CN112560689B - Parking space detection method and device, electronic equipment and storage medium - Google Patents
Parking space detection method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a parking space detection method, a parking space detection device, electronic equipment and a storage medium; the method comprises the following steps: acquiring a visual parking space; matching the visual parking space with a preset parking space tracking list; updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces; and outputting the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value. By the method and the device, the reliability of the fusion parking space is improved, and the accurate detection of the parking space is realized.
Description
Technical Field
The invention relates to the technical field of parking space detection, in particular to a parking space detection method, a device, electronic equipment and a storage medium.
Background
The automatic parking refers to automatic parking of the automobile through an automatic parking system, and manual control is not needed.
Different automatic parking systems employ different methods for detecting objects around the vehicle. Some have sensors around the front and rear bumpers that can act as both transmitters and receivers. These sensors transmit signals that are reflected back when they hit an obstacle around the vehicle body. The computer on the vehicle then uses the time it takes to receive the signal to determine the location of the obstacle. Other systems use cameras or radar mounted on the bumper to detect obstructions. But the end result is the same: the car detects the size of the parked vehicle, the parking space, and the distance from the roadside, and then drives the vehicle into the parking space.
However, in the process of finding a parking space from far to near, the detection accuracy of the parking space detection model on the parking space can be improved along with the reduction of the distance, and the positioning of the parking space by the parking space images acquired by the parking space detection model at different stages may have slight deviation.
Disclosure of Invention
The invention provides a parking space detection method, a device, electronic equipment and a storage medium, which are used for solving or partially solving the technical problem that the accuracy rate of a fusion parking space is low due to the fact that parking space images acquired at different stages are affected.
The invention provides a parking space detection method, which comprises the following steps:
acquiring a visual parking space;
Matching the visual parking space with a preset parking space tracking list;
updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces;
And outputting the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value.
Optionally, the step of obtaining the visual parking space includes:
detecting an initial visual parking space through a preset parking space detection model;
Determining the size and shape of the initial vision parking space;
and obtaining an initial visual parking space with the size and shape meeting the preset parking space standard as a visual parking space.
Optionally, the first confidence level includes a first match confidence level and a first no match confidence level; and updating the fusion parking spaces in the parking space tracking list according to the matching result, and before the step of obtaining the first confidence coefficient of the fusion parking spaces, further comprising:
Determining the sending stage of the visual parking space, and acquiring a second confidence coefficient of each corner point of the visual parking space;
obtaining a confidence coefficient attenuation rate corresponding to the sending stage;
Acquiring the current confidence coefficient of each corner point of the fusion parking space;
and updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces, wherein the step comprises the following steps:
when the matching result is that the matching parking spaces and the unmatched parking spaces exist in the parking space tracking list, calculating a first matching confidence coefficient of each corner point of the matching parking spaces by adopting the second confidence coefficient, the confidence coefficient attenuation rate and the current confidence coefficient;
And calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
Optionally, the first confidence level further includes a second unmatched confidence level; updating the fusion parking space in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking space, and further comprising:
and when the matching result is that only the unmatched parking spaces exist in the parking space tracking list, calculating second unmatched confidence coefficients of all angular points of the unmatched parking spaces by adopting the second confidence coefficients and the confidence coefficient attenuation rates.
Optionally, after the step of updating the fused parking space in the parking space tracking list according to the matching result to obtain the first confidence coefficient of the fused parking space, the method further includes:
Acquiring the current angular point position of the fusion parking space and the first angular point position of the vision parking space;
Calculating the updating weight of the corner points of the matched parking spaces by adopting the first confidence coefficient and the second confidence coefficient of the corner points of the fused parking spaces;
and calculating a second angular point position of the fusion parking space by adopting the updating weight, the current angular point position and the first angular point position.
Optionally, when the distance between the vehicle and the fused parking space meets a preset distance condition and the first confidence coefficient is greater than a preset threshold, the step of outputting the fused parking space includes:
When the distance between the vehicle and the fusion parking space meets the preset distance condition, and the first confidence coefficient of each corner point of the fusion parking space is larger than a preset threshold value, outputting the fusion parking space and the second corner point position of the fusion parking space.
Optionally, the method further comprises:
And when the matching result is that only unmatched parking spaces exist in the parking space tracking list, adding the visual parking spaces to the parking space tracking list.
The invention also provides a parking space detection device, which comprises:
the visual parking space acquisition module is used for acquiring a visual parking space;
the matching module is used for matching the visual parking space with a preset parking space tracking list;
the first confidence updating module is used for updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain the first confidence of the fusion parking spaces;
And the fusion parking space output module is used for outputting the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value.
Optionally, the first confidence level includes a first match confidence level and a first no match confidence level; the apparatus further comprises:
The second confidence coefficient determining module is used for determining the sending stage of the visual parking space and acquiring the second confidence coefficient of each corner point of the visual parking space;
the confidence coefficient attenuation rate determining module is used for obtaining the confidence coefficient attenuation rate corresponding to the sending stage;
the current confidence coefficient determining module is used for obtaining the current confidence coefficient of each corner point of the fusion parking space;
the first confidence updating module includes:
The first matching confidence calculation submodule is used for calculating the first matching confidence of each angular point of the matching parking space by adopting the second confidence, the confidence attenuation rate and the current confidence when the matching result is that the matching parking space and the unmatched parking space exist in the parking space tracking list;
And the first unmatched confidence coefficient calculating sub-module is used for calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
Optionally, the first confidence level further includes a second unmatched confidence level; the first confidence updating module further includes:
And the second unmatched confidence coefficient calculating submodule is used for calculating the second unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate when the matching result is that only the unmatched parking space exists in the parking space tracking list.
The invention also provides an electronic device comprising a processor and a memory:
The memory is used for storing program codes and transmitting the program codes to the processor;
The processor is configured to execute the parking space detection method according to any one of the above instructions in the program code.
The present invention also provides a computer-readable storage medium for storing program code for executing the parking space detection method as set forth in any one of the above.
From the above technical scheme, the invention has the following advantages: the invention obtains the visual parking space; matching the visual parking space with a preset parking space tracking list; updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces; and outputting the fusion parking space with the first confidence coefficient larger than a preset threshold value. Thereby improving the reliability of the fusion parking space and realizing the accurate detection of the parking space.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a step flowchart of a parking space detection method provided by an embodiment of the present invention;
Fig. 2 is a flowchart of steps of a parking space detection method according to another embodiment of the present invention;
FIG. 3 is a flowchart illustrating a step of updating a first confidence level of a fused parking space according to an embodiment of the present invention;
Fig. 4 is a flowchart of a step of updating corner positions of each corner of a fusion parking space according to an embodiment of the present invention;
fig. 5 is a block diagram of a parking space detection device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a parking space detection method, a device, electronic equipment and a storage medium, which are used for solving or partially solving the technical problem that the accuracy rate of a fusion parking space is low due to the fact that parking space images acquired at different stages are affected.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating steps of a parking space detection method according to an embodiment of the present invention.
The invention provides a parking space detection method, which specifically comprises the following steps:
Step 101, obtaining a visual parking space;
In the embodiment of the invention, the visual parking space refers to a visual image containing the parking space, which is obtained by acquiring data of the environment around the vehicle through the vehicle-mounted detection device.
In the embodiment of the invention, the visual parking space detection can be performed by adopting a vehicle-mounted camera and the like, and the selection of the detection device is not particularly limited.
It should be noted that, in the process of searching for a parking space, the detection device selected for collecting each frame of visual image of the same area is the same, and meanwhile, parameters of the detection device need to be kept unchanged in the process of collecting the visual images.
102, Matching a visual parking space with a preset parking space tracking list;
in the embodiment of the invention, a parking space tracking list needs to be maintained in advance, and the parking space tracking list records fusion data generated after each visual parking space acquisition.
The visual parking spaces collected each time are matched with the fusion parking spaces in the parking space tracking list, and fusion data in the parking space tracking list can be adjusted, so that detection deviation of the parking space positions generated in the previous parking space fusion process is reduced.
Step 103, updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces;
Confidence, also called reliability, or confidence level, confidence coefficient, i.e. when a sample estimates the overall parameter, its conclusion is always uncertain due to the randomness of the sample. Therefore, a method of stating probability, that is, interval estimation in mathematical statistics, is adopted, that is, how large the estimated value and the overall parameter are within a certain allowable error range, and the corresponding probability is called confidence.
Specifically, in the embodiment of the invention, the confidence level of the fusion parking space in the parking space tracking list can be updated according to the matching result, so that the first confidence level of the fusion parking space is obtained.
And 104, outputting the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value.
In the embodiment of the invention, a confidence coefficient threshold value can be preset, and if the first confidence coefficient of the fusion parking space in the parking space tracking list is larger than the confidence coefficient threshold value under the condition that the distance between the vehicle and the fusion parking space meets the preset distance condition, the fusion parking space can be represented to more accurately express the specific position of the parking space in the actual environment, and the fusion parking space can be output at the moment.
The invention obtains the visual parking space; matching the visual parking space with a preset parking space tracking list; updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces; and outputting the fusion parking space with the first confidence coefficient larger than a preset threshold value. Thereby improving the reliability of the fusion parking space and realizing the accurate detection of the parking space.
Referring to fig. 2, fig. 2 is a flowchart illustrating steps of a parking space detection method according to another embodiment of the present invention, where the method specifically includes the following steps:
step 201, detecting an initial visual parking space through a preset parking space detection model;
step 202, determining the size and shape of an initial vision parking space;
step 203, obtaining an initial visual parking space with the size and shape meeting the preset parking space standard as a visual parking space;
in the embodiment of the invention, a parking space detection model can be preset to detect the visual parking space.
After the initial visual parking space is detected, the size and the shape of the visual parking space are needed to be judged, and whether the visual parking space is a reasonable parking space or not is judged. For example, in one example, the position between adjacent parking spaces is easily misjudged as a parking space, and whether the position meets the requirement of a standard parking space can be judged through analysis of the size and the shape of the visual parking space, so that unreasonable parking spaces are eliminated, and parking space fusion operation is only performed on reasonable parking spaces in the follow-up process.
Step 204, matching the visual parking space with a preset parking space tracking list;
in the embodiment of the invention, a parking space tracking list needs to be maintained in advance, and the parking space tracking list records fusion data generated after each visual parking space acquisition.
The visual parking spaces collected each time are matched with the fusion parking spaces in the parking space tracking list, and fusion data in the parking space tracking list can be adjusted, so that detection deviation of the parking space positions generated in the previous parking space fusion process is reduced.
Step 205, updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces;
In the embodiment of the invention, the confidence level of the fusion parking space in the parking space tracking list can be updated according to the matching result, so that the first confidence level of the fusion parking space is obtained.
In a specific example of the present invention, as shown in fig. 3, step 205 may further comprise the following sub-steps:
s11, determining a sending stage of the visual parking space, and acquiring a second confidence coefficient of each corner point of the visual parking space;
S12, obtaining a confidence coefficient attenuation rate corresponding to the sending stage;
S13, acquiring the current confidence coefficient of each corner point of the fusion parking space;
step 205 may specifically comprise the sub-steps of:
S14, when the matching result is that the matching parking spaces and the unmatched parking spaces exist in the parking space tracking list, calculating a first matching confidence coefficient of each corner point of the matching parking spaces by adopting a second confidence coefficient, a confidence coefficient attenuation rate and a current confidence coefficient;
and S15, calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
In the embodiment of the invention, for the fusion parking spaces in different stages, corresponding attenuation strategies can be adopted, and different confidence degree attenuation rates are determined according to different stages. The specific confidence coefficient attenuation rate can be obtained through multiple test tests according to different factors such as the distance between the vehicle and the parking space, the precision of the parking space detection model and the like, and the invention is not limited in particular.
In a specific implementation, after the visual parking space is acquired, the second confidence coefficient of each corner point of the visual parking space can be calculated, and the current confidence coefficient of each corner point of each fusion parking space in the parking space tracking list is acquired. And selecting an updating mode of the fusion parking space according to whether the fusion parking space in the parking space tracking list is matched with the visual parking space.
In one example, when the visual parking space matches a certain parking space in the parking space tracking list, the second confidence level of the visual parking space, the current confidence level of the fused parking space, and the confidence decay rate of the current stage may be used to update the first confidence level of each corner point of the fused parking space. The specific calculation process can be seen in the following formula:
ft＝ft-1*αn+fnew
Wherein f t is the first confidence coefficient of the fused parking space corner, f t-1 is the current confidence coefficient of the fused parking space corner, f new is the second confidence coefficient of the visual parking space corner, and alpha n is the confidence coefficient attenuation rate.
And for the fusion parking spaces which are not matched with the visual parking spaces, updating the first confidence coefficient of each corner point of the fusion parking spaces by adopting the second confidence coefficient and the confidence coefficient attenuation rate. The specific calculation process can be found in the following formula:
ft＝ft-1*αn
In another example, the first confidence level further includes a second unmatched confidence level; step 205 may further comprise:
And S16, when the matching result is that only the unmatched parking spaces exist in the parking space tracking list, calculating second unmatched confidence coefficients of all angular points of the unmatched parking spaces by adopting the second confidence coefficients and the confidence coefficient attenuation rate.
In a specific implementation, when any one of the fused parking spaces in the visual parking space and the parking space tracking list cannot be matched, the formula f t＝ft-1*αn can be adopted to calculate the first confidence coefficient of each corner point of the fused parking space.
Further, when the matching result is that only unmatched parking spaces exist in the parking space tracking list, the visual parking spaces are added to the parking space tracking list.
In the embodiment of the invention, after updating the fusion parking spaces in the parking space tracking list, the angular point positions of all the angular points of the fusion parking spaces can be updated. As shown in fig. 4, the specific update procedure may include the sub-steps of:
s21, acquiring the current angular point position of the fusion parking space and the first angular point position of the vision parking space;
S22, calculating the updating weight of the corner points of the matched parking space by adopting the first confidence coefficient and the second confidence coefficient of the corner points of the fused parking space;
s23, calculating a second corner position of the fusion parking space by adopting the updated weight, the current corner position and the first corner position.
In a specific implementation, the update weight of the fusion parking space can be calculated according to the following formula:
w＝ft/(ft+fnew)
Wherein w is the updating weight of the fusion parking space corner point.
It should be noted that, when the fused parking space is not matched with the visual parking space, f new takes 0, and the update weight is 1.
Further, according to the update weight, the second corner position of the fused parking space can be calculated based on the following formula:
pt＝pt-1*w+pnew*(1-w)
Wherein p t is the second corner position of the fused parking space corner, and p new is the first corner position of the visual parking space corner; p t-1 is the current corner position of the corner of the fusion parking space.
It should be noted that, when the fusion parking space is not matched with the visual parking space, p new takes 0.
And 206, outputting the positions of the second corner points of the fusion parking space and the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient of each corner point of the fusion parking space is larger than the preset threshold value.
In the embodiment of the invention, a confidence coefficient threshold value can be preset, and if the first confidence coefficient of the fusion parking space in the parking space tracking list is larger than the confidence coefficient threshold value under the condition that the distance between the vehicle and the fusion parking space meets the preset distance condition, the fusion parking space can be represented to more accurately express the specific position of the parking space in the actual environment, and the fusion parking space can be output at the moment.
The invention obtains the visual parking space; matching the visual parking space with a preset parking space tracking list; updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces; and outputting the fusion parking space with the first confidence coefficient larger than a preset threshold value. Thereby improving the reliability of the fusion parking space and realizing the accurate detection of the parking space.
Referring to fig. 5, fig. 5 is a block diagram of a parking space detection device according to an embodiment of the present invention.
The embodiment of the invention provides a parking space detection device, which comprises:
The visual parking space acquisition module 501 is used for acquiring a visual parking space;
the matching module 502 is configured to match the visual parking space with a preset parking space tracking list;
A first confidence updating module 503, configured to update the fused parking spaces in the parking space tracking list according to the matching result, to obtain a first confidence of the fused parking spaces;
The fused parking space output module 504 is configured to output a fused parking space when the distance between the vehicle and the fused parking space satisfies a preset distance condition and the first confidence coefficient is greater than a preset threshold.
In an embodiment of the present invention, the visual parking space acquisition module 501 includes:
The initial visual parking space detection sub-module is used for detecting an initial visual parking space through a preset parking space detection model;
The size and shape determining submodule is used for determining the size and shape of the initial vision parking space;
the vision parking stall confirms submodule piece for obtain that the initial vision parking stall that size and shape all satisfy the parking stall standard of predetermineeing is the vision parking stall.
In an embodiment of the present invention, the method further includes:
The second confidence coefficient determining module is used for determining the sending stage of the visual parking space and acquiring the second confidence coefficient of each corner point of the visual parking space;
The confidence coefficient attenuation rate determining module is used for obtaining the confidence coefficient attenuation rate corresponding to the sending stage;
The current confidence coefficient determining module is used for obtaining the current confidence coefficient of each corner point of the fusion parking space;
The first confidence update module 503 includes:
The first matching confidence calculating submodule is used for calculating the first matching confidence of each corner point of the matched parking space by adopting the second confidence, the confidence attenuation rate and the current confidence when the matching result is that the matched parking space and the unmatched parking space exist in the parking space tracking list;
The first unmatched confidence coefficient calculation sub-module is used for calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
In an embodiment of the present invention, the first confidence updating module 503 further includes:
and the second unmatched confidence coefficient calculating submodule is used for calculating the second unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate when the matching result is that only the unmatched parking space exists in the parking space tracking list.
In an embodiment of the present invention, the method further includes:
the current angular point position and first angular point position acquisition submodule is used for acquiring the current angular point position of the fusion parking space and the first angular point position of the vision parking space;
the updating weight calculation sub-module is used for calculating the updating weight of the corner points of the matched parking space by adopting the first confidence coefficient and the second confidence coefficient of the corner points of the fused parking space;
And the second angular point position calculating sub-module is used for calculating the second angular point position of the fusion parking space by adopting the updating weight, the current angular point position and the first angular point position.
In an embodiment of the present invention, the fused parking space output module 504 includes:
And the fusion parking space output sub-module is used for outputting the fusion parking space and the second corner point position of the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient of each corner point of the fusion parking space is larger than the preset threshold value.
In an embodiment of the present invention, the method further includes:
And the adding module is used for adding the visual parking space to the parking space tracking list when the matching result is that only unmatched parking spaces exist in the parking space tracking list.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or terminal device that comprises the element.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The parking space detection method is characterized by comprising the following steps of:
acquiring a visual parking space;
Matching the visual parking space with a preset parking space tracking list;
updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces;
outputting the fusion parking space when the distance between the vehicle and the fusion parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value;
The first confidence level comprises a first matching confidence level and a first unmatched confidence level; and updating the fusion parking spaces in the parking space tracking list according to the matching result, and before the step of obtaining the first confidence coefficient of the fusion parking spaces, further comprising:
Determining the sending stage of the visual parking space, and acquiring a second confidence coefficient of each corner point of the visual parking space;
obtaining a confidence coefficient attenuation rate corresponding to the sending stage;
Acquiring the current confidence coefficient of each corner point of the fusion parking space;
and updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking spaces, wherein the step comprises the following steps:
when the matching result is that the matching parking spaces and the unmatched parking spaces exist in the parking space tracking list, calculating a first matching confidence coefficient of each corner point of the matching parking spaces by adopting the second confidence coefficient, the confidence coefficient attenuation rate and the current confidence coefficient;
And calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
2. The method of claim 1, wherein the step of obtaining a visual space comprises:
detecting an initial visual parking space through a preset parking space detection model;
Determining the size and shape of the initial vision parking space;
and obtaining an initial visual parking space with the size and shape meeting the preset parking space standard as a visual parking space.
3. The method of claim 1, wherein the first confidence level further comprises a second unmatched confidence level; updating the fusion parking space in the parking space tracking list according to the matching result to obtain a first confidence coefficient of the fusion parking space, and further comprising:
and when the matching result is that only the unmatched parking spaces exist in the parking space tracking list, calculating second unmatched confidence coefficients of all angular points of the unmatched parking spaces by adopting the second confidence coefficients and the confidence coefficient attenuation rates.
4. The method of claim 3, wherein after the step of updating the fused parking space in the parking space tracking list according to the matching result to obtain the first confidence coefficient of the fused parking space, the method further comprises:
Acquiring the current angular point position of the fusion parking space and the first angular point position of the vision parking space;
Calculating the updating weight of the corner points of the matched parking spaces by adopting the first confidence coefficient and the second confidence coefficient of the corner points of the fused parking spaces;
and calculating a second angular point position of the fusion parking space by adopting the updating weight, the current angular point position and the first angular point position.
5. The method of claim 4, wherein the step of outputting the fused parking space when the distance between the vehicle and the fused parking space satisfies a preset distance condition and the first confidence level is greater than a preset threshold value comprises:
When the distance between the vehicle and the fusion parking space meets the preset distance condition, and the first confidence coefficient of each corner point of the fusion parking space is larger than a preset threshold value, outputting the fusion parking space and the second corner point position of the fusion parking space.
6. The method as recited in claim 1, further comprising:
And when the matching result is that only unmatched parking spaces exist in the parking space tracking list, adding the visual parking spaces to the parking space tracking list.
7. The utility model provides a parking stall detection device which characterized in that includes:
the visual parking space acquisition module is used for acquiring a visual parking space;
the matching module is used for matching the visual parking space with a preset parking space tracking list;
the first confidence updating module is used for updating the fusion parking spaces in the parking space tracking list according to the matching result to obtain the first confidence of the fusion parking spaces;
The fused parking space output module is used for outputting the fused parking space when the distance between the vehicle and the fused parking space meets the preset distance condition and the first confidence coefficient is larger than a preset threshold value;
The first confidence level comprises a first matching confidence level and a first unmatched confidence level; the apparatus further comprises:
The second confidence coefficient determining module is used for determining the sending stage of the visual parking space and acquiring the second confidence coefficient of each corner point of the visual parking space;
the confidence coefficient attenuation rate determining module is used for obtaining the confidence coefficient attenuation rate corresponding to the sending stage;
the current confidence coefficient determining module is used for obtaining the current confidence coefficient of each corner point of the fusion parking space;
the first confidence updating module includes:
The first matching confidence calculation submodule is used for calculating the first matching confidence of each angular point of the matching parking space by adopting the second confidence, the confidence attenuation rate and the current confidence when the matching result is that the matching parking space and the unmatched parking space exist in the parking space tracking list;
And the first unmatched confidence coefficient calculating sub-module is used for calculating the first unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate.
8. The apparatus of claim 7, wherein the first confidence level further comprises a second unmatched confidence level; the first confidence updating module further includes:
And the second unmatched confidence coefficient calculating submodule is used for calculating the second unmatched confidence coefficient of each corner point of the unmatched parking space by adopting the second confidence coefficient and the confidence coefficient attenuation rate when the matching result is that only the unmatched parking space exists in the parking space tracking list.
9. An electronic device, the device comprising a processor and a memory:
The memory is used for storing program codes and transmitting the program codes to the processor;
The processor is configured to execute the parking space detection method according to any one of claims 1 to 6 according to instructions in the program code.
10. A computer readable storage medium for storing program code for performing the parking space detection method according to any one of claims 1 to 6.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109740521A (en) * | 2018-12-29 | 2019-05-10 | 百度在线网络技术（北京）有限公司 | The parking stall location determining method and device of automatic parking, electronic equipment and computer-readable medium |
| CN110775052A (en) * | 2019-08-29 | 2020-02-11 | 浙江零跑科技有限公司 | Automatic parking method based on fusion of vision and ultrasonic perception |
| CN110861639A (en) * | 2019-11-28 | 2020-03-06 | 安徽江淮汽车集团股份有限公司 | Parking information fusion method and device, electronic equipment and storage medium |
| CN110969655A (en) * | 2019-10-24 | 2020-04-07 | 百度在线网络技术（北京）有限公司 | Method, device, equipment, storage medium and vehicle for detecting parking space |
| WO2020238284A1 (en) * | 2019-05-29 | 2020-12-03 | 北京市商汤科技开发有限公司 | Parking space detection method and apparatus, and electronic device |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109740521A (en) * | 2018-12-29 | 2019-05-10 | 百度在线网络技术（北京）有限公司 | The parking stall location determining method and device of automatic parking, electronic equipment and computer-readable medium |
| WO2020238284A1 (en) * | 2019-05-29 | 2020-12-03 | 北京市商汤科技开发有限公司 | Parking space detection method and apparatus, and electronic device |
| CN110775052A (en) * | 2019-08-29 | 2020-02-11 | 浙江零跑科技有限公司 | Automatic parking method based on fusion of vision and ultrasonic perception |
| CN110969655A (en) * | 2019-10-24 | 2020-04-07 | 百度在线网络技术（北京）有限公司 | Method, device, equipment, storage medium and vehicle for detecting parking space |
| CN110861639A (en) * | 2019-11-28 | 2020-03-06 | 安徽江淮汽车集团股份有限公司 | Parking information fusion method and device, electronic equipment and storage medium |
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