WO2023123697A1 - 用于车辆后备箱的控制方法、控制系统及车辆 - Google Patents

用于车辆后备箱的控制方法、控制系统及车辆 Download PDF

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Publication number
WO2023123697A1
WO2023123697A1 PCT/CN2022/081391 CN2022081391W WO2023123697A1 WO 2023123697 A1 WO2023123697 A1 WO 2023123697A1 CN 2022081391 W CN2022081391 W CN 2022081391W WO 2023123697 A1 WO2023123697 A1 WO 2023123697A1
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Prior art keywords
light pattern
images
image
deformation
predetermined
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PCT/CN2022/081391
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English (en)
French (fr)
Inventor
鲁桂桂
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博泰车联网(南京)有限公司
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Publication of WO2023123697A1 publication Critical patent/WO2023123697A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R5/00—Compartments within vehicle body primarily intended or sufficiently spacious for trunks, suit-cases, or the like
    • B60R5/04—Compartments within vehicle body primarily intended or sufficiently spacious for trunks, suit-cases, or the like arranged at rear of vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
    • B60Q1/26—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
    • B60R16/0231—Circuits relating to the driving or the functioning of the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/20—Means to switch the anti-theft system on or off
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05B—LOCKS; ACCESSORIES THEREFOR; HANDCUFFS
    • E05B83/00—Vehicle locks specially adapted for particular types of wing or vehicle
    • E05B83/16—Locks for luggage compartments, car boot lids or car bonnets
    • E05B83/18—Locks for luggage compartments, car boot lids or car bonnets for car boot lids or rear luggage compartments
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05F—DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION; CHECKS FOR WINGS; WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05F15/00—Power-operated mechanisms for wings
    • E05F15/70—Power-operated mechanisms for wings with automatic actuation
    • E05F15/73—Power-operated mechanisms for wings with automatic actuation responsive to movement or presence of persons or objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05F—DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION; CHECKS FOR WINGS; WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05F15/00—Power-operated mechanisms for wings
    • E05F15/70—Power-operated mechanisms for wings with automatic actuation
    • E05F15/73—Power-operated mechanisms for wings with automatic actuation responsive to movement or presence of persons or objects
    • E05F2015/765—Power-operated mechanisms for wings with automatic actuation responsive to movement or presence of persons or objects using optical sensors

Definitions

  • the present application relates to the field of vehicle control, in particular to a control system and a control method for a vehicle trunk.
  • the control of the trunk of the vehicle has been changed from traditional manual control to inductive control, so that when the user carries heavy objects with both hands, it is no longer necessary to manually open the trunk.
  • the car key/mobile terminal positioning function it is proposed to use the car key/mobile terminal positioning function to automatically open the trunk when it senses that the user holding the car key/mobile terminal is approaching the trunk.
  • the trunk there is a high rate of false triggers in this way, for example, if the user just stands by the car and chats with friends, or just passes by the car, it is also possible to trigger the trunk to open.
  • An object of the present application is to provide a method of controlling the trunk of a vehicle, which has the advantage that by this method, whether the user wants to open the trunk can be confirmed through one or more interactions of the user with a light pattern projected at a predetermined location , so as to reduce the false trigger rate of the trunk.
  • Another object of the present application is to provide a system for controlling the trunk of a vehicle, which has the advantage of being able to interact with users effectively and conveniently, and can effectively reduce the probability of accidentally opening the trunk.
  • Another object of the present application is to provide a computer storage medium storing a computer program, wherein when the computer program is executed by a processor, a method for controlling the trunk of a vehicle is implemented.
  • the present application provides a method for controlling the trunk of a vehicle, which includes: projecting a light pattern to a predetermined projection area in response to determining that a target object enters a predetermined range of the trunk; whether the change satisfies a preset condition; and in response to determining that the change of the light emitting pattern satisfies a preset condition, opening the trunk. Determining whether the light pattern satisfies a preset condition includes: determining whether the deformation amount of the light pattern is greater than a first predetermined threshold.
  • the present application provides a system for controlling the trunk of a vehicle, which includes: a light projector installed on the vehicle and configured to project a light pattern to a predetermined projection area; and a processor configured to Projecting a light pattern to a predetermined projection area in response to determining that a target object enters a predetermined range of the trunk; determining whether a change in the light pattern satisfies a preset condition; and opening the trunk in response to the light pattern satisfying the preset condition. Determining whether the change of the light pattern satisfies a preset condition includes: whether the deformation amount of the light pattern is greater than a first predetermined threshold.
  • the present application provides a vehicle, which includes the above-mentioned system for controlling the trunk of the vehicle.
  • FIG. 1 is a schematic block diagram illustrating a system for controlling a trunk of a vehicle according to an embodiment of the present application
  • FIG. 2 is a schematic flowchart illustrating a method for controlling a trunk of a vehicle according to an embodiment of the present application
  • FIG. 3 is a diagram showing an exemplary application scenario for explaining a method for controlling a trunk of a vehicle
  • FIG. 4 is a schematic flowchart illustrating step S20 according to the present application.
  • FIG. 5 is a schematic flowchart illustrating step S220 according to another example of the present application.
  • FIG. 6 is a schematic flow chart showing step S2210 for acquiring a region of interest in an image
  • FIG. 7 is a schematic diagram showing step S2210 for acquiring a region of interest in an image
  • Fig. 8 is a schematic pixel layout diagram showing a region of interest
  • FIG. 9 is a schematic flowchart illustrating step S220 according to another example of the present application.
  • FIG. 10 is a schematic flowchart showing step S220 according to another example of the present application.
  • Fig. 11 is a schematic flowchart illustrating step S20 according to another exemplary embodiment.
  • first and second are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, a feature defined as “first” and “second” may explicitly or implicitly include one or more of these features.
  • FIG. 1 is a schematic block diagram illustrating a system for controlling a trunk of a vehicle according to an embodiment of the present application.
  • FIG. 2 is a schematic flowchart illustrating a method for controlling a trunk of a vehicle according to an embodiment of the present application.
  • FIG. 3 is a diagram showing an exemplary application scenario for explaining a method for controlling a trunk of a vehicle.
  • a system 10 for controlling the trunk of a vehicle may include: a processor 100, a light projector 200, an image collector 300 and memory 400.
  • the processor 100 may be physically and/or communicatively connected with the light projector 200 , the image collector 300 and the memory 400 .
  • the processor 100 may send control signals to the light projector 200 and the image collector 300 to control them to perform corresponding actions, and may acquire corresponding preset information from the memory 400 .
  • the method for controlling the trunk of a vehicle described below will be executed by the processor 100 controlling corresponding components.
  • the light projector 200 may be installed on a vehicle.
  • the light projector 200 is installed at a position near the trunk of the vehicle (e.g., the bottom of a bumper of the vehicle) or may be installed on the trunk.
  • the light projector 200 is exemplarily shown as being installed on the trunk, but it should be understood that the present application is not limited thereto.
  • the light projector 200 may be configured to project a light-emitting image (herein, also referred to as a light pattern) to a specific location area under the control of the processor 100 .
  • the light projector 200 may project a light pattern toward a predetermined projection area on the ground.
  • the light projector 200 may be a laser projector, which may include, for example, a high-power light-emitting element, so that the light pattern projected by it may still have strong visibility in a strong light environment.
  • the light projector 200 can be provided in multiples, and can be installed at multiple positions in the trunk of the vehicle, for example, at the left, right and/or middle positions of the trunk, In order to project light patterns to different positions according to the user's movement path. This will be described in detail below.
  • the image collector 300 may be installed on a vehicle.
  • the image collector 300 may be installed at a position near the trunk of the vehicle (for example, the bottom of a bumper of the vehicle) or may be installed on the trunk.
  • the image collector 300 may be configured adjacent to the light projector 200 .
  • the image collector 300 may be configured to acquire images of a predetermined projection area at predetermined time intervals under the control of the processor 100 .
  • the image collector 300 may be a high-definition camera, and may continuously collect image sets of a predetermined projection area at a fixed position and a fixed viewing angle.
  • a method 1000 for controlling a vehicle trunk includes:
  • Step S10 projecting a light pattern to a predetermined projection area in response to determining that the target object enters within a predetermined range of the trunk;
  • Step S20 Determine whether the change of the light pattern satisfies a preset condition.
  • Step S30 opening the trunk in response to determining that the change of the light emitting pattern satisfies a preset condition.
  • determining whether the change of the light pattern satisfies a preset condition includes: determining whether the deformation amount of the light pattern is greater than a first predetermined threshold. If the deformation amount of the light pattern is greater than the first predetermined threshold, it is determined that the change of the light pattern satisfies the preset condition; otherwise, it is determined that the change of the light pattern does not meet the preset condition.
  • the trunk control system 10 senses that the target object OBJ approaches the trunk (ie, enters within a predetermined range of the trunk)
  • the light projector 200 may be used to project a light pattern PAT toward a predetermined projection area on the ground. If the target object OBJ stands on the light pattern PAT, it can indicate that the target object OBJ has a need to open the trunk, so the trunk control system 10 can control the vehicle to automatically open the trunk.
  • the method 1000 may further include step S40: determining whether the target object enters within a predetermined range of the trunk.
  • whether the target object enters a predetermined range of the trunk can be determined through a car key/mobile terminal positioning function.
  • the vehicle key/mobile terminal positioning function can be realized by a UWB positioning method.
  • the UWB positioning method can, for example, be positioned based on the two-way time-of-flight method (including the unilateral two-way time-of-flight method and the bilateral two-way time-of-flight method), and the positioning methods can be, for example, TOA (time of arrival) positioning, TDOA (time difference of arrival) positioning and One or a combination of AOA (phase difference) positioning.
  • the target object may be a user holding a car key/mobile terminal that has been successfully authenticated and paired with the vehicle, thereby ensuring the safety of starting the vehicle.
  • the distance between the trunk of the vehicle and the target object may also be measured in real time by various other methods such as ultrasonic distance measuring sensors.
  • the predetermined range of the trunk may mean that the distance from the trunk of the vehicle in each direction is less than a preset distance, specifically, the preset distance may be within the range of 0.5 meters to 1.5 meters, for example, it may be 1 meter.
  • the interval value of the predetermined range can be set by the user according to preference, and the present application does not make specific limitations on this.
  • the trunk control system 10 may control the light projector 200 to project a light pattern toward a predetermined projection area on the ground.
  • the position of the predetermined projection area for the trunk may not be fixed, but may be changed according to the moving path of the target object. For example, when the vehicle determines that the target object is approaching the trunk from the left rear of the vehicle based on the positioning function of the car key/mobile terminal, the light pattern may be projected toward a predetermined position on the left rear of the vehicle.
  • the present application is not limited thereto, and the predetermined projection area may be fixed, or may also be set to deviate from the moving path of the target object, so as to avoid direct projection on the target object (eg, the target object's feet/shoes) , which can effectively reduce the false trigger rate.
  • the light pattern may be projected toward a predetermined position at the right rear/middle of the vehicle.
  • the light pattern may have various pattern shapes, sizes, colors and brightness according to user settings.
  • the light pattern can be presented as a car pattern, a key pattern, a car logo, a footprint landmark, etc., which is not specifically limited in the present application.
  • the present application takes the light pattern presenting a car pattern as an example for illustrative description.
  • the present application does not specifically limit the size of the light pattern, which may have a size larger than the target object’s feet as shown in FIG. Reduce false trigger rate while having a relatively small size.
  • Fig. 4 is a schematic flowchart illustrating step S20 according to the present application.
  • the trunk control system 10 can use the image collector 300 and the processor 100 to determine the specific change of the light pattern PAT caused by the standing of the target object OBJ.
  • the specific change of the light pattern PAT caused by the standing of the target object OBJ.
  • the light pattern PAT When an object OBJ stands on the light pattern PAT, at least part of the light pattern will fall on the feet (or shoes) of the object OBJ which are not flat. Due to the unevenness of the projection surface of the light pattern, the shape of the light pattern may change.
  • determining whether the change of the light pattern satisfies a preset condition may include: determining whether a deformation amount of the light pattern is greater than a certain threshold (eg, a first predetermined threshold).
  • a certain threshold eg, a first predetermined threshold
  • the image collector 300 may be controlled to acquire a first set of images including a plurality of images of a predetermined projection area at predetermined time intervals (step S210), and the processor 100 may determine the amount of deformation of the light pattern based on the first set of images Whether it is greater than the first predetermined threshold (step S220).
  • the deformation amount of the light pattern being greater than the first predetermined threshold, it is determined that the change of the light pattern satisfies a preset condition (step S230 ), thereby controlling the vehicle to open the trunk.
  • the first set of images may refer to a series of images of the predetermined projection area acquired over time since it is determined that the target object enters the predetermined range of the trunk (for example, before projecting the light pattern).
  • the position of the predetermined projection area can be determined according to the moving path of the target object detected by the vehicle.
  • the image collector 300 in order to ensure that the image collector 300 at a fixed position can acquire images of predetermined projection areas at different positions, the image collector 300 can be driven by the processor 100 to freely track the projection orientation of the light pattern. rotate.
  • the shooting angle of the image collector 300 can be kept fixed, and various imaging parameters of the image collector 300 (such as field of view, focal length, etc.) etc.) remain unchanged.
  • various imaging parameters of the image collector 300 such as field of view, focal length, etc.
  • step S220 it may be determined whether the deformation amount of the light pattern is greater than a first predetermined threshold based on the change between each group of adjacent images in the first set of images after the light pattern is projected.
  • a first predetermined threshold based on the change between each group of adjacent images in the first set of images after the light pattern is projected.
  • adjacent images means images captured one after the other in the time order in which they were captured.
  • the determination result of this example is easily affected by changes in areas other than the light pattern in the predetermined projection area, making it impossible to accurately detect changes in the light pattern itself.
  • Fig. 5 is a schematic flowchart illustrating step S220 according to another example of the present application.
  • step S220 first determine the region of interest including the light pattern of each image in the first image collection (step S2210); secondly, based on the first image For the region of interest of each group of adjacent images in the set, it is determined whether the amount of deformation of the light pattern is greater than a first predetermined threshold.
  • FIG. 6 is a schematic flow chart showing step S2210 for acquiring a region of interest in an image.
  • FIG. 7 is a schematic diagram illustrating step S2210 for acquiring a region of interest in an image.
  • Fig. 8 is a schematic pixel layout diagram showing a region of interest. The method of acquiring the region of interest will be described in detail below with reference to FIGS. 6 to 8 .
  • the step S2210 of determining the region of interest including the light pattern of each image in the first image collection includes: Step S2211, extracting the adjacent first image collection in the first image collection An image and a second image, wherein the first image does not include a light pattern, and the second image is an image acquired after the first image and includes a light pattern; step S2212, calculating a difference between the first image and the second image; and Step S2213, determine the region of interest based on the calculated difference.
  • the first image and the second image may be images captured during projection of the light pattern.
  • the first image corresponds to an image P1 of a predetermined projection area captured immediately before the light projector 200 starts projecting a light pattern.
  • the first image P1 may include a background part BG, which may represent basic information of a light projection area, such as ground environment information of a projection light pattern.
  • the second image may correspond to the image P2 of the predetermined projection area captured immediately after projecting the light pattern.
  • the second image P2 may also include a light pattern PAT projected on the ground.
  • the light pattern PAT is shown as a car pattern, but this is only an example. As described above, the light pattern PAT may have other arbitrary shapes.
  • difference information between the first image P1 and the second image P2 may be obtained by subtracting them.
  • the subtraction of two images may mean that the grayscale values or color components of the corresponding pixels of the two images are subtracted.
  • the subtraction operation between images according to the present application may be implemented by speckle interferometry, holographic filtering method, interference filtering method, grating coding method, etc., which is not limited in the present application.
  • the first difference image P3 can be obtained by subtracting the first image P1 and the second image P2. Through subtraction, the background part BG in the first image P1 and the second image P2 can be removed, and only the light pattern PAT remains. Thus, only the light pattern PAT may be included in the first difference image P3, which is in the form of a binarized black and white image.
  • the region of interest Q1 including the light pattern PAT in the first difference image P3 is determined.
  • the shape of the region of interest Q1 may be determined based on the shape and/or contour of the light pattern PAT.
  • the region of interest Q1 may have a rectangular shape as shown in FIG. 7 , but the present application is not limited thereto. The closer the region of interest Q1 is determined to be to the outer contour edge of the light pattern PAT, the more accurately the variation of the light pattern can be presented, and thus the more accurately the deformation of the light pattern can be determined.
  • the pixel coordinate positions of each pixel in the region of interest Q1 in the first difference image P3 may be acquired.
  • the region of interest Q1 may include a plurality of pixels PX 11 to PX mn .
  • the pixel PX 11 may be a pixel located in the first row and the first column of the region of interest Q1, and its pixel coordinate position in the first difference image P3 may be determined as (x 11 , y 11 ).
  • the pixel PX 1n may be a pixel located in the first row, nth column of the region of interest Q1, and its pixel coordinate position in the first difference image P3 may be determined as (x 1n , y 1n ).
  • the pixel PX mn may be a pixel located in the mth row and nth column of the region of interest Q1, and its pixel coordinate position in the first difference image P3 may be determined as (x mn , y mn ).
  • only the pixel coordinates of some pixels in the region of interest Q1 in the first difference image P3 may be obtained Location.
  • the pixel coordinate positions of pixels at the edge of the region of interest Q1 may be obtained, and further, the pixel coordinate positions of pixels at the four corners of the region of interest Q1 may also be obtained.
  • the determined pixel coordinate positions can be applied to the respective images in the first set of images taken after the second image P2, whereby the position of the corresponding region of interest can be locked in each image in the first set of images .
  • the method of determining whether the amount of deformation of the light pattern is greater than the first predetermined threshold after locking the region of interest in each image is continued.
  • determining whether the deformation of the light pattern is greater than a first predetermined threshold includes: step S2220, calculating the first The coincidence degree of the region of interest of each group of adjacent images in an image collection; Step S2230, determine whether any one of the calculated coincidence degrees is less than a predetermined value; and Step S2240, in response to determining that the calculated coincidence degree If any one is less than the predetermined value, it is determined that the deformation amount of the light pattern is greater than the first predetermined threshold, that is, it is determined that the preset condition for opening the trunk is met.
  • step S2220 for each image in the first image set, whenever a new image is acquired, the region of interest of the current image may be intercepted based on the pixel coordinate position of the region of interest; and It is compared with the ROI of the previous image to calculate the coincidence between the two.
  • the second difference image can be obtained by performing an image subtraction operation (which may be the same as the image subtraction operation in the previously described step S2210) on the region of interest between the current image and the previous image, which can present two front and back images.
  • the change of the region of interest of the first image; and then, the coincidence degree between the current image and the previous image can be determined based on the second difference image.
  • the higher the degree of coincidence the smaller the amount of variation between adjacent images, which can also mean that the target object is less likely to stand on the pattern.
  • the coincidence degree in adjacent images being less than a predetermined value, it is determined that the light pattern has a large deformation, that is, it is determined that the preset condition for opening the trunk is met.
  • FIG. 9 is a schematic flowchart illustrating step S220 according to another example of the present application.
  • step S220 the region of interest including the light pattern of each image in the first image set is first determined (step S2210); secondly, based on the first image For the region of interest of each group of adjacent images in the set, it is determined whether the amount of deformation of the light pattern is greater than a first predetermined threshold.
  • determining whether the deformation of the light pattern is greater than a first predetermined threshold includes: step S2220, calculating the phase of each group in the first image set The coincidence degree of the region of interest of adjacent images; Step S2230, determine whether any one of the calculated coincidence degrees is less than a predetermined value; Step S2250, in response to the adjacent third image and the fourth image in the first image set The coincidence degree of the region of interest is less than a predetermined value, determine whether there is a target object in the fourth image, the fourth image is an image acquired after the third image; and step S2240, in response to the existence of the target object in the fourth image, determine the light pattern
  • the deformation amount is greater than the first predetermined threshold, that is, it is determined that the preset condition for opening the trunk is met.
  • Step S2250 is added to further determine whether the preset condition for opening the trunk is met.
  • the present application will omit the description of the same steps as the method in FIG. 5 , and focus on the differences from the method in FIG. 5 to avoid redundancy.
  • each time an image is acquired its corresponding region of interest is intercepted for comparison with the previous image, so as to determine the degree of overlap between the region of interest of the current image and the previous image .
  • the third image may correspond to the previous image and the fourth image may correspond to the current image acquired after the previous image.
  • the region of interest of the current image (or the fourth image) has changed compared with the region of interest of the previous image (or the third image) (that is, the overlap between the two is less than a predetermined value)
  • the current image may be identified through an artificial intelligence (AI) model such as a convolutional neural network, so as to determine whether there is a target object therein.
  • AI artificial intelligence
  • the present application is not limited thereto, and the implementation form of the artificial intelligence model is not specifically limited, as long as it can effectively and intelligently identify the content in the image.
  • step S2240 in response to determining in step S2250 that there is a target object in the fourth image, it is determined whether the deformation amount of the light pattern is greater than a first predetermined threshold, that is, it is determined that the preset condition for opening the trunk is met.
  • the AI model is used to determine the target object (for example, the foot/shoe) pixel coordinate position in the current image; then, it is compared with the pixel coordinate position of the region of interest in the current image; if the coincidence degree of the two is greater than a predetermined value, it means that there is a target object standing on the On the light pattern, it can be determined that the preset condition for opening the trunk is met.
  • FIG. 10 is a schematic flowchart illustrating step S220 according to another example of the present application.
  • the processor may identify the profile of the light pattern in the current image each time an image is acquired, and compare it with a preset profile, To determine in real time whether the deformation amount of the light pattern in the current pattern satisfies the preset condition for opening the trunk.
  • the contour of the light pattern in each image in the first image set may be determined based on an artificial intelligence (AI) model such as a convolutional neural network.
  • AI artificial intelligence
  • the present application is not limited thereto, and the implementation form of the artificial intelligence model is not specifically limited, as long as it can effectively and intelligently identify the content in the image.
  • step S2270 firstly, the processor 100 (refer to FIG. 1 ) may extract from the memory 400 (refer to FIG. 1 ) the preset profile of the light pattern stored in it in advance, and then the light pattern of the current image identified based on the AI model may be The outline of the pattern is compared with the preset outline, and it is determined whether the coincidence degree of the two is less than a predetermined value. The greater the degree of coincidence between the two, the smaller the deformation of the light pattern projected on the ground, which may also mean that the target object is less likely to stand on the pattern.
  • FIG. 11 is a schematic flowchart illustrating step S20 according to another exemplary embodiment.
  • step S20 in FIG. 11 The difference between step S20 in FIG. 11 and step S20 shown in FIG. 4 is that after it is determined in step S220 that the deformation of the light pattern is greater than the first predetermined threshold, step S240, step S250 and step S260 are added to further Determine whether the preset conditions for opening the trunk are met.
  • step S240, step S250 and step S260 are added to further Determine whether the preset conditions for opening the trunk are met.
  • the method for determining that the deformation of the light pattern is greater than the first predetermined threshold described above with reference to FIGS. 5 to 10 may also be applied in steps S210 and S220 of FIG. 11 to constitute a part of this exemplary embodiment.
  • step S240 in response to determining in step S220 that the deformation amount of the light-emitting pattern is greater than a first predetermined threshold, a reminder signal is output to the target object.
  • the action that the target object still keeps standing on the projected pattern after receiving the reminder signal can further clarify that it really has the need to open the trunk.
  • the reminder action the scene of directly opening the trunk due to the direct projection of the light pattern on the target object (or its feet or shoes), or the scene of accidentally opening the trunk caused by the target object stepping on the light pattern unconsciously can be avoided .
  • the possibility of accidentally opening the trunk can be further eliminated and/or reduced.
  • the reminder signal may be a light signal and/or a sound signal.
  • the light projector 200 may change the color of the light pattern to remind the user, such as changing the color of the light pattern from green to more conspicuous red.
  • the vehicle can also send a voice reminder to the user, such as "Please confirm whether to open the trunk", or send out a specific melody as a prompt sound, which is not limited in this application.
  • the light pattern can also be flashed multiple times continuously through the light projector 200, so as to increase the probability that the user notices the light pattern.
  • a light reminder signal to the target object through other lighting devices of the vehicle (such as a rear taillight), which is not limited in the present application.
  • step S250 after the reminder signal is output, a second image set including a plurality of images of the predetermined projection area is acquired at predetermined time intervals.
  • This step S250 may be basically the same as the step S210 for acquiring the first image set, and details are not repeated here to avoid redundancy.
  • the predetermined time interval in step S250 may be the same as or different from the predetermined time interval in step S210, which is not specifically limited in this application.
  • step S260 it is determined based on the second set of images whether the amount of deformation of the light pattern is greater than a second predetermined threshold.
  • the second predetermined threshold may be the same as or different from the first predetermined threshold in step S220, which is not specifically limited herein.
  • step S260 it may be determined whether the deformation amount of the light pattern is greater than the second predetermined threshold by the following method: determining whether a target object exists in a region corresponding to the region of interest in a plurality of predetermined images in the second set of images; and in response to determining a region corresponding to the region of interest in each of the plurality of predetermined images There are target objects in all of them, and it is determined that the deformation amount of the light pattern is greater than a second predetermined threshold.
  • each time the processor acquires an image it intercepts the current image based on the pixel coordinate position of the region of interest acquired in step S2210 described with reference to FIG. 6 to FIG. 8 region of interest; then, use an AI model such as a convolutional neural network to identify whether there is a target object (eg, the foot/shoe of the target object) in the region of interest.
  • an AI model such as a convolutional neural network to identify whether there is a target object (eg, the foot/shoe of the target object) in the region of interest.
  • the image collector captures the second set of images at a fixed position with the same imaging parameters (such as field angle, focal length, etc.) During the collection, the image collector 300 can also take pictures of the predetermined projection area at a fixed position with the same viewing angle, so as to ensure that the second image collection can accurately record changes in the predetermined projection area as time goes by.
  • imaging parameters such as field angle, focal length, etc.
  • a plurality of images may be taken during the flashing interval of the light pattern (that is, during the period when the light pattern is not projected), and based on this A second image collection is formed. For example, an image can be captured every time a light pattern is flashed. Thereby, a plurality of images that do not include light patterns can be acquired. Subsequently, the AI model may be utilized to identify the presence or absence of the target object (eg, the target object's foot or shoe) in these multiple images that do not include the light pattern. In this embodiment, since the image used for AI recognition does not include the light pattern, the interference of the light pattern on the recognition result of the AI model can be eliminated, thereby making the recognition result more accurate.
  • step S230 in response to determining in step S260 that the deformation of the light pattern is greater than the second predetermined threshold, it is determined that the change of the light pattern satisfies a preset condition, and then the vehicle may be controlled to open the trunk.
  • step S260 whether the deformation amount of the light pattern is greater than the second predetermined threshold can be determined by the following methods: determining the contour of the light pattern in each image in the second image set; and responding If any one of the contours of the light patterns coincides with the preset contour is less than a predetermined value, it is determined that the amount of deformation of the light pattern is greater than a second predetermined threshold.
  • This process may be substantially the same as the step S220 for determining that the deformation of the light pattern is greater than the first predetermined threshold described with reference to FIG. 10 , and therefore, details are not repeated here to avoid redundancy.
  • the projection position of the light pattern remains unchanged, and the imaging parameters of the image collector remain the same during the two determinations of the light pattern deformation.
  • the light pattern may be projected to other directions deviated from the initial projection position of the light pattern after outputting the reminder signal to the target object. If the target object really needs to open the trunk, it can move to the new light pattern projection position. Correspondingly, if the processor 100 still detects that the target object is standing on the light pattern after switching the projection position of the light pattern (for example, the deformation of the light pattern is greater than a certain threshold), the trunk may be opened.
  • the change of the newly projected light pattern can be implemented by the method for determining that the deformation of the light pattern is greater than the first predetermined threshold (step S220 ) described with reference to FIGS. 5 to 10 .
  • the method of controlling a trunk of a vehicle may further include closing the trunk in response to determining that the target object is out of a predetermined range of the trunk. Similar to step S40 in FIG. 2 for determining that the target object enters its predetermined range, this process can also be implemented by using the car key/mobile terminal positioning function.
  • the light projector may emit infrared light, that is, it may project an infrared light pattern.
  • the image grabber may include an infrared filter that allows only infrared light to pass through. Since the target object (that is, the vehicle user) can emit infrared radiation, in this example, it is determined whether there are other infrared patterns overlapped at the infrared light pattern/whether the contour of the infrared light pattern coincides with the preset contour through an AI model or the like lower. If yes, it can be determined that the trunk opening condition is met; otherwise, the trunk opening condition is not met.
  • a vehicle which may include the trunk control system 10 described above, and the trunk control system 10 may implement the method for controlling the trunk of a vehicle described with reference to FIGS. 2 to 11 .
  • Another aspect of the present application also provides a computer-readable storage medium storing a computer program.
  • the computer program is executed by the processor, the method for controlling the trunk of the vehicle mentioned in the above embodiments is implemented.

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Abstract

一种控制车辆后备箱的方法，包括：响应于确定出目标对象进入后备箱的预定范围内（S40），向预定投射区域投射光图案（S10）；确定光图案的变化是否满足预设条件（S20）；以及响应于确定出光图案的变化满足预设条件，开启后备箱（S30）。确定光图案是否满足预设条件包括：确定光图案的形变量是否大于第一预定阈值（S220）。还公开了一种控制车辆后备箱的系统、一种包括控制车辆后备箱的系统的车辆以及一种计算机存储介质。

Description

用于车辆后备箱的控制方法、控制系统及车辆
相关申请的交叉引用
本申请要求于2021年12月29日提交于中国国家知识产权局(CNIPA)的、专利申请号为202111637293.0的中国专利申请的优先权和权益，该中国专利申请通过引用整体并入本文。
技术领域
本申请涉及车辆控制领域，具体地涉及用于车辆后备箱的控制系统及控制方法。
背景技术
随着车辆的智能化控制技术的逐渐发展，愈发倾向于对车辆内的各个部件进行智能化管控，以进一步在各个场景下方便用户的操作。
例如，对于车辆后备箱的控制，已从传统的手动控制转变成感应式控制，以在用户在双手搬有重物时，不必再手动开启后备箱。
在一些相关技术中，提出了通过车钥匙/移动终端定位功能，在感知到持有车钥匙/移动终端的用户接近后备箱时自动开启后备箱。然而，在这种方式存在较高的误触发率，例如，如果用户只是站在车边和朋友聊天，或者只是从车边经过，也有可能触发后备箱打开。
在另一些相关技术中，提出了利用传感器并配合相应的抬脚动作来实现车辆后备箱的自动开启。然而，受传感器位置(例如，设置在车辆保险杠底部)的影响，通常需要配合用户通过抬脚动作方能触发传感器，但当用户手提的物体过重，很难在保持身体平衡的同时抬起另一只脚以触发后备箱的开启。
发明内容
本申请的一个目的在于提供一种控制车辆后备箱的方法，其优势在于通过该方法，可以通过用户与投射在预定位置处的光图案的一次或多次互动来确认用户是否想要开启后备箱，以此降低后备箱的误触发率。
本申请的另一个目的在于提供一种控制车辆后备箱的系统，其优势在于能够有效便捷地与用户交互，并且可以有效降低后备箱误开启的概率。
本申请的另一个目的在于提供一种计算机存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时，实现控制车辆后备箱的方法。
本发明的其它优势和特点通过下述的详细说明得以充分体现并可通过所附权利要求中特地指出的手段和装置的组合得以实现。
根据本申请的第一方面，本申请提供了一种控制车辆后备箱的方法，其包括：响应于确定出目标对象进入后备箱的预定范围内，向预定投射区域投射光图案； 确定光图案的变化是否满足预设条件；以及响应于确定出光图案的变化满足预设条件，开启后备箱。确定光图案是否满足预设条件包括：确定所述光图案的形变量是否大于第一预定阈值。
根据本申请的第二方面，本申请提供了一种控制车辆后备箱的系统，其包括：光投射器，安装在车辆上，并且配置成向预定投射区域投射光图案；以及处理器，配置成：响应于确定出目标对象进入后备箱的预定范围内，向预定投射区域投射光图案；确定光图案的变化是否满足预设条件；以及响应于光图案满足预设条件，开启后备箱。确定光图案的变化是否满足预设条件包括：光图案的形变量是否大于第一预定阈值。
根据本申请的第三方面，本申请提供了一种车辆，其包括上述控制车辆后备箱的系统。
与本领域的相关技术相比，本申请具有下列至少一个技术效果：
1)使用光图案投射方式，通过用户与光图案的交互，来确认其开启后备箱的需求，可以有效避免后备箱在用户接近时自动开启而导致的误开启，可以有效降低车门开启误触发率；
2)光图案的交互方式简单便捷，且富有科技感；
3)通过灯光/声音提醒方式，进一步确认用户开启后备箱的需求，可以有效避免用户无意识地踩踏在光图案上而造成误开启后备箱；
4)在整个开关后备箱的过程中，无需接触后备箱，保证用户清洁和便利；以及
5)在整个开关后备箱的过程中，无需通过单腿站立完成指定动作，交互过程更加安全。
附图说明
通过参照附图详细描述本公开的实施方式，本公开的以上和其它实施方式和特征将变得更加显而易见，在附图中：
图1是示出了根据本申请的实施方式的用于控制车辆后备箱的系统的示意性框图；
图2是示出了根据本申请的实施方式的用于控制车辆后备箱的方法的示意性流程图；
图3是示出了用于说明用于控制车辆后备箱的方法的示例性应用场景图；
图4是示出了根据本申请的步骤S20的示意性流程图；
图5是示出了根据本申请的另一示例的步骤S220的示意性流程图；
图6是示出了用于获取图像中的感兴趣区域的步骤S2210的示意性流程图；
图7是示出了用于获取图像中的感兴趣区域的步骤S2210的示意图；
图8是示出了感兴趣区域的示意性像素布局图；
图9是示出了根据本申请的另一示例的步骤S220的示意性流程图；
图10是示出了根据本申请的另一示例的步骤S220的示意性流程图；以及
图11是示出了根据另外的示例性实施方式的步骤S20的示意性流程图。
具体实施方式
现将参照附图在下文中更全面地描述本发明，在附图中示出了本发明的实施方式。然而，本发明可以以不同的形式来实现，并且不应被解释为限于本文中阐述的实施方式。相反，提供这些实施方式是为了使本公开将是透彻且完整的，并且将向本领域的技术人员充分地传达本发明的范围。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本申请的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。
本技术领域技术人员可以理解，除非另外限定，这里使用的所有术语(包括技术术语和科学术语)，具有与本申请所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语，应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像本申请实施例中一样被特定定义，否则不会用理想化或过于正式的含义来解释。
图1是示出了根据本申请的实施方式的用于控制车辆后备箱的系统的示意性框图。图2是示出了根据本申请的实施方式的用于控制车辆后备箱的方法的示意性流程图。图3是示出了用于说明用于控制车辆后备箱的方法的示例性应用场景图。
首先，将参照图1对用于控制车辆后备箱的系统进行简要描述。
如图1中所示，根据示例性实施方式的用于控制车辆后备箱的系统10(下文中，简称为“后备箱控制系统”)可以包括：处理器100、光投射器200、图像采集器300和存储器400。
具体地，处理器100可以与光投射器200、图像采集器300和存储器400物理地和/或通信地连接。示例性地，处理器100可以向光投射器200和图像采集器300发送控制信号以控制其执行相应动作，并且可以从存储器400获取相应的预设信息。在本申请中，以下将描述的控制车辆后备箱的方法将由处理器100控制相应部件执行。
示例性地，光投射器200可以安装在车辆上。例如，光投射器200安装在车 辆的靠近后备箱的位置(例如，车辆保险杠的底部)处或可以安装在后备箱上。在图3中，仅出于描述和图示的便利，将光投射器200示例性地示出为安装在后备箱上，然而应理解，本申请不限于此。
根据示例性实施方式，光投射器200可以配置成在处理器100的控制下向特定位置区域投射发光的影像(本文中，也称为光图案)。作为一个示例，光投射器200可以朝向地面的预定投射区域投射光图案。示例性地，光投射器200可以是激光投影仪，其可以包括诸如具有大功率的发光元件，以便于在强光环境下其所投射的光图案仍然具有较强的可视性。
根据本申请的另外的实施方式，光投射器200可以设置成多个，并且可以安装在车辆后备箱的多个位置处，例如安装在后备箱的左侧、右侧和/或中间位置处，以便于根据用户的移动路径向不同位置处投射光图案。这将在下面进行详细描述。
示例性地，图像采集器300可以安装在车辆上。例如，类似于光投射器200，图像采集器300可以安装在车辆的靠近后备箱的位置(例如，车辆保险杠的底部)处或可以安装在后备箱上。示例性地，图像采集器300可以配置成与光投射器200相邻。
根据示例性实施方式，图像采集器300可以配置成在处理器100的控制下以预定的时间间隔获取预定投射区域的图像。例如，图像采集器300可以是高清摄像头，并且可以在固定位置处以固定的视角持续性采集预定投射区域的图像集合。
接下来，将参照图2和图3对利用后备箱控制系统来控制车辆后备箱的方法进行描述。
如图2中所示，根据示例性实施方式，用于控制车辆后备箱的方法1000包括：
步骤S10：响应于确定出目标对象进入后备箱的预定范围内，向预定投射区域投射光图案；
步骤S20：确定光图案的变化是否满足预设条件；以及
步骤S30：响应于确定出光图案的变化满足预设条件，开启后备箱。
在一个示例性实施方式中，确定光图案的变化是否满足预设条件包括：确定光图案的形变量是否大于第一预定阈值。如果光图案的形变量大于第一预定阈值，则确定光图案的变化满足预设条件；否则，则确定光图案的变化不满足预设条件。
参照图3，示出了方法1000的一个示例性应用场景。具体地，在后备箱控制系统10感测到有目标对象OBJ靠近后备箱(即，进入后备箱的预定范围内)，可以利用光投射器200朝向地面的预定投射区域投射光图案PAT。如果目标对象OBJ站立到光图案PAT上，则可以表示目标对象OBJ有开启后备箱的需求，由 此后备箱控制系统10可以控制车辆自动开启后备箱。
下文中，将对方法1000的各个步骤进行详细描述。
根据示例性实施方式，在步骤S10之前，方法1000还可以包括步骤S40：确定目标对象是否进入后备箱的预定范围内。根据示例性实施方式，可以通过车钥匙/移动终端定位功能来确定目标对象是否进入后备箱的预定范围内。
示例性地，车钥匙/移动终端定位功能可以通过UWB定位方法来实现。UWB定位方法可以例如基于双向飞行时间法(包括单侧双向飞行时间法、双侧双向飞行时间法)进行定位，并且定位方式可例如为TOA(到达20时间)定位、TDOA(到达时间差)定位和AOA(相位差)定位中的一种或多种的组合。在该示例中，目标对象可以是持有已与车辆完成安全认证且已配对成功的车钥匙/移动终端的用户，由此可以保证车辆启动的安全性。
然而，这仅是示例，本申请不限于此。在其它示例中，也可以通过诸如超声测距传感器等的其它各种方法来实时测量车辆后备箱与目标对象之间的距离。
示例性地，“后备箱的预定范围内”可以表示在各个方位距车辆后备箱的距离小于预设距离，具体地，所述预设距离可以在0.5米至1.5米的范围内，例如可以是1米。然而，这仅是示例，该预定范围的区间值可以由用户根据偏好进行设定，本申请对此不作具体限制。
根据示例性实施方式，在确定目标对象是否进入后备箱的预定范围内，后备箱控制系统10可以控制光投射器200朝向地面的预定投射区域投射光图案。
根据本申请的一个实施方式，预定投射区域对于后备箱的位置可以不是固定的，而是可以根据目标对象的移动路径而改变。例如，当车辆基于车钥匙/移动终端定位功能确定出目标对象从车辆的左后方接近后备箱，则可朝向车辆的左后方的预定位置处投射光图案。
然而，本申请不限于此，预定投射区域可以是固定不变的，或者也可以设定成偏离目标对象的移动路径，以避免直接投射在目标对象(例如，目标对象的脚部/鞋子)上，从而可以有效降低误触发率。例如，当车辆基于车钥匙/移动终端定位功能确定出目标对象从车辆的左后方接近后备箱，则可朝向车辆的右后方/中间的预定位置处投射光图案。
在本申请中，根据用户设定，光图案可以具有各种不同的图案形状、大小、颜色和亮度。例如，光图案可以呈现为汽车图案、钥匙图案、车标logo、脚印地标等各种类型，本申请对此不作具体限定。然而，出于图示和描述的便利，本申请以光图案呈现汽车图案为例进行例示性描述。同样地，本申请对光图案的大小也不作具体限定，其可以如图3中所示具有比目标对象的脚部大的尺寸，以便于目标对象站立和后续光图案变化的识别，也可以为了降低误触发率而具有相对较小的尺寸。
图4是示出了根据本申请的步骤S20的示意性流程图。
在步骤S20中，后备箱控制系统10可以利用图像采集器300和处理器100确定出由于目标对象OBJ的站立而导致的光图案PAT的特定变化。当有目标对象OBJ站立在光图案PAT上时，至少部分光图案会落在不平坦的目标对象OBJ的脚部(或者鞋子)上。由于光图案的投射面的不平坦，光图案的形状可能发生改变。
根据示例性实施方式，在步骤S20中，确定光图案的变化是否满足预设条件可以包括：确定光图案的形变量是否大于特定阈值(例如，第一预定阈值)。具体地，可以通过控制图像采集器300以预定的时间间隔获取包括预定投射区域的多个图像的第一图像集合(步骤S210)，并且处理器100可以基于第一图像集合判定光图案的形变量是否大于第一预定阈值(步骤S220)。响应于光图案的形变量大于第一预定阈值，确定出光图案的变化满足预设条件(步骤S230)，由此可以控制车辆开启后备箱。
在本文中，第一图像集合可以是指从确定有目标对象进入后备箱的预定范围内开始(例如，在投射光图案之前)随着时间的流逝获取的预定投射区域的一系列图像。
如上所述，可以根据车辆所检测到的目标对象的移动路径，来决定预定投射区域的位置。在这种情况下，为了确保处于固定位置处的图像采集器300能够获取到不同位置处的预定投射区域的图像，图像采集器300可以在处理器100的驱动下，追踪光图案投射方位自由地旋转。
然而，在确定光图案投射方位之后(例如，在获取第一图像集合期间)，图像采集器300的拍摄角度可以保持固定，且图像采集器300的各项成像参数(诸如，视场角、焦距等)均保持不变。由此，可以保证图像采集器300能够在固定位置处以相同的视角拍摄预定投射区域的第一图像合集，从而可以保证第一图像集合可以准确地记录随着时间的流逝预定投射区域中的变化。
根据本申请的一个示例，在步骤S220中，可以基于第一图像集合中在投射光图案之后的每一组相邻图像之间的变化，来确定光图案的形变量是否大于第一预定阈值。换言之，在该示例中，可以在投射光图案之后，每拍摄一个图像，均与其前一个图像进行比较，以计算二者间的重合度。重合度越高，相邻图像之间的变化量越小，这也可以意味着目标对象站立在图案上的可能性越小。响应于相邻图像中的重合度小于预定值，确定光图案发生形变，即确定出满足开启后备箱的预设条件。
在本文中，术语“相邻图像”表示按照被拍摄的时间顺序一前一后拍摄的图像。
然而，该示例的判定结果容易受到预定投射区域中除了光图案之外的其他区 域的变化的影响，使其无法准确地检测到光图案本身的变化情况。
图5是示出了根据本申请的另一示例的步骤S220的示意性流程图。
如图5中所示，根据本申请的另一示例，在步骤S220中，首先确定第一图像集合中的每个图像的包括光图案的感兴趣区域(步骤S2210)；其次，基于第一图像集合中的每一组相邻图像的感兴趣区域，确定光图案的形变量是否大于第一预定阈值。
图6是示出了用于获取图像中的感兴趣区域的步骤S2210的示意性流程图。图7是示出了用于获取图像中的感兴趣区域的步骤S2210的示意图。图8是示出了感兴趣区域的示意性像素布局图。以下将参照图6至图8来详细描述获取感兴趣区域的方法。
如图6中所示，根据示例性实施方式，确定第一图像集合中的每个图像的包括光图案的感兴趣区域的步骤S2210包括：步骤S2211，提取第一图像集合中的相邻的第一图像和第二图像，其中第一图像不包括光图案，第二图像是在第一图像之后获取的图像，并且包括光图案；步骤S2212，计算第一图像和第二图像的差值；以及步骤S2213，基于所计算的差值，来确定感兴趣区域。
根据示例性实施方式，第一图像和第二图像可以是在投射光图案期间拍摄的图像。
参照图7，示例性地，第一图像对应于在光投射器200开始投射光图案之前一瞬间拍摄的预定投射区域的图像P1。第一图像P1可以包括背景部分BG，其可以呈现光投射区域的基础信息，诸如投射光图案的地面环境信息。
示例性地，第二图像可以对应于在投射光图案之后一瞬间拍摄的预定投射区域的图像P2。除了背景部分BG之外，第二图像P2还可以包括投射在地面上的光图案PAT。在图7中，光图案PAT示出为汽车图案，但这仅是示例。如上所述，光图案PAT可以具有其他任意形状。
根据示例性实施方式，可以通过将第一图像P1和第二图像P2相减，获取二者之间的差异信息。两个图像相减可以表示将两个图像的对应像素的灰度值或彩色分量做减法运算。示例性地，根据本申请的图像之间的减法运算可以通过散斑干涉法、全息滤波法、干涉滤波法和光栅编码法等来实现，本申请对此不作限制。
如图7中所示，通过第一图像P1和第二图像P2相减可以获得第一差图像P3。通过减法运算，可以去除第一图像P1和第二图像P2中的背景部分BG，仅保留光图案PAT。因而，第一差图像P3中可以仅包括光图案PAT，其呈现二值化黑白图像的形式。
随后，基于第一差图像P3中的光图案PAT的位置，确定第一差图像P3中的包括光图案PAT的感兴趣区域Q1。感兴趣区域Q1的形状可以基于光图案PAT的形状和/或轮廓来确定。示例性地，感兴趣区域Q1可以如图7中所示那样具有矩形形状，但本申请不限于此。感兴趣区域Q1被确定成越接近于光图案PAT的外轮廓边缘，越能精确地呈现光图案的变化情况，由此越能准确地确定出光图案 的形变量。
接下来，根据一个实施方式，可以获取感兴趣区域Q1中的各个像素在第一差图像P3中的像素坐标位置。
示例性地，如图8中所示，感兴趣区域Q1可以包括多个像素PX 11至PX mn。像素PX 11可以是位于感兴趣区域Q1的第一行第一列中的像素，并且其在第一差图像P3中的像素坐标位置可以确定为(x 11，y 11)。像素PX 1n可以是位于感兴趣区域Q1的第一行第n列中的像素，并且其在第一差图像P3中的像素坐标位置可以确定为(x 1n，y 1n)。以此类推，像素PX mn可以是位于感兴趣区域Q1的第m行第n列中的像素，并且其在第一差图像P3中的像素坐标位置可以确定为(x mn，y mn)。
不同于前述实施方式中获取感兴趣区域Q1中的各个像素的像素坐标位置，在另一示例性实施方式中，可以仅获取感兴趣区域Q1中的部分像素在第一差图像P3中的像素坐标位置。例如，可以获取在感兴趣区域Q1的边缘处的像素的像素坐标位置，更进一步地，也可以获取在感兴趣区域Q1的四个拐角处的像素的像素坐标位置。
随后，可以将所确定的像素坐标位置应用到第一图像集合中的在第二图像P2之后拍摄的各个图像，由此可以在第一图像集合中的每个图像中锁定相应感兴趣区域的位置。
返回参照图5，继续描述在锁定各个图像中的感兴趣区域之后，确定光图案的形变量是否大于第一预定阈值的方法。
根据示例性实施方式，如图5中所示，基于第一图像集合中的每一组相邻图像的感兴趣区域，确定光图案的形变量是否大于第一预定阈值包括：步骤S2220，计算第一图像集合中的每一组相邻图像的感兴趣区域的重合度；步骤S2230，确定所计算的重合度中的任一个是否小于预定值；以及步骤S2240，响应于确定出所计算的重合度中的任一个小于预定值，确定光图案的形变量大于第一预定阈值，即确定满足开启后备箱的预设条件。
示例性地，在步骤S2220中，对于第一图像集合中的每个图像而言，每获取到一个新图像，便可以基于感兴趣区域的像素坐标位置，截取当前图像的感兴趣区域；并将其与前一图像的感兴趣区域进行比较，以计算二者间的重合度。
进一步地，可以通过对当前图像与前一图像的感兴趣区域执行图像减法运算(其可以与先前描述的步骤S2210中的图像减法运算相同)，获取到第二差图像，其可以呈现出前后两张图像的感兴趣区域的变化情况；并且随后，可以基于第二差图像来确定当前图像和前一图像之间的重合度。第二差图像的像素的灰度值或彩色分量越小，二者的重合度越高。重合度越高，相邻图像之间的变化量越小，这也可以意味着目标对象站立在图案上的可能性越小。响应于相邻图像中的重合 度小于预定值，确定光图案发生较大形变，即确定出满足开启后备箱的预设条件。
图9是示出了根据本申请的另一示例的步骤S220的示意性流程图。
如图9中所示，根据本申请的另一示例，在步骤S220中，首先确定第一图像集合中的每个图像的包括光图案的感兴趣区域(步骤S2210)；其次，基于第一图像集合中的每一组相邻图像的感兴趣区域，确定光图案的形变量是否大于第一预定阈值。
参照图9，基于第一图像集合中的每一组相邻图像的感兴趣区域，确定光图案的形变量是否大于第一预定阈值包括：步骤S2220，计算第一图像集合中的每一组相邻图像的感兴趣区域的重合度；步骤S2230，确定所计算的重合度中的任一个是否小于预定值；步骤S2250，响应于第一图像集合中的相邻的第三图像和第四图像的感兴趣区域的重合度小于预定值，确定第四图像中是否存在目标对象，第四图像是在第三图像之后获取的图像；以及步骤S2240，响应于第四图像中存在目标对象，确定光图案的形变量大于第一预定阈值，即确定满足开启后备箱的预设条件。
简言之，以上过程与参照图5描述的方法的不同之处在于，在S2230中确定出有相邻的图像(对应于第三图像和第四图像)之间的重合度小于预定值之后，增加了步骤S2250来进一步确定是否满足开启后备箱的预设条件。为了便于描述，本申请将省略对与图5中的方法相同的步骤的描述，并将重点侧重于与图5的方法的不同之处，以避免冗余。
具体地，如先前参照图5所描述的，每获取一个图像，便截取其相应的感兴趣区域来与前一图像进行比较，从而确定当前图像与前一图像的感兴趣区域之间的重合度。在该示例中，第三图像可以对应于所述前一图像，第四图像可以对应于在前一图像之后获取到的所述当前图像。
在确定出当前图像(或第四图像)的感兴趣区域相较于前一图像(或第三图像)的感兴趣区域发生变化(即二者间的重合度小于预定值)之后，可以进一步确定当前图像(或第四图像)中是否存在目标对象(例如，目标对象的脚部/鞋子)。
示例性地，可以通过卷积神经网络等人工智能(AI)模型来对当前图像(或第四图像)进行识别，以确定其中是否存在目标对象。然而，本申请不限于此，并且不对人工智能模型的实现形式进行具体限定，只要其能够有效且智能地识别图像中的内容即可。
在步骤S2240中，响应于在步骤S2250中确定出第四图像中存在目标对象，确定光图案的形变量是否大于第一预定阈值，即确定满足开启后备箱的预设条件。
在另外的实施方式中，更进一步地，在步骤S2250中确定出第四图像中存在目标对象(例如，目标对象的脚部/鞋子)时，利用AI模型确定出目标对象(例 如，目标对象的脚部/鞋子)在当前图像中的像素坐标位置；随后，将其与感兴趣区域在当前图像中的像素坐标位置进行比较；若二者的重合度大于预定值，则表示有目标对象站立在光图案上，由此可以确定满足开启后备箱的预设条件。
图10是示出了根据本申请的另一示例的步骤S220的示意性流程图。
如图10中所示，根据本申请的另一示例，在步骤S220中，基于第一图像集合判定光图案的形变量是否大于第一预定阈值可以包括：步骤S2260，确定第一图像集合中的每个图像中的光图案的轮廓；步骤S2270，确定光图案的轮廓中的任一个与预设轮廓的重合度是否小于预定值；以及步骤S2280，响应于光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定光图案的形变量大于第一预定阈值。
在示例性实施方式中，对于第一图像集合中的每个图像而言，处理器可以每获取到一个图像，便识别当前图像中的光图案的轮廓，并将其与预设轮廓进行比较，以实时地确定当前图案中的光图案的形变量是否满足开启后备箱的预设条件。
具体地，在步骤S2260中，可以基于通过卷积神经网络等人工智能(AI)模型来确定第一图像集合中的每个图像中的光图案的轮廓。然而，本申请不限于此，并且不对人工智能模型的实现形式进行具体限定，只要其能够有效且智能地识别图像中的内容即可。
在步骤S2270中，首先处理器100(参照图1)可以从存储器400(参照图1)中提取预先存储在其中的光图案的预设轮廓，随后可以将基于AI模型识别到的当前图像的光图案的轮廓与预设轮廓进行比较，并确定二者的重合度是否小于预定值。二者重合度越大，表示投射在地面上的光图案的形变量越小，这也可以意味着目标对象站立在图案上的可能性越小。
以下将参照图11对根据本申请的另外的示例性实施方式进行描述。图11是示出了根据另外的示例性实施方式的步骤S20的示意性流程图。
图11中的步骤S20与图4中所示的步骤S20的不同之处在于，在步骤S220中确定出光图案的形变量大于第一预定阈值之后，增加了步骤S240、步骤S250和步骤S260来进一步确定是否满足开启后备箱的预设条件。为了便于描述，本申请将省略对与图4中的方法相同的步骤的描述，并将重点侧重于与图4的方法的不同之处，以避免冗余。
应理解，以上参照图5至图10描述的用于确定光图案的形变量大于第一预定阈值的方法也可应用于图11的步骤S210和S220中，以构成本示例性实施方式的一部分。
具体地，在步骤S240中，响应于在步骤S220中确定出光图案的形变量大于第一预定阈值，向目标对象输出提醒信号。目标对象在收到提醒信号之后仍保持 站立在投射图案上的动作，可以进一步明确其确有开启后备箱的需求。通过提醒动作，可以避免由于光图案直接投射到目标对象(或其脚部或鞋子)上直接开启后备箱的场景，或者可以避免目标对象无意识地踩踏在光图案上而造成误开启后备箱的场景。由此，可以进一步消除和/或降低误开启后备箱的可能。
根据示例性实施方式，提醒信号可以是光信号和/或声音信号。例如，可以通过光投射器200变换光图案的颜色来提醒用户，诸如将光图案的颜色由绿色转换成更显眼的红色。同时，车辆也可以向用户发送语音提醒，例如“请确认是否开启后备箱”，也可以发出特定旋律作为提示音，本申请对此不做限制。
进一步地，也可以通过光投射器200连续多次地闪动光图案，以提高用户注意到光图案的概率。
在另外的实例中，也可以通过车辆的其他灯光装置(例如后尾灯)来向目标对象输出光提醒信号，本申请对此不做限制。
在步骤S250中，在输出提醒信号之后，以预定的时间间隔获取包括预定投射区域的多个图像的第二图像集合。该步骤S250可以与用于获取第一图像集合的步骤S210基本上相同，此处不作过多赘述以避免冗余。
另外，在该步骤S250中的预定的时间间隔可以与步骤S210中的预定时间间隔相同或者不同，本申请对此不作具体限定。
在步骤S260中，基于第二图像集合确定光图案的形变量是否大于第二预定阈值。应理解，第二预定阈值可以与步骤S220中的第一预定阈值相同或不同，本文对此不作具体限定。
不同于用于确定光图案的形变量是否大于第一预定阈值的步骤S220，根据一个示例性实施方式，在步骤S260中，可以通过以下方法来确定光图案的形变量是否大于第二预定阈值：确定第二图像集合中的多个预定图像中的与在感兴趣区域对应的区域中是否存在目标对象；以及响应于确定出在多个预定图像中的每个中的与感兴趣区域对应的区域中均存在目标对象，确定光图案的形变量大于第二预定阈值。
具体地，对于第二图像合集中的每个图像，处理器每获取到一个图像，便基于在参照图6至图8描述的步骤S2210中获取的感兴趣区域的像素坐标位置，来截取当前图像的感兴趣区域；然后，利用诸如卷积神经网络的AI模型来识别感兴趣区域中是否存在目标对象(例如，目标对象的脚部/鞋子)。
应注意，在该示例中，图像采集器在固定位置处以与第一图像集合的成像参数(诸如，视场角、焦距等)相同的成像参数来拍摄第二图像集合，并且在拍摄第二图像集合期间，图像采集器300也可以以在固定位置处以相同的视角对预定投射区域进行拍摄，从而可以保证第二图像集合可以准确地记录随着时间的流逝预定投射区域中的变化。
更进一步地，在通过光投射器200连续多次地闪动光图案以提醒用户的示例 中，可以在光图案的闪动间隙(即，不投射光图案期间)拍摄多张图像，并以此形成第二图像合集。例如，每闪动一次光图案，便可以拍摄一次图像。由此，可以获取不包括光图案的多个图像。随后，可以利用AI模型在这些不包括光图案的多个图像中识别是否存在目标对象(例如，目标对象的脚部或鞋子)。在该实施方式中，由于用于AI识别的图像不包括光图案，因而可以排除光图案对AI模型识别结果的干扰，从而使得识别结果更准确。
在步骤S230中，响应于在步骤S260中确定出光图案的形变量大于第二预定阈值，确定光图案的变化满足预设条件，随即可以控制车辆开启后备箱。
根据另一示例性实施方式，在步骤S260中，可以通过以下方法来确定光图案的形变量是否大于第二预定阈值：确定第二图像集合中的每个图像中的光图案的轮廓；以及响应于光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定光图案的形变量大于第二预定阈值。该过程可以与参照图10描述的用于确定光图案的形变量大于第一预定阈值的步骤S220基本上相同，因而，在此不作赘述以避免冗余。
以上参照图11描述的实施方式中，在向目标对象输出提醒信号之后，光图案的投射位置保持不变，且在两次光图案形变量的确定期间，图像采集器的成像参数保持相同。
然而，根据本申请的另一实施方式，不同于图11的实施方式，在向目标对象输出提醒信号之后，可以向偏离光图案的初始投射位置的其他方位投射光图案。如果目标对象确有开启后备箱的需求，则可以移步至新的光图案投射位置上。相应地，处理器100如果在转换光图案投射位置之后，仍检测到光图案上有目标对象站立(例如，光图案的形变量大于特定阈值)，则可以开启后备箱。
在该示例性实施方式中，对新投射的光图案的变化情况可以通过参照图5至图10描述的用于确定光图案的形变量大于第一预定阈值的方法(步骤S220)来实现。
进一步地，根据示例性实施方式的控制车辆后备箱的方法还可以包括：响应于确定目标对象离开后备箱的预定范围，关闭后备箱。类似于图2中的用于确定目标对象进入其预定范围内的步骤S40，该过程也可以利用车钥匙/移动终端定位功能来实现。
进一步地，根据示例性实施方式的光投射器可以发射红外光，即其可以投射红外光图案。图像采集器可以包括仅允许红外光线通过的红外滤光片。由于目标对象(即，车辆用户)可以散发红外辐射，因而在该示例中，通过AI模型等来确定在红外光图案处是否重叠有其他红外图案/是否红外光图案的轮廓与预设轮 廓重合度较低。如果是，则可以确定满足后备箱开启条件；否则，不满足后备箱开启条件。
根据本申请的另一方面，还提供了一种车辆，其可以包括以上描述的后备箱控制系统10，该后备箱控制系统10可以执行参照图2至图11描述的控制车辆后备箱的方法。
本申请的另一面还提供一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述实施方式提及的控制车辆后备箱的方法。
以上对本申请的实施方式进行了描述。但是，这些实施方式仅仅是为了说明的目的，而并非为了限制本申请的范围。本申请的范围由所附权利要求及其等同限定。在不背离本申请的范围的情况下，本领域技术人员可以做出多种替代和修改，这些替代和修改都应落在本申请的范围之内。
本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离本申请的构思的情况下，由上述技术特征或其等同特征进行任意组合而形成的其它技术方案。例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。

Claims (26)

  1. 一种控制车辆后备箱的方法，包括：
    响应于确定出目标对象进入所述后备箱的预定范围内，向预定投射区域投射光图案；
    确定所述光图案的变化是否满足预设条件；以及
    响应于确定出所述光图案的变化满足所述预设条件，开启所述后备箱，
    其中，确定所述光图案是否满足所述预设条件包括：确定所述光图案的形变量是否大于第一预定阈值。
  2. 根据权利要求1所述的方法，其中，所述方法还包括：
    响应于确定所述目标对象离开所述后备箱的预定范围，关闭所述后备箱。
  3. 根据权利要求1所述的方法，其中，确定所述光图案的形变量是否大于所述第一预定阈值包括：
    以预定的时间间隔获取包括所述预定投射区域的多个图像的第一图像集合；以及
    基于所述第一图像集合判定所述光图案的形变量是否大于所述第一预定阈值。
  4. 根据权利要求3所述的方法，其中，基于所述第一图像集合判定所述光图案的形变量是否大于所述第一预定阈值包括：
    确定所述第一图像集合中的每个图像的包括所述光图案的感兴趣区域；以及
    基于所述第一图像集合中的每一组相邻图像的感兴趣区域，确定所述光图案的形变量是否大于所述第一预定阈值。
  5. 根据权利要求4所述的方法，其中，确定所述第一图像集合中的每个图像的包括所述光图案的感兴趣区域包括：
    提取所述第一图像集合中的相邻的第一图像和第二图像，其中所述第一图像不包括所述光图案，所述第二图像是在所述第一图像之后获取的图像，并且包括所述光图案；以及
    基于所述第一图像和所述第二图像的差值，确定所述感兴趣区域。
  6. 根据权利要求4或5所述的方法，其中，基于所述第一图像集合中的每一组相邻图像的感兴趣区域，确定所述光图案的形变量是否大于所述第一预定阈值包括：
    计算所述第一图像集合中的每一组相邻图像的感兴趣区域的重合度；以及
    响应于所述重合度中的任一个小于预定值，确定所述光图案的形变量大于所述第一预定阈值。
  7. 根据权利要求4或5所述的方法，其中，基于所述第一图像集合中的每一组相邻图像的感兴趣区域，确定所述光图案的形变量是否大于第一预定阈值包括：
    计算所述第一图像集合中的每一组相邻图像的感兴趣区域的重合度；
    响应于所述第一图像集合中的相邻的第三图像和第四图像的感兴趣区域的重合度小于预定值，确定所述第四图像中是否存在目标对象，所述第四图像是在所述第三图像之后获取的图像；以及
    响应于所述第四图像中存在所述目标对象，确定所述光图案的形变量大于所述第一预定阈值。
  8. 根据权利要求3所述的方法，其中，基于所述第一图像集合判定所述光图案的形变量是否大于所述第一预定阈值包括：
    确定所述第一图像集合中的每个图像中的光图案的轮廓；以及
    响应于所述光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定所述光图案的形变量大于第一预定阈值。
  9. 根据权利要求4或5所述的方法，其中，确定所述光图案是否满足预设条件还包括：
    响应于确定出所述光图案的形变量大于所述第一预定阈值，向所述目标对象输出提醒信号；以及
    确定所述光图案的形变量是否大于第二预定阈值。
  10. 根据权利要求9所述的方法，其中，确定所述光图案的形变量是否大于所述第二预定阈值包括：
    在输出所述提醒信号之后，以预定的时间间隔获取包括所述预定投射区域的多个图像的第二图像集合；以及
    基于所述第二图像集合确定所述光图案的形变量是否大于所述第二预定阈值。
  11. 根据权利要求10所述的方法，其中，基于所述第二图像集合确定所述光图案的形变量是否大于所述第二预定阈值包括：
    确定所述第二图像集合中的多个预定图像中的与所述感兴趣区域对应的区域中是否存在所述目标对象；以及
    响应于确定出在所述多个预定图像中的每个中的与所述感兴趣区域对应的 区域中均存在所述目标对象，确定所述光图案的形变量大于所述第二预定阈值。
  12. 根据权利要求9所述的方法，其中，确定所述光图案的形变量是否大于所述第二预定阈值包括：
    在输出所述提醒信号之后，以预定的时间间隔获取包括所述预定投射区域的多个图像的第二图像集合；
    确定所述第二图像集合中的每个图像中的光图案的轮廓；以及
    响应于所述光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定所述光图案的形变量大于所述第二预定阈值。
  13. 控制车辆后备箱的系统，包括：
    光投射器，安装在所述车辆上，并且配置成向预定投射区域投射光图案；以及
    处理器，配置成：
    响应于确定出目标对象进入所述后备箱的预定范围内，向预定投射区域投射光图案；
    确定所述光图案的变化是否满足预设条件；以及
    响应于所述光图案满足所述预设条件，开启所述后备箱，
    其中，确定所述光图案的变化是否满足预设条件包括：光图案的形变量是否大于第一预定阈值。
  14. 根据权利要求13所述的系统，其中，所述系统还包括：图像采集器，安装在所述车辆上，并且配置成在固定位置处以固定的视角获取所述预定投射区域的图像，以及
    其中，所述处理器还配置成：
    控制所述图像采集器以预定的时间间隔获取包括所述预定投射区域的多个图像的第一图像集合；以及
    基于所述第一图像集合判定所述光图案的形变量是否大于所述第一预定阈值。
  15. 根据权利要求14所述的系统，其中，所述处理器还配置成：
    确定所述第一图像集合中的每个图像的包括所述光图案的感兴趣区域；以及
    基于所述第一图像集合中的每一组相邻图像的感兴趣区域，确定所述光图案的形变量是否大于所述第一预定阈值。
  16. 根据权利要求15所述的系统，其中，所述处理器还配置成：提取所述第一图像集合中的相邻的第一图像和第二图像，其中所述第一图像不包括所述光 图案，所述第二图像是在所述第一图像之后获取的图像，并且包括所述光图案；以及
    基于所述第一图像和所述第二图像的差值，确定所述感兴趣区域。
  17. 根据权利要求15或16所述的系统，其中，所述处理器还配置成：计算所述第一图像集合中的每一组相邻图像的感兴趣区域的重合度；以及
    响应于所述重合度中的任一个小于预定值，确定所述光图案的形变量大于所述第一预定阈值。
  18. 根据权利要求15或16所述的系统，其中，所述处理器还配置成：计算所述第一图像集合中的每一组相邻图像的感兴趣区域的重合度；
    响应于所述第一图像集合中的相邻的第三图像和第四图像的感兴趣区域的重合度小于预定值，确定所述第四图像中是否存在目标对象，所述第四图像是在所述第三图像之后获取的图像；以及
    响应于所述第四图像中存在所述目标对象，确定所述光图案的形变量大于所述第一预定阈值。
  19. 根据权利要求14所述的系统，其中，所述处理器还配置成：
    确定所述第一图像集合中的每个图像中的光图案的轮廓；以及
    响应于所述光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定所述光图案的形变量大于第一预定阈值。
  20. 根据权利要求15或16所述的系统，其中，所述处理器还配置成：响应于确定出所述光图案的形变量大于所述第一预定阈值，向所述目标对象输出提醒信号；以及
    确定所述光图案的形变量是否大于第二预定阈值。
  21. 根据权利要求20所述的系统，其中，所述处理器还配置成：在输出所述提醒信号之后，控制所述图像采集器以预定的时间间隔获取包括所述预定投射区域的多个图像的第二图像集合；以及
    基于所述第二图像集合确定所述光图案的形变量是否大于所述第二预定阈值。
  22. 根据权利要求21所述的系统，其中，所述处理器还配置成：
    确定所述第二图像集合中的多个预定图像中的与所述感兴趣区域对应的区域中是否存在所述目标对象；以及
    响应于确定出在所述多个预定图像中的每个中的与所述感兴趣区域对应的 区域中均存在所述目标对象，确定所述光图案的形变量大于所述第二预定阈值。
  23. 根据权利要求20所述的系统，其中，所述处理器还配置成：在输出所述提醒信号之后，控制所述图像采集器以预定的时间间隔获取包括所述预定投射区域的多个图像的第二图像集合；
    确定所述第二图像集合中的每个图像中的光图案的轮廓；以及
    响应于所述光图案的轮廓中的任一个与预设轮廓的重合度小于预定值，确定所述光图案的形变量大于所述第二预定阈值。
  24. 根据权利要求13所述的系统，其中，所述处理器还配置成：响应于确定所述目标对象离开所述后备箱的预定范围，关闭所述后备箱。
  25. 车辆，包括权利要求13至24中任一项所述的控制车辆后备箱的系统。
  26. 一种计算机存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时，实现如权利要求1至12中任一项所述的控制车辆后备箱的方法。
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