, correcting and processing live-action shot images of actual mobile shooting equipment in different time periods to form a panoramic positioning model rule base, compressing the model and the rule base, and placing the compressed model and the rule base into mobile intelligent equipment with a shooting function; the mobile intelligent equipment shoots a plurality of outdoor scenes in different directions at a fixed point, image matching is carried out, and image space structure information is extracted to carry out cross comparison positioning. In addition, the mobile intelligent device can also reduce the search range by means of wifi, Bluetooth and the like, and is mutually verified with the live-action image positioning. Wherein the content of the first and second substances,
the high-definition camera is used for collecting indoor panoramic image data, the laser radar is matched with the high-definition camera to take a picture, point cloud data are recorded, the distance between a shooting point and an object in the surrounding environment is determined, and positioning of the shooting point of the panoramic image is realized; the positioning and model rule base is obtained by utilizing image processing algorithm learning and analysis through computing resources gathered by a cloud center, and a mobile positioning App is formed and is put into the mobile intelligent equipment; the mobile intelligent equipment has a photographing function and certain computing capacity and can execute a mobile positioning App; the wifi and Bluetooth signal generator is in indoor wireless communication connection with wifi and Bluetooth.
The invention provides an indoor positioning method based on salient feature recognition, which is used for indoor positioning of mobile intelligent equipment and comprises the following steps:
101, the laser radar is matched with the high-definition camera to shoot panoramic photos indoors, point cloud data are collected by the laser radar, and the distance between a shooting point and an object in the surrounding environment is recorded in an identification mode;
102, uploading the collected image, point cloud data and distance data to a cloud end, preprocessing, and finishing data structuring;
103, performing superpixel segmentation on the panoramic image shot for multiple times to obtain an initial saliency map;
104, according to the panoramic data shot for multiple times, fully considering the change of the shielding relation and the dynamic object, and identifying a significant static object target;
105, fusing the segmented image and the characteristic region of the static object, and determining a saliency map region;
step 106, extracting spatial structure information and determining the position according to the image resolution and the shooting position by combining point cloud data ranging;
step 107, repeatedly executing the step 103 to the step 106 to finish the model and the rule base of the indoor panorama;
step 108, compressing the model and the rule base, combining with an indoor panoramic map to form a mobile positioning APP, and putting the mobile positioning APP into a cloud terminal;
step 109, downloading a mobile positioning APP from a cloud end by the mobile intelligent device;
step 110, the mobile intelligent device shoots a plurality of real scenes in different directions at a fixed point, and pre-processes the obtained picture, and extracts shooting metadata of the picture, wherein the shooting metadata comprises an aperture, a shutter, a focal length, pixels, shooting time and the like;
step 111, the mobile positioning APP of the (optional) mobile intelligent device can be connected with other positioning devices such as wifi and bluetooth to obtain a position range;
step 112, extracting image features by the mobile positioning APP of the mobile intelligent device, performing image matching, and determining the position of the panoramic image;
113, projecting the image on the panoramic image according to metadata of the shot image, extracting image space structure information for cross comparison and positioning, determining the position of the mobile intelligent equipment and performing label display through an App;
step 114, the mobile intelligent device corrects the marked position by using a mobile positioning APP, and uploads the shot images to the cloud;
and step 115, the cloud receives the data uploaded by the user, continuously optimizes the App identification positioning model of the user, and improves the positioning accuracy.
The invention has the advantages that
The invention realizes positioning by utilizing a computer vision technology, greatly solves the problem of weak indoor GPS positioning signals, eliminates the influence generated by the motion of dynamic objects, can realize indoor positioning with higher precision, and is suitable for various application scenes; the searching range is reduced by means of wifi, Bluetooth and the like, the matching speed is increased, and the method and the device are mutually verified in positioning with live-action images. In addition, the effective utilization removes APP and continuously collects the outdoor scene data and revises the location, has guaranteed the real-time of outdoor scene image scene, has promoted image identification's accuracy, and then improves the precision of indoor location.
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FIG. 1 is a schematic diagram of an indoor positioning system;
fig. 2 is a flow chart of indoor positioning of a mobile smart device.
Detailed Description
The invention will be explained in more detail below with reference to the accompanying drawings:
as shown in fig. 1, a high-definition camera is used for collecting indoor panoramic images, the distance measurement is completed by matching with point cloud data of a laser radar, the identification of salient features and the image segmentation are performed based on a panoramic map, the real-scene shot images of actual mobile shooting equipment in different time periods are corrected and processed to form a panoramic positioning model rule base, and the model and the rule base are compressed and placed into mobile intelligent equipment with a shooting function; the mobile intelligent equipment shoots a plurality of outdoor scenes in different directions at a fixed point, image matching is carried out, and image space structure information is extracted to carry out cross comparison positioning. In addition, the mobile intelligent device can also reduce the search range by means of wifi, Bluetooth and the like, and is mutually verified with the live-action image positioning.
Wherein the content of the first and second substances,
the high-definition camera is used for collecting indoor panoramic image data, the laser radar is matched with the high-definition camera to take a picture, point cloud data are recorded, the distance between a shooting point and an object in the surrounding environment is determined, and positioning of the shooting point of the panoramic image is realized;
the positioning and model rule base is obtained by utilizing image processing algorithm learning and analysis through computing resources gathered by a cloud center, and a mobile positioning App is formed and is put into the mobile intelligent equipment;
the mobile intelligent equipment has a photographing function and certain computing capacity and can execute a mobile positioning App; the wifi and Bluetooth signal generator is in indoor wireless communication connection with wifi and Bluetooth.
For clarity of description, the image feature recognition algorithm in the following examples adopts R-CNN, the saliency target detection algorithm adopts SLRC algorithm, and the feature extraction adopts HOG + SVM algorithm. Those skilled in the art will appreciate that the configurations according to embodiments of the present invention can be applied to other algorithms in addition to using the above algorithm.
As illustrated in fig. 2, indoor positioning of a mobile smart device comprises the steps of:
101, the laser radar is matched with the high-definition camera to shoot panoramic photos indoors, point cloud data are collected by the laser radar, and the distance between a shooting point and an object in the surrounding environment is recorded in an identification mode;
102, uploading the collected image, point cloud data and distance data to a cloud end, preprocessing, and finishing data structuring;
103, performing superpixel segmentation on the panoramic image shot for multiple times to obtain an initial saliency map;
104, according to the panoramic data shot for multiple times, fully considering the change of the shielding relation and the dynamic object, and identifying a significant static object target;
105, fusing the segmented image and the characteristic region of the static object, and determining a saliency map region;
step 106, extracting spatial structure information and determining the position according to the image resolution and the shooting position by combining point cloud data ranging;
step 107, repeatedly executing the step 103 to the step 106 to finish the model and the rule base of the indoor panorama;
step 108, compressing the model and the rule base, combining with an indoor panoramic map to form a mobile positioning APP, and putting the mobile positioning APP into a cloud terminal;
step 109, downloading a mobile positioning APP from a cloud end by the mobile intelligent device;
step 110, the mobile intelligent device shoots a plurality of real scenes in different directions at a fixed point, and pre-processes the obtained picture, and extracts shooting metadata of the picture, wherein the shooting metadata comprises an aperture, a shutter, a focal length, pixels, shooting time and the like;
step 111, the mobile positioning APP of the mobile intelligent device can be connected with other positioning devices such as wifi and Bluetooth to obtain a position range;
step 112, extracting image features by the mobile positioning APP of the mobile intelligent device, performing image matching, and determining the position of the panoramic image;
113, projecting the image on the panoramic image according to metadata of the shot image, extracting image space structure information for cross comparison and positioning, determining the position of the mobile intelligent equipment and performing label display through an App;
step 114, the mobile intelligent device corrects the marked position by using a mobile positioning APP, and uploads the shot images to the cloud;
and step 115, the cloud receives the data uploaded by the user, continuously optimizes the App identification positioning model of the user, and improves the positioning accuracy.
The above-described embodiment is only one specific embodiment of the present invention, and general changes and substitutions by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention.
Claims (8)
1. An indoor positioning method based on the identification of the significant features is characterized in that,
firstly, modeling an indoor panoramic map, extracting image significance characteristics by using a computer vision technology, training, correcting and processing live-action images to form a model, and finally performing image matching by live-action shooting through intelligent equipment to extract spatial structure data so as to realize accurate positioning;
the method comprises the following specific operation steps:
step 101, a laser radar is matched with a high-definition camera to shoot panoramic photos indoors, the laser radar collects point cloud data, and the distance between a shooting point and objects in the surrounding environment is recorded in an identification mode;
102, uploading the collected image, point cloud data and distance data to a cloud end, preprocessing, and finishing data structuring;
103, performing superpixel segmentation on the panoramic image shot for multiple times to obtain an initial saliency map;
104, according to the panoramic data shot for multiple times, fully considering the change of the shielding relation and the dynamic object, and identifying a significant static object target;
105, fusing the segmented image and the characteristic region of the static object, and determining a saliency map region;
step 106, extracting spatial structure information and determining the position according to the image resolution and the shooting position by combining point cloud data ranging;
step 107, repeatedly executing the step 103 to the step 106 to finish the model and the rule base of the indoor panorama;
step 108, compressing the model and the rule base, combining with an indoor panoramic map to form a mobile positioning APP, and putting the mobile positioning APP into a cloud terminal;
step 109, downloading a mobile positioning APP from a cloud end by the mobile intelligent device;
step 110, the mobile intelligent device shoots a plurality of real scenes in different directions at a fixed point, and pre-processes the obtained picture, and extracts shooting metadata of the picture, wherein the shooting metadata comprises an aperture, a shutter, a focal length, pixels, shooting time and the like;
step 111, extracting image features by the mobile positioning APP of the mobile intelligent device, performing image matching, and determining the position of the panoramic image;
step 112, projecting the image on the panoramic image according to the metadata of the shot image, extracting image space structure information for cross comparison and positioning, determining the position of the mobile intelligent device and performing label display through an App;
step 113, the mobile intelligent equipment corrects the marked position by using a mobile positioning APP, and uploads the shot images to the cloud;
and step 114, the cloud receives the data uploaded by the user, continuously optimizes the App identification positioning model of the user, and improves the positioning precision.
2. The method of claim 1,
collecting an indoor panoramic image, completing ranging by matching point cloud data of a laser radar, performing salient feature recognition and image segmentation based on a panoramic map, correcting and processing live-action shot images of actual mobile shooting equipment in different time periods to form a panoramic positioning model rule base, compressing the model and the rule base, and placing the compressed model and the rule base into mobile intelligent equipment with a shooting function; the mobile intelligent equipment shoots a plurality of outdoor scenes in different directions at a fixed point, image matching is carried out, and image space structure information is extracted to carry out cross comparison positioning.
3. The method of claim 2,
in addition, the mobile intelligent device can also narrow the search range by means of wifi and Bluetooth and perform mutual verification with live-action image positioning.
4. The method of claim 2,
the high-definition camera is used for collecting indoor panoramic image data, the laser radar is matched with the high-definition camera to shoot, point cloud data are recorded, the distance between a shooting point and an object in the surrounding environment is determined, and positioning of the shooting point of the panoramic image is achieved.
5. The method of claim 2,
the positioning and model rule base is obtained by utilizing image processing algorithm learning and analysis through computing resources gathered by the cloud center, and a mobile positioning App is formed and is placed into the mobile intelligent device.
6. The method of claim 2,
the mobile intelligent device has a photographing function and computing capability and can execute the mobile positioning App.
7. The method of claim 3,
the wifi and Bluetooth signal generator is in indoor wireless communication connection with wifi and Bluetooth.
8. The method of claim 1,
the mobile positioning APP of the mobile intelligent device can be connected with wifi and Bluetooth to obtain a position range.
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| CN110298320B (en) * | 2019-07-01 | 2021-06-22 | 北京百度网讯科技有限公司 | Visual positioning method, device and storage medium |
| CN110427936B (en) * | 2019-07-04 | 2022-09-30 | 深圳市新潮酒窖文化传播有限公司 | Wine storage management method and system for wine cellar |
| CN112242002B (en) * | 2020-10-09 | 2022-07-08 | 同济大学 | Object identification and panoramic roaming method based on deep learning |
| CN113137963B (en) * | 2021-04-06 | 2023-05-05 | 上海电科智能系统股份有限公司 | High-precision comprehensive positioning and navigation method for passive indoor people and objects |
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