CN108984643A - A kind of sports center extracting method based on GPS track data of jogging - Google Patents
A kind of sports center extracting method based on GPS track data of jogging Download PDFInfo
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Abstract
The invention discloses a kind of sports center extracting methods based on GPS track data of jogging, method includes the following steps: step 1, obtaining original GPS track line number evidence of jogging from database, original GPS track line number evidence of jogging is decomposed into two-dimensional time sequence curve data, and crucial point set is extracted to two-dimensional time sequence curve data；Step 2, the building sub-trajectory of the track point set according to corresponding to crucial point set are searched the pitch of the laps sub-trajectory for meeting pitch of the laps trajectory model feature by row scanning search matrix apart from upper triangular matrix；In ergodic data library after all GPS track lines, output group circlees trajectory line collection；Step 3 concentrates the geological information and semantic information for extracting sports center from group's pitch of the laps trajectory line.The present invention can quickly and automatically extract pitch of the laps sports center information of jogging on semantic hierarchies, reduce fine playground acquisition of information cost, and this method is simple, is easily achieved.
Description
Technical field
The present invention relates to geography information and space-time trajectory data digging technology field, more particularly to one kind is based on the GPS that jogs
The sports center extracting method of track data.
Background technique
It is influenced by nationwide fitness programs trend, people's health consciousness is increasingly enhanced, more and more people's weight in daily life
Depending on taking exercises, the life idea that health is pursued by motion exercise has been rooted in the hearts of the people.Jogging as sport and body-building, stop
The important way of spare time amusement, for build up health, lose weight prevent it is fat, relieve stress etc. and to play a significant role.Pitch of the laps is jogged as slow
The main behavior in movement is run, pitch of the laps behavior pattern is accurately identified and extracts pitch of the laps sports center informative is great.It is how fast
Speed accurately obtains jogging Locale information (geological information and semantic information) in city, and is place recommendation of jogging, slow
Path planning is run, the offer decisions such as friend's recommendation are provided and suggests it being the research topic with high value of practical.Traditional field
Institute's information extracting method includes artificial field investigation measurement and remote sensing technology.Manual research measurement method is at high cost, the update cycle
It is long, it is difficult to meet practical application request.High score remote sensing image technology is mostly used to extract urban land use data, monitoring soil benefit
With covering variation etc., but this method cannot extract the Locale information of specific mankind's activity (such as jog, ride), and it is even more impossible to perceive people
Class crawler behavior dynamic change and playground characteristic information.
Currently, the extensive use of the software and hardwares such as running fix equipment (GPS, bracelet), movement App (thud, happy run about circle), produces
The outdoor activity track data (jog, ride) with individual mark, movement properties data (energy consumption, the heart of magnanimity are given birth to
Rate etc.).The behavioral data of these high-spatial and temporal resolutions helps to excavate between mankind's activity behavior pattern, analysis place and behavior
Coupled relation, perception playground feature, monitoring health variation.Space-time trajectory has low cost, high Up-to-date state, high space-time
The advantages that resolution ratio, big data, ubiquitous crowd-sourced, and it is widely used in the extraction of city relevant information.Specifically include that road is believed
Cease extraction, city analysis of central issue, human behavioral mode detection, Spatial data capture and update etc..But society is used in existing research more
Hand over the detection such as media data, mobile phone communication data, taxi GPS track data land use pattern, identification urban function region.This
It is a little to study mostly using traffic zone as the land used semantics recognition of unit, and for the playground information extraction under human behavior visual angle
It studies less.By analyzing existing correlative study discovery, the mankind are extracted with GPS track data and are jogged pitch of the laps sports center letter
Breath is still a research blank.
Summary of the invention
The technical problem to be solved in the present invention is that for the defects in the prior art, providing a kind of based on GPS rail of jogging
The sports center extracting method of mark data.
The technical solution adopted by the present invention to solve the technical problems is:
The present invention provides a kind of sports center extracting method based on GPS track data of jogging, and this method includes following step
It is rapid:
Step 1 obtains original GPS track line number evidence of jogging from database, by original GPS track line number of jogging according to decomposition
For two-dimensional time sequence curve data, and crucial point set is extracted to two-dimensional time sequence curve data；
Step 2, the building sub-trajectory of the track point set according to corresponding to crucial point set are scanned apart from upper triangular matrix, and by row
Searching matrix searches the pitch of the laps sub-trajectory for meeting pitch of the laps trajectory model feature；In ergodic data library after all GPS track lines, output
Group circlees trajectory line collection；
Step 3 concentrates the geological information and semantic information for extracting sports center from group's pitch of the laps trajectory line.
Further, step 1 of the invention method particularly includes:
Step 1.1 determines parameter threshold, comprising: shortest path distance, maximum direction distance, time minimum period；
One step 1.2, input original GPS track line number evidence of jogging, by original space-time trajectory line coordinates (x, y, t) point
Solution is the two-dimensional time sequence curve data of (t, x), (t, y)；
Step 1.3, the starting point using in two-dimensional time sequence data, terminal, maximum and minimum point are as key point；It will
(t, x), the set of keypoints extracted in (t, y) sequence simultaneously, obtain all key point set KP={ k1, k2..., kn}；According to when
Between sequentially extract lookup point set SP={ s of the corresponding initial trace point of key point as pitch of the laps behavior sub-trajectory1, s2...,
sn}。
Further, the parameter threshold determined in step 1.1 of the invention specifically:
Shortest path distance minPath=400m, maximum direction distance maxDirct=16m, time minimum period
MinTime=5min.
Further, the method for extreme point is chosen in step 1.3 of the invention specifically:
For continuous three point sequences (xi-1, xi, xi+1), if point xiMeet { xi< xi-1&&xi< xi+1Or { xi> xi-1&&
xi> xi+1It is then Local Extremum；Extreme point xiIt the period for keeping extreme value, i.e. the period of the point and front and back extreme point, answers
Time minimum period is indicated greater than minTime/4, minTime；Otherwise the point is deleted as redundancy key point.
Further, step 2 of the invention method particularly includes:
Step 2.1, sequentially in time using SP point set obtained in step 1.3 as ranks construct trajectory distance on three angular moments
Battle array, each matrix unit record the ranks and correspond to the path distance (pathDist) for the sub-trajectory that tracing point is constituted, direction distance
(dirDist) and pitch of the laps duration (Tdur)；For arbitrary trajectory line T={ pn, pn+1..., pm, trajectory path distance, direction
The calculation formula such as distance, duration are as follows:
DirDist (T)=Dist (pn, pm)
Tdur=T (pm)-T(pn)
Wherein, Dist (pk, pk+1) indicate two tracing points Euclidean distance, T (pk) indicate tracing point pkThe time of record；
Step 2.2 is searched for trajectory distance upper triangular matrix by row, if 3 characteristic values in matrix unit all meet
Pitch of the laps action trail feature, that is, meet condition:
{pathDist≥minPath&&dirDist≤maxDirct&&Tdur≥minTime}
Then the corresponding sub-trajectory of the ranks is pitch of the laps sub-trajectory, and presses row successively with the row matrix where the sub-trajectory terminal
Search for pitch of the laps sub-trajectory；If searching pitch of the laps sub-trajectory, repeats step 2.2 and carry out depth-first search；Until nothing
Pitch of the laps sub-trajectory, the trajectory line are disposed, then export pitch of the laps behavior sub-trajectory；
Step 2.3 repeats step 2.1- step 2.2 and traverses all GPS track lines, finally obtains group's pitch of the laps behavior
Trajectory line collection.
Further, in step 3 of the invention using Delaunay triangulation network and anti-address code method from group around
It encloses trajectory line and concentrates the geological information and semantic information for extracting sports center.
Further, step 3 of the invention method particularly includes:
Step 3.1, the group's pitch of the laps trajectory line collection building constraint Delaunay triangulation network extracted to step 2.3, are deleted
Whole long side in Delaunay triangulation network then gathers the pitch of the laps trajectory line of each sports center for one kind；Whole long edge contract
Threshold value Globalalue calculates as follows:
GlobalValue=Mean (DT)+α × Variation (DT)
Wherein, Mean (DT) indicates all side length average values of triangulation network DT；Variation (DT) indicates all sides of the triangulation network
Long standard deviation；α is adjustment parameter, is defaulted as 1；Arbitrary triangle side is deleted if side length is greater than GlobalValue
The side；
Step 3.2 after deleting clustering cluster obtained in step 3.1 local long side again, merges three to each clustering cluster
Angular extraction polygon, and to Simplifying Polygons to obtain motion path polygon；The long edge contract threshold value LocalValue in part
It calculates as follows:
Wherein,Indicate clustering cluster GiMidpoint pjSecond order neighborhood in all side length mean values；
LocalVariation(pj) indicate clustering cluster GiIn with point pjIt is directly connected to the side length standard deviation on side；β is adjustment parameter, default
It is 2；
To extract pitch of the laps place polygon, then step 3.3 deletes the path polygon extracted in step 3.2 inner ring
Pitch of the laps sports center semantic information is extracted using the reversed address code of Baidu, semantic type includes: stadium, residence district, public affairs
Garden, road, lake greenery patches, leisure greenery patches, greenery patches square.
Further, recording in the database of step 1 of the invention has: the magnanimity that running fix equipment, movement APP are generated
GPS track line number evidence of jogging with individual mark.
The beneficial effect comprise that: the sports center extracting method of the invention based on GPS track data of jogging,
By carrying out excavation processing to GPS track data of jogging, one kind is constructed and has obtained sports center letter from GPS track data of jogging
The method of breath；This method can rapidly from magnanimity jog identification in GPS track line, extract pitch of the laps behavior sub-trajectory, and in semanteme
Jogging Locale information is extracted with group's pitch of the laps trajectory line collection on level, has filled up jogging place Study on Extraction Method
Blank；Meanwhile the invention reduces sports center information extraction cost using crowd-sourced GPS track as data source, and detects and extract
Method is simple, is easily achieved.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the flow chart of the embodiment of the present invention；
Fig. 2 is that the time-serial position key point set of the embodiment of the present invention extracts schematic diagram, and wherein Fig. 2 (a) is original GPS
Trajectory line is decomposed into two-dimensional time sequence data schematic diagram, and Fig. 2 (b) is that sequence data key point set extracts schematic diagram；
Fig. 3 is the building of trajectory distance matrix and trajectory distance matrix search pitch of the laps behavior sub-trajectory original of the embodiment of the present invention
Reason figure；
Fig. 4 be the embodiment of the present invention group jog pitch of the laps action trail extract result schematic diagram；
Fig. 5 is that the constraint Delaunay triangulation network of the embodiment of the present invention extracts sports center schematic diagram, and wherein Fig. 5 (a) is
Group's pitch of the laps trajectory line collection constructs Delaunay triangulation network schematic diagram, and Fig. 5 (b) is to delete whole long side to cluster trajectory line signal
Figure；
Fig. 6 is the sports center information extraction schematic diagram of the embodiment of the present invention and as a result, wherein Fig. 6 (a) is extraction pitch of the laps
Sports center path polygon schematic diagram, Fig. 6 (b) are to extract jogging place polygon and place semantic information schematic diagram.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
As shown in Figure 1, the sports center extracting method based on GPS track data of jogging of the embodiment of the present invention, including with
Lower step:
Step 1: as shown in Fig. 2, original GPS track line latitude and longitude coordinates of jogging are decomposed into (t, x), the time of (t, y)
Sequence data, and crucial point set is extracted to time-serial position；
Step 1.1: determining parameter threshold: minimal path distance minPath=400m, maximum direction distance maxDirct=
16m, time minimum period minTime=5min；
Step 1.2: as shown in Fig. 2 (a), input a GPS track line of jogging, by original space-time trajectory line coordinates (x, y,
T) the two-dimensional time sequence data of (t, x), (t, y) are decomposed into；
Step 1.3: as shown in Fig. 2 (b), using starting point, terminal, maximum and the minimum point in time series data as
Key point.For continuous three point sequences (xi-1, xi, xi+1), if point xiMeet { xi< xi-1&&xi< xi+1Or { xi> xi-1&&
xi> xi+1It is then Local Extremum.Extreme point xiKept for the period (i.e. the period of the point and front and back extreme point) of extreme value answer
Greater than minTime/4, otherwise the point is as redundancy key point deletion.By (t, x), the set of keypoints extracted in (t, y) sequence
And obtain all key point set KP={ k1, k2..., kn}.The corresponding initial trace point of key point is extracted sequentially in time to make
For the lookup point set SP={ s of pitch of the laps behavior sub-trajectory1, s2..., sn, as a result as shown in Fig. 2 (b)；
Step 2: the crucial point set extracted according to step 1.3 constructs sub-trajectory to track point set corresponding to crucial point set
Apart from upper triangular matrix, and the pitch of the laps sub-trajectory for meeting pitch of the laps trajectory model feature is searched by row scanning search matrix；Traverse number
After GPS track lines all in library, output group circlees trajectory line collection；
Step 2.1: as shown in figure 3, sequentially in time using SP point set obtained in step 1.3 as ranks construct track away from
From upper triangular matrix, each matrix unit records the path distance that the ranks correspond to the sub-trajectory of tracing point composition
(pathDist), direction distance (dirDist) and pitch of the laps duration (Tdur).For arbitrary trajectory line T={ pn, pn+1..., pm,
The calculation formula such as its trajectory path distance, direction distance, duration are as follows:
DirDist (T)=Dist (pn, pm)
Tdur=T (pm)-T(pn)
Dist (p in above formulak, pk+1) indicate two tracing points Euclidean distance, T (pk) indicate tracing point pkThe time of record；
Step 2.2: as shown in figure 3, being searched for trajectory distance matrix by rows, if 3 characteristic values in matrix unit are all
Meet pitch of the laps action trail feature, that is, meet condition:
{pathDist≥minPath&&dirDist≤maxDirct&&Tdur≥minTime}
Then the corresponding sub-trajectory of the ranks is pitch of the laps sub-trajectory, and presses row successively with the row matrix where the sub-trajectory terminal
Search for pitch of the laps sub-trajectory.If searching pitch of the laps sub-trajectory, by above-mentioned steps depth-first search.Until without rail of circling
Mark, the trajectory line are disposed, and export pitch of the laps behavior sub-trajectory；
Step 2.3: it repeats the above steps and traverses all GPS track lines, finally obtain group's pitch of the laps action trail line collection,
Group jog pitch of the laps trajectory line collection extract result it is as shown in Figure 4；
Step 3: as shown in Figure 5, Figure 6, being extracted with the methods of Delaunay triangulation network, anti-address code from step 2
Group's pitch of the laps trajectory line, which is concentrated, extracts sports center geological information and semantic information.
Step 3.1: as shown in Fig. 5 (a), Fig. 5 (b), constraint being constructed to group's pitch of the laps trajectory line collection that step 2.3 is extracted
Delaunay triangulation network is deleted the whole long side in Delaunay triangulation network, is then gathered the pitch of the laps trajectory line of each sports center
For one kind.Whole long edge contract threshold value GlobalValue calculates as follows:
GlobalValue=Mean (DT)+α × Variation (DT)
Mean (DT) indicates all side length average values of triangulation network DT in above formula；Variation (DT) indicates that the triangulation network is all
Side length standard deviation；α is adjustment parameter, is defaulted as 1.GlobalValue is greater than for arbitrary triangle side such as side length, then deleting should
Side, shown in the result such as Fig. 6 (b) for deleting whole long side；
Step 3.2: as shown in Fig. 6 (a), after deleting clustering cluster obtained in step 3.1 local long side again, to each
Clustering cluster merges triangle and extracts polygon, and to Simplifying Polygons to obtain motion path polygon.The long edge contract threshold in part
Value LocalValue calculates as follows:
In above formulaIndicate clustering cluster GiMidpoint pjSecond order neighborhood in all side length mean values；
LocalVariation(pj) indicate clustering cluster GiIn with point pjIt is directly connected to the side length standard deviation on side；β is adjustment parameter, default
It is 2；
Step 3.3: as shown in Fig. 6 (b), inner ring being deleted to extract pitch of the laps field to the path polygon extracted in step 3.2
Then institute's polygon extracts pitch of the laps sports center semantic information using the reversed address code of Baidu, mainly include stadium, life
The semantic types such as cell, park, road, lake greenery patches, leisure greenery patches, greenery patches square.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (8)
1. a kind of sports center extracting method based on GPS track data of jogging, which is characterized in that this method includes following step
It is rapid:
Step 1 obtains original GPS track line number evidence of jogging from database, and original GPS track line number evidence of jogging is decomposed into two
Time-serial position data are tieed up, and crucial point set is extracted to two-dimensional time sequence curve data；
Step 2, the building sub-trajectory of the track point set according to corresponding to crucial point set press row scanning search apart from upper triangular matrix
Matrix searches the pitch of the laps sub-trajectory for meeting pitch of the laps trajectory model feature；In ergodic data library after all GPS track lines, group is exported
Trajectory line of circling collection；
Step 3 concentrates the geological information and semantic information for extracting sports center from group's pitch of the laps trajectory line.
2. the sports center extracting method according to claim 1 based on GPS track data of jogging, which is characterized in that step
Rapid 1 method particularly includes:
Step 1.1 determines parameter threshold, comprising: shortest path distance, maximum direction distance, time minimum period；
One step 1.2, input original GPS track line number evidence of jogging, original space-time trajectory line coordinates (x, y, t) is decomposed into
The two-dimensional time sequence curve data of (t, x), (t, y)；
Step 1.3, the starting point using in two-dimensional time sequence data, terminal, maximum and minimum point are as key point；Will (t,
X), the set of keypoints extracted in (t, y) sequence simultaneously, obtains all key point set KP={ k1, k2..., kn}；It is suitable according to the time
Sequence extracts lookup point set SP={ s of the corresponding initial trace point of key point as pitch of the laps behavior sub-trajectory1, s2..., sn}。
3. the sports center extracting method according to claim 2 based on GPS track data of jogging, which is characterized in that step
The parameter threshold determined in rapid 1.1 specifically:
Shortest path distance minPath=400m, maximum direction distance maxDirct=16m, time minimum period minTime=
5min。
4. the sports center extracting method according to claim 2 based on GPS track data of jogging, which is characterized in that step
The method of extreme point is chosen in rapid 1.3 specifically:
For continuous three point sequences (xi-1, xi, xi+1), if point xiMeet { xi< xi-1&&xi< xi+1Or { xi> xi-1&&xi>
xi+1It is then Local Extremum；Extreme point xiIt the period for keeping extreme value, i.e. the period of the point and front and back extreme point, should be greater than
MinTime/4, minTime indicate time minimum period；Otherwise the point is deleted as redundancy key point.
5. the sports center extracting method according to claim 2 based on GPS track data of jogging, which is characterized in that step
Rapid 2 method particularly includes:
Step 2.1, sequentially in time using SP point set obtained in step 1.3 as ranks construct trajectory distance upper triangular matrix,
Each matrix unit records the ranks and corresponds to the path distance (pathDist) for the sub-trajectory that tracing point is constituted, direction distance
(dirDist) and pitch of the laps duration (Tdur)；For arbitrary trajectory line T={ pn, pn+1..., pm, trajectory path distance, direction
The calculation formula such as distance, duration are as follows:
DirDist (T)=Dist (pn, pm)
Tdur=T (pm)-T(pn)
Wherein, Dist (pk, pk+1) indicate two tracing points Euclidean distance, T (pk) indicate tracing point pkThe time of record；
Step 2.2 is searched for trajectory distance upper triangular matrix by row, if 3 characteristic values in matrix unit all meet pitch of the laps
Action trail feature, that is, meet condition:
{pathDist≥minPath&&dirDist≤maxDirct&&Tdur≥minTime}
Then the corresponding sub-trajectory of the ranks is pitch of the laps sub-trajectory, and is successively searched for the row matrix where the sub-trajectory terminal by row
Pitch of the laps sub-trajectory；If searching pitch of the laps sub-trajectory, repeats step 2.2 and carry out depth-first search；Until no pitch of the laps
Sub-trajectory, the trajectory line are disposed, then export pitch of the laps behavior sub-trajectory；
Step 2.3 repeats step 2.1- step 2.2 and traverses all GPS track lines, finally obtains group's pitch of the laps action trail
Line collection.
6. the sports center extracting method according to claim 1 based on GPS track data of jogging, which is characterized in that step
It is concentrated using Delaunay triangulation network and the method for anti-address code from group's pitch of the laps trajectory line in rapid 3 and extracts the several of sports center
What information and semantic information.
7. the sports center extracting method according to claim 5 based on GPS track data of jogging, which is characterized in that step
Rapid 3 method particularly includes:
Step 3.1, the group's pitch of the laps trajectory line collection building constraint Delaunay triangulation network extracted to step 2.3, are deleted
Whole long side in Delaunay triangulation network then gathers the pitch of the laps trajectory line of each sports center for one kind；Whole long edge contract
Threshold value Globalalue calculates as follows:
GlobalValue=Mean (DT)+α × Variation (DT)
Wherein, Mean (DT) indicates all side length average values of triangulation network DT；Variation (DT) indicates all side length marks of the triangulation network
It is quasi- poor；α is adjustment parameter, is defaulted as 1；The side is deleted if side length is greater than GlobalValue for arbitrary triangle side；
Step 3.2 after deleting clustering cluster obtained in step 3.1 local long side again, merges triangle to each clustering cluster
Polygon is extracted, and to Simplifying Polygons to obtain motion path polygon；The long edge contract threshold value LocalValue in part is calculated
It is as follows:
Wherein,Indicate clustering cluster GiMidpoint pjSecond order neighborhood in all side length mean values；LocalVariation
(pj) indicate clustering cluster GiIn with point pjIt is directly connected to the side length standard deviation on side；β is adjustment parameter, is defaulted as 2；
Step 3.3 deletes the path polygon extracted in step 3.2 inner ring to extract pitch of the laps place polygon, then utilizes
The reversed address code of Baidu extracts pitch of the laps sports center semantic information, and semantic type includes: stadium, residence district, park, road
Road, lake greenery patches, leisure greenery patches, greenery patches square.
8. the sports center extracting method according to claim 1 based on GPS track data of jogging, which is characterized in that step
There is record in rapid 1 database: the magnanimity that running fix equipment, movement APP are generated has the GPS track line of jogging of individual mark
Data.
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