Method for calibrating a headlight of a motor vehicle, system comprising a camera and at least one headlight and motor vehicle comprising the system

Abstract

The invention relates to a method for calibrating a headlight (12) of a motor vehicle (10). The headlight (12) generates a light-based calibration pattern (28) which comprises at least one pattern feature (32) and which is projected onto an object (26) in the vicinity of the motor vehicle (10). For different pattern features (32), camera coordinates are determined to map the respective pattern feature (32) onto a camera projection plane (34) in a camera coordinate system (18), and headlight coordinates are determined to map the respective pattern feature (32) onto a headlight projection plane in a headlight coordinate system (20). A translation vector (36) between an origin of the camera coordinate system (18) and an origin of the headlight coordinate system (20) is determined.From several relations forming a system of equations, a rotation matrix is ​​determined which, together with the translation vector (36), describes a coordinate transformation between the camera coordinate system (18) and the headlight coordinate system (20) by establishing, for each of the different pattern features (32), one of the relations between the camera coordinates of one of the pattern features (32) and the headlight coordinates of the same pattern feature (32) via an essential matrix.

Description

[0001] The invention relates to a method for calibrating a headlight of a motor vehicle, a system comprising a camera and at least one headlight, and a motor vehicle comprising the system comprising the camera and at least one headlight.

[0002] A motor vehicle (vehicle) includes at least one headlight, which may require calibration. This headlight could be, for example, a front headlight capable of providing low beam and / or high beam. The need for calibration, specifically determining and / or adjusting the headlight's orientation, arises particularly because an incorrect headlight orientation can cause glare for other road users. In the case of a front headlight, these other road users could include oncoming traffic, vehicles ahead, and / or pedestrians. The headlight's orientation describes, in particular, its direction, i.e., the solid angle relative to the vehicle into which the headlight emits its light.

[0003] Correct headlight alignment is particularly important when using glare-free high beams. Glare-free high beams are a known technology that remains permanently switched on during activation, automatically detects other road users, and adjusts the beam distribution to prevent dazzling them. Specifically, the beam distribution is adjusted and / or restricted to ensure that other road users are not illuminated by the glare-free high beam. To achieve a balance between driver visibility and limiting the beam distribution to avoid dazzling other road users, calibration of the glare-free high beam and / or the headlight in general is necessary.This allows for a small tolerance or safety margin, ensuring that even in the event of an estimation error in the position of another road user, a change in the headlight orientation, or predefinable calibration errors, glare for other road users is still prevented. The tolerance or safety margin is therefore, in particular, a solid angle area in which none of the other road users are located, but which is nevertheless kept clear of the high beam light. Specifically, the tolerance or safety margin is a range of a predefinable width around a solid angle area in which the other road user is located and / or has been detected. The predefinable width can, for example, be specified as an angle.To keep the safety zone small, calibration of the headlight may be necessary, in particular calibration at predefined time intervals and / or time intervals.

[0004] Over time, a calibrated headlight can change its orientation, for example due to weather events, temperature changes, and / or physical impact, such as a bump. Therefore, a simple calibration method, particularly one that can be repeated at predefined intervals, can be advantageous.

[0005] Calibrating the headlight means, in particular, adjusting and / or setting the orientation and / or alignment of the headlight.

[0006] An exemplary calibration procedure for a headlight is described in DE 10 2022 103 294 B4. According to the calibration procedure described therein, a calibration pattern is projected onto a flat surface of an object, a homography matrix is ​​determined from which an estimated position of the calibration pattern is derived, and subsequently, a deviation between the estimated calibration pattern and the actual calibration pattern is determined. A disadvantage of the procedure is that a flat surface is absolutely necessary onto which the calibration pattern can be projected, which makes the procedure less flexible in its application.

[0007] Similarly, US Patent 10,814,775 B2 describes a method for calibrating a headlight. According to this method, a calibration pattern is projected onto a projection plane, and a trajectory is determined in the image plane of the sensor, which describes the propagation of electromagnetic radiation. A disadvantage of this method is the significant computational effort required to calculate the trajectory.

[0008] Similarly, DE 10 2017 117 594 A1 describes a method for the automatic detection of headlight misalignment, whereby a calibration pattern is projected in the area in front of the vehicle, two images are taken at a predetermined time interval, and it is determined whether a characteristic feature from the first image can be found on a corresponding epipolar line in the second image. A disadvantage of this method is that the same characteristic feature must be depicted in two consecutive images.

[0009] The object of the invention is to provide a method for calibrating a headlight, which can be carried out in particular without a predetermined calibration environment.

[0010] The problem is solved by the subject matter of the independent claims. Possible embodiments of the invention are specified in the dependent claims, the following description, and the figures.

[0011] The invention relates to a method for calibrating a headlight of a motor vehicle. Calibration of the headlight means, in particular, determining the orientation and / or alignment of the headlight relative to the motor vehicle, and thus, in particular, determining the solid angle relative to the motor vehicle in which the light emitted by the headlight is emitted.

[0012] The motor vehicle includes at least one camera whose position and orientation relative to the motor vehicle are known. This means, in particular, that the motor vehicle includes a calibrated camera. Furthermore, the motor vehicle includes at least one headlight whose position on the motor vehicle is known. This means, in particular, that starting from a vehicle coordinate system that moves with the motor vehicle and whose origin and axes are fixed and / or constant relative to the motor vehicle, the coordinates of the camera and the headlight are known within this vehicle coordinate system. Additionally, the alignment and / or orientation of the camera within the vehicle coordinate system may be known.

[0013] The aim of the method is, in particular, to determine the alignment and / or orientation of the headlight in a camera coordinate system and / or in the vehicle coordinate system. According to the invention, the headlight emits light and generates and / or radiates a light-based calibration pattern, which comprises at least one pattern feature and is projected onto an object in the vicinity of the vehicle. The distance between the headlight and the object can be arbitrary. The headlight, in particular, generates a light distribution that can be characterized by areas of varying brightness and that at least partially illuminates an object in the vicinity of the vehicle. This allows the object to be illuminated at different points with varying brightness, whereby a pattern (calibration pattern) can be projected onto the object due to the different brightness levels.This means, in particular, that areas with a first brightness are formed, separated from other areas with the first brightness by areas with a different second brightness. Specifically, the use of only two brightness levels to generate the calibration pattern may be intended, for example, illuminated areas where the headlight emits light and / or which the headlight illuminates, and areas where the headlight does not emit light and / or which the headlight does not illuminate.

[0014] A pattern area describes, in particular, a characteristic brightness distribution of a portion of the calibration pattern. A pattern feature can be a characteristic point within the pattern area. Additionally or alternatively, the pattern feature can be identical to the pattern area. In particular, the pattern feature is a point uniquely identifiable within the calibration pattern. For example, the pattern feature is a characteristic point of a shape, such as a center point and / or a corner and / or a point along an edge and / or boundary of the shape. The shape can be formed by having a different brightness than its surroundings, in particular a region surrounding the shape. The shape is, in particular, a first brightness region that is delimited by a second brightness region from at least one other shape (first brightness region), and / or vice versa.The edge of the shape can be defined by a line that describes a transition between areas of different brightness and / or between the shape and its surroundings. The shape can be unique within the calibration pattern and / or the pattern area. The calibration pattern can, in particular, comprise multiple pattern features and / or multiple pattern areas, whereby it may be stipulated that the multiple pattern features and / or the multiple pattern areas do not overlap and / or do not adjoin each other. A pattern feature can be implemented by a luminance with a geometric distribution (e.g., the geometric shape of a luminous edge) and / or a temporal distribution (e.g., a blinking pattern).

[0015] The calibration pattern can be generated by one or a combination of several methods known from the prior art for generating the pattern of a headlight. For example, the headlight can include several LEDs (light-emitting diodes), wherein a predetermined portion of the LEDs can be switched off and another predetermined portion of the LEDs switched on to generate the calibration pattern. Additionally or alternatively, the headlight can include several mirrors whose position and / or orientation relative to the vehicle and / or to another part of the headlight is adjustable, with the calibration pattern being generated by adjusting the mirrors. Additionally or alternatively, the headlight can include an LCD layer whose light transmittance and / or transmissivity is varied and / or decreased in predeterminable ranges to generate the calibration pattern.

[0016] For different projections of at least one pattern feature, camera coordinates are determined to describe a mapping of the respective pattern feature onto a camera projection plane in a camera coordinate system. This means, in particular, that the camera captures an image in which at least part of the respective calibration pattern is depicted. This image represents, in particular, nothing other than the vehicle's surroundings as mapped onto the camera projection plane, which may be a focal plane of the camera. The camera coordinates are, in particular, available as normalized coordinates and / or normalized image coordinates, as known from the prior art. Specifically, the camera projection plane may be a virtual plane that can result from representing the camera coordinates as normalized coordinates.The camera coordinates can specify, for each pattern feature, where the representation of that feature is located on the camera projection plane. This description is relative to a camera coordinate system whose axes and origin can be defined relative to the camera. In particular, the camera coordinate system is fixed relative to the vehicle coordinate system, allowing coordinate transformations between the vehicle and camera systems to be independent of changing influencing factors and / or the current driving situation. Specifically, the camera coordinates are determined by evaluating each image captured by the camera.

[0017] A similar principle applies to the headlight. According to the invention, the headlight coordinates are determined by describing an image of the respective pattern feature on a headlight projection plane within a headlight coordinate system. The headlight projection plane is, in particular, the plane in which the calibration pattern is generated. For example, the headlight projection plane is the plane in which the LEDs and / or the LCD layer and / or the mirrors are arranged, and / or a plane in which the calibration pattern can be sharply projected. The headlight projection plane is preferably located between the headlight and the object and / or within the headlight. The headlight coordinates can describe, within the headlight coordinate system, where the respective pattern feature is located on the headlight projection plane.The headlight coordinates are provided, in particular, as normalized coordinates and / or normalized image coordinates, as known from the prior art. The headlight projection plane can be a virtual plane, which can result from representing the headlight coordinates as normalized coordinates. The headlight coordinate system is defined relative to the headlight, meaning that the orientation of the headlight coordinate system—that is, the orientation of the axes of the headlight coordinate system relative to the camera coordinate system and relative to the vehicle coordinate system—can depend on the orientation and / or alignment of the headlight relative to the vehicle. The headlight coordinates are determined, in particular, by ascertaining a relative position of the pattern feature within the calibration pattern.

[0018] The spotlight coordinates and the camera coordinates are therefore independent of the distance between the spotlight and the object onto which the calibration pattern is projected. This means, in particular, that the magnitude of the distance between the spotlight and the object is neither a component of the camera coordinates nor a component of the spotlight coordinates. The spotlight coordinates and the camera coordinates can describe positions on a plane, thus comprising precisely two values ​​for determining position in two-dimensional space, for example, without specifying a distance between the plane and a reference point, such as the spotlight and / or the camera. This is achieved, in particular, by using normalized coordinates as spotlight and camera coordinates.

[0019] Both the camera position and the headlight position relative to the vehicle are known. From these known positions, a translation vector is determined between an origin of the camera coordinate system and an origin of the headlight coordinate system. This means that the translation vector can be determined that maps the origin of the camera coordinate system to the origin of the headlight coordinate system, and / or vice versa.

[0020] From several relations forming a system of equations, a rotation matrix is ​​determined which, together with the translation vector, describes a coordinate transformation between the camera coordinate system and the spotlight coordinate system. This means, in particular, that by applying the rotation matrix and the translation vector together, the camera coordinate system can be transformed into the spotlight coordinate system and / or vice versa. Specifically, by applying the coordinate transformation comprising the translation vector and the rotation matrix, a point described in the camera coordinate system can be described in the spotlight coordinate system, and / or a point in the spotlight coordinate system can be described in the camera coordinate system.

[0021] The rotation matrix is ​​determined by establishing an essential matrix for each of the different pattern features, encompassing one of the relations between the camera coordinates of one of the pattern features and the headlight coordinates of the same pattern feature via an epipolar equation. The essential matrix depends on the rotation matrix and the translation vector. In particular, this means that a relation is established for each of the pattern features, where the relation can be an equation describing a connection between the headlight coordinates and the camera coordinates of the respective pattern feature.The relation includes in particular the essential matrix known from the epipolar equations, which is known from the prior art and which depends on both the rotation matrix and the translation vector, which together can describe the coordinate transformation between the camera coordinate system and the headlight coordinate system.

[0022] The rotation matrix is, in particular, a 3x3 matrix with three unknown angles, which can be used to describe a rotation in space. Thus, every relation includes the same three unknown angles as unknowns, where, in particular, all other quantities in each relation can be known by knowing the respective camera coordinates, the respective spotlight coordinates, and the translation vector. A relation can be an equation with the three unknowns in the form of the three unknown rotation angles of the rotation matrix.

[0023] A separate relation can be established for each of the different pattern features. These relations can then form a system of equations in which each relation can have the same unknowns, namely the three rotation angles of the rotation matrix, and none of the relations has any additional unknowns. By solving the system of equations, the rotation matrix can be determined by finding the three unknown rotation angles.

[0024] The relative orientation of the spotlight to the known orientation of the camera is determined using the calculated rotation matrix. This is done in particular by knowing the orientation of the camera in the camera coordinate system and by knowing the orientation of the spotlight in the spotlight coordinate system. The relative orientation of the spotlight to the orientation of the camera can be determined by calculating the orientation of the spotlight in the camera coordinate system using the rotation matrix and the translation vector, for example, via a coordinate transformation.

[0025] The invention provides a method for calibrating a motor vehicle headlight, which offers several advantages. For example, calibration requires only the position of the pattern feature in the camera projection plane and / or headlight projection plane, thus rendering the actual distance between the motor vehicle and the object irrelevant for calibration. In particular, the method is independent of the object onto which the calibration pattern is projected. Additionally or alternatively, a flat surface for projection is not required to perform the method. Rather, any object can be used. This results in exceptional flexibility.

[0026] Additionally or alternatively, the problem is reduced by this method to determining three unknown rotation angles, which can be solved using a system of equations. The headlight coordinates and camera coordinates of the same pattern feature are always entered into the system of equations for each relation, whereby different pattern features can be used for different equations and / or relations. Since the distance to the object serving as the projection surface for the calibration pattern is irrelevant to the method (only the distance to the camera projection plane or the headlight projection plane, which can be determined from the normalized coordinates, is used), the distance between the vehicle and the object is also irrelevant to the method.Regardless of the location of the object onto which the projection pattern is projected, it is sufficient to know only the relative position of the headlight to the camera, as well as the position of the pattern feature on both the camera and headlight projection planes, to determine the relative orientation of the headlight to the camera. The distance of the camera projection plane from the camera and / or the headlight projection plane from the headlight can be determined by using normalized coordinates to describe the pattern feature on the camera and / or headlight projection plane. This allows the method to be performed while the vehicle is in motion and / or the pattern features can be captured at different times during the vehicle's journey, with the pattern features and / or the calibration pattern being projected onto different objects each time.

[0027] Different pattern features can be the same pattern feature on different objects and / or different pattern features of the projection pattern. This results in a very large quantity and / or number of available pattern features during a vehicle's journey (the quantity of pattern features can depend on how many different objects the calibration pattern is projected onto during the vehicle's journey). The number of pattern features results in a corresponding number of relations that form the system of equations, enabling a more precise determination of the rotation matrix and thus a more accurate calibration of the headlight. In particular, the calibration quality depends on the number of relations in the system of equations.Additionally, the calibration quality depends particularly on the variability of the relationships, with the difference potentially increasing the more varied the object's distance from the vehicle is when the pattern features are used for the procedure. It is especially advantageous to use pattern features projected onto objects that were at varying distances from the vehicle at the time of acquisition. This can be achieved by estimating the distance between the object and the vehicle, for example, by measuring the distance between the vehicle and a predefined number of reference points on the object, such as a maximum of one, two, five, or ten reference points.

[0028] Based on the determined orientation of the headlight (estimated or actual current orientation), an automatic adjustment of the headlight can be performed so that it has a predefined orientation (target orientation). This means, in particular, that after calibration, the headlight's orientation can be adjusted so that it corresponds to the predefined orientation. The predefined orientation could, for example, be a predetermined orientation (e.g., stipulated by law, regulation, or manufacturer) that illuminates a predefined area and / or excludes predefined areas from the headlight's beam. After the automatic adjustment, the headlight can be recalibrated.If the recalibration of the headlight does not result in the desired headlight orientation, a message may be issued to the driver, indicating, for example, a fault in a headlight adjustment mechanism, which can then be used to adjust the headlight orientation. In particular, the safety zone may be adjusted to the determined headlight orientation when using the glare-free high beam.

[0029] Further developments of the invention result in additional advantages.

[0030] Further training includes defining the essential matrix E as a cross product of the translation vector t→ and the rotation matrix R is calculated. In the case of the translation vector t→=(txtytz) In particular, it is a three-dimensional vector that can describe the translation between the camera coordinate system and the spotlight coordinate system. The rotation matrix R can be appended to the three rotation angles ψ, θ, ϕ. Specifically, the three rotation angles ψ, θ, ϕ are the only unknowns of the rotation matrix R: R = R(ψ, θ, ϕ). The cross product of the translation vector t→ and the rotation matrix R can also be written as T x R with Tx=(0−tztytz0−tx−tytx0). The essential matrix E can be given as E = T x R.

[0031] One of the relations is established by assigning a camera vector to one of the pattern features M1. pc,M1→ Describing the camera coordinates from one side, multiplied by the essential matrix E, for the same pattern feature M1 a headlight vector ph,M1→ The camera coordinates are described by multiplying the headlight coordinates from another side against the essential matrix E, and the resulting product is set to zero. This means, in particular, that the camera coordinates describe the position of one of the pattern features M1 in the camera coordinate system using the camera vector. pc,M1→ The headlight coordinates of the same pattern feature M1 can accordingly be expressed as a headlight vector. ph,M1→ can be described as a relation that defines the headlight coordinates and thus the headlight vector. ph,M1→ of the pattern feature M1 via the essential matrix E with the camera coordinates and thus the camera vector pc,M1→ When comparing and / or describing things in a confusing way, it follows in particular that pc,M1→TEph,M1→=0 as a relation for the pattern feature M1, where pc,M1→T the transposed vector.

[0032] In particular, it is intended that the camera vector describes the camera coordinates and / or the spotlight vector describes the spotlight coordinates, each as normalized coordinates. This means, in particular, that the camera vector and / or the spotlight vector describe the point projected onto a plane only as a function of two coordinates lying in the plane. The plane is, in particular, the camera projection plane and / or the spotlight projection plane. Specifically, no knowledge of the distance between the projection of the pattern feature onto the object and the spotlight and / or the camera is required. This use of normalized coordinates is described, in particular, by the fact that the spotlight coordinates describe the pattern feature projected onto the spotlight projection plane, and the camera coordinates describe the pattern feature projected onto the camera projection plane.

[0033] For various pattern features M1, M2, M3, ..., each of which can describe a point in the calibration pattern, in particular a characteristic and / or uniquely identifiable point in the calibration pattern, a relation is established for each, whereby the entirety of the relations forms a nonlinear system of equations. This means that the relation pc,M1→TEph,M1→=0, The relationship established for one of the pattern features M1 is additionally established for other pattern features M2, M3, ... This is done in particular by using the headlight coordinates and camera coordinates of the respective pattern feature in the relation. The following additional relations result as examples: pc,M2→TEph,M2→=0,pc,M3→TEph,M3→=0,… The nonlinear system of equations includes, in particular, all relations of the different pattern features M1, M2, M3, ....

[0034] In particular, the relations of the nonlinear system of equations each contain the same three unknowns, which can be the three rotation angles ψ, θ, ϕ of the rotation matrix R(ψ, θ, ϕ). The nonlinear system of equations is solved using a nonlinear optimization approach, for example, using an iterative Levenberg-Marquardt algorithm known from the art and / or a Gauss-Newton method known from the art. Through nonlinear optimization, the unknowns of the nonlinear system of equations can be determined. In particular, if the nonlinear system of equations contains more than three relations, the three rotation angles ψ, θ, ϕ of the rotation matrix can be determined, which are, in particular, the only unknowns of the nonlinear system of equations, and thus the rotation matrix can be determined.The more relations the nonlinear system of equations encompasses, the more accurately the rotation matrix can be determined. Therefore, it may be advisable to use as many pattern features as possible and thereby establish as many relations as possible that can be encompassed by the nonlinear system of equations.

[0035] The method offers the advantage of a procedure for calibrating a headlight that is independent of a calibration environment.

[0036] Further development involves conducting the procedure while the vehicle is in motion, ensuring that at least two different pattern features, which contribute to the same determination of the same rotation matrix, are captured at different times and projected by the headlight onto different objects in the environment and / or captured by the camera onto different objects in the environment. This means, in particular, that the vehicle's movement projects the calibration pattern onto different objects in the environment, which can, in particular, change the distance between the vehicle and the projected calibration pattern.

[0037] According to the invention, the determination of the rotation matrix is ​​based in particular on providing a relation for each of the various pattern features and determining the unknowns of the rotation matrix from the resulting system of equations. In a further development, it is particularly provided that the different pattern features include those pattern features that were captured at different times during the journey of the motor vehicle, i.e., that were projected onto different objects and / or onto objects at different distances from the motor vehicle, and whose projections thus exhibit different distances to the motor vehicle.The various pattern features can therefore be, in particular, pattern features taken from different areas of the projection pattern (pattern areas), where the different areas may have a different appearance and / or the pattern features describe a characteristic and clearly recognizable point in the respective area, and / or pattern features that were captured at two different times and thus projected onto different objects, and / or projected onto objects that are at different distances from the motor vehicle. At least two of the pattern features are different pattern features.

[0038] The various pattern features are all incorporated into a single calculation of the rotation matrix via the non-linear system of equations. This means, in particular, that a separate relation is established for each of the different pattern features. These relations together form the system of equations. The rotation matrix can then be determined from this entire system of equations.

[0039] It is specifically not intended that only those pattern features be selected for calculating the rotation matrix that were captured while the vehicle was stationary and whose projections on the object each have the same distance to the vehicle, and / or describe only a single point in time of capture and whose projections on the object each have the same distance to the vehicle. In particular, it is not intended that pattern features captured at different times and / or from different distances between the vehicle and the object be used for multiple iterative calculations of the rotation matrix.Multiple iterative calculations of the rotation matrix can involve improving a rotation matrix derived from the previous iteration (or, in the first iteration, an initial rotation matrix) in each iteration step by adding new data. The data for different iterations may be collected at different times, while within a single iteration step, all data may be collected at the same time. This means that, according to the training, it is not intended to successively determine an improved version of the rotation matrix, where only pattern features recorded at the same time are used for each individual calculation of the rotation matrix, but different time points can be used for different improvement steps.

[0040] The rotation matrix can be iteratively improved, whereby, according to the refinement, camera and headlight coordinates of pattern features are used for each iteration step. These features are captured at different times and / or projected onto different objects and / or objects at varying distances from the vehicle. Alternatively, or in addition, the rotation matrix can be determined in a single step, incorporating all relationships. Preferably, an initial rotation matrix is ​​used as the starting matrix for the rotation matrix. This initial rotation matrix can be characterized by describing a rotation component of the coordinate transformation, which gives the headlight coordinate system a predefinable orientation relative to the camera coordinate system and / or relative to the vehicle—an orientation that is, in particular, one specified by regulations and / or deemed correct.

[0041] Additionally or alternatively, it is not intended that point pairs be formed for a relation, where the points of a point pair describe the same part of the calibration pattern but were acquired at different times, thus describing different pattern features. This means, in particular, that the points of a point pair do not enter into a single relation. Rather, according to the further development, a relation can describe the same pattern feature in each case, incorporating the camera coordinates and the spotlight coordinates that describe the same pattern feature at the same time. Different relations can each encompass different pattern features, that is, pattern features that describe other parts of the calibration pattern and / or were acquired at different times. The different relations can form the system of equations for determining the rotation matrix.In particular, all relations of the system of equations are used to determine the same rotation matrix. Different relations are specifically not used to determine different iteration levels and / or improvement levels of the rotation matrix.

[0042] The advantage of this advanced training is that, firstly, a larger dataset is available due to the pattern characteristics recorded at different times, derived from projections with varying distances between the object and the vehicle. This larger dataset can describe more diverse situations, thus enabling a more precise determination of the rotation matrix.

[0043] Additionally or alternatively, further training offers the advantage that the procedure can be carried out flexibly and easily while driving.

[0044] Further training includes the requirement that the procedure is carried out regardless of the degree of flatness of the object onto which at least part of the calibration pattern is projected, and / or that flatness determination is omitted. This means, in particular, that the procedure is independent of the object's surface structure. This is primarily because the distance between the vehicle and the object onto which the calibration pattern is projected is irrelevant to the procedure. Therefore, any object of any shape can be used, as long as it causes diffuse scattering of light such that areas of varying brightness appear on the object, especially on its surface.The object can cause different or locally varying perspective distortions, particularly within the projection pattern and / or between different pattern features, as might be the case with a bush or the canopy of a tree. In particular, it may be intended that pattern features are used that are projected onto an uneven surface.

[0045] Additionally or alternatively, the training stipulates that the procedure is carried out regardless of whether the entire calibration pattern is projected onto the object. This means, in particular, that pattern features derived from a calibration pattern and / or describing at least a portion of a calibration pattern that is not fully projected onto the single object can also be used. It may be the case that the calibration pattern is only partially visible on the object, for example, because the calibration pattern extends beyond the area on the object onto which it can be projected. The calibration pattern may, for instance, be divided across multiple objects and / or only partially detectable. Specifically, it is stipulated that at least one pattern feature from this multi-object and / or partially detectable calibration pattern is used to establish at least one of the relationships.

[0046] The advantage of this advanced training is that no requirements are placed on the environment or the object onto which the calibration pattern is projected. In particular, it is not necessary for the entire calibration pattern to be visible. Additionally or alternatively, it is not required that all parts of the calibration pattern maintain a specific distance from the vehicle during headlight calibration.

[0047] Further training includes the requirement that a shape and / or outline of at least one of the pattern features and / or of a pattern area encompassing the respective pattern feature is unique within the calibration pattern. This means, in particular, that the calibration pattern defines areas of varying brightness. At least one of the pattern features and / or one of the pattern areas can exhibit a distribution of lighter and darker areas and / or a shape and / or arrangement of the boundaries between areas of differing brightness that does not occur elsewhere in the calibration pattern. This offers the advantage of enabling unambiguous identification of the pattern feature, even if the calibration pattern is only partially visible and / or detectable, for example, because the calibration pattern extends beyond the object. Additionally or alternatively, further training results in a simple identification of the pattern feature and / or pattern area.

[0048] Further training includes calibration when environmental conditions are detected that would prompt the vehicle to suggest activating glare-free high beams. Specifically, this means that the vehicle will suggest activating glare-free high beams when predefined environmental conditions are present. Activation of glare-free high beams can occur, for example, automatically and / or via a prompt to the driver, such as a display in the vehicle.

[0049] The environmental conditions in question may be those in which the use of high beams is mandatory and / or customary, in particular those in which at least 50% and / or at least 80% of motor vehicles are driving with their high beams on. For example, the environmental conditions may include twilight and / or night situations in which natural brightness has fallen below a predefined threshold, and / or situations in which ambient brightness has fallen below a predefined threshold, and / or situations in which visibility falls below a predefined threshold, for example due to road layout and / or weather conditions.

[0050] The training may stipulate that, upon detection of the described environmental conditions, the headlight is calibrated, and only then is the activation of the glare-free high beam offered and / or carried out. Additionally or alternatively, the glare-free high beam can be activated with a predefined safety zone while the calibration is taking place, and / or the calibration can begin with the activation of the glare-free high beam, with the safety zone being reduced after calibration.

[0051] One advantage of this advanced training is that calibration provides a precise orientation of the headlight relative to the vehicle. This allows the aforementioned safety zone for the glare-free high beam to be kept small—for example, a border with a maximum angular thickness of 10°, 5°, or 3° around the solid angle in which the other road user is located and / or in which the other road user has been detected. This ensures, for example, good visibility for the driver. In particular, calibration immediately before switching on the glare-free high beam can prevent dazzling other road users while simultaneously ensuring the largest possible illuminated area.The method according to the invention provides a simple, effective and quick method by which calibration can be carried out in the short term, so that the functionality of the glare-free high beam can be used effectively.

[0052] Further development includes the requirement that at least one headlight emits light in the form of the calibration pattern, instead of at the very edge of the light cone emitted by the headlight when the low beam and / or high beam is activated. For example, the headlight may include an operating mode for normal use in which it emits a normal light cone. The normal light cone is, in particular, the light cone emitted when the low beam and / or high beam is activated. The normal light cone in operating mode is specifically based on legal regulations, specifications, and / or manufacturer's data.Additionally, the headlight may include a calibration mode in which a peripheral area of ​​the normal light cone, as emitted by the headlight in operating mode, exhibits a different brightness and / or light distribution than would be present in the normal light cone at that peripheral level. This different distribution forms the calibration pattern. The calibration mode is specifically activated only during headlight calibration. At all other times, either the operating mode may be activated and / or the headlight may be deactivated, meaning that the headlight emits no light. The peripheral area may, for example, comprise a maximum of 20%, 10%, or 5% of the cross-sectional area of ​​the normal light cone.The outermost area forms, in particular, the outermost part of the light cone (normal light cone), i.e., the area of ​​the cross-section of the light cone (normal light cone) to which no further area of ​​the light cone adjoins. An advantage of this advanced training is, for example, that calibration is possible even when the headlight must be activated and / or the driver wants to activate it. In particular, the headlight can also be used during calibration, for example, to illuminate a road and / or to ensure a predetermined level of visibility for the driver.

[0053] For use cases or application situations that may arise during the procedure and are not explicitly described here, it may be provided that, according to the procedure, an error message and / or a request for user feedback is issued and / or a default setting and / or a predetermined initial state is set.

[0054] As a further solution, the invention comprises a system comprising a camera and at least one spotlight, wherein the camera and the at least one spotlight have a fixed position relative to each other, and wherein the system is configured to carry out the method according to the invention.

[0055] As a further solution, the invention comprises a motor vehicle comprising a system comprising a camera and at least one headlight, wherein the camera and the at least one headlight have a fixed position relative to each other, wherein the motor vehicle is configured to carry out the method according to the invention.

[0056] Further development of the motor vehicle includes the requirement that the camera is one that provides image data for at least one driver assistance system. For example, it could be a camera oriented in the direction of travel of the vehicle.

[0057] The motor vehicle according to the invention comprises in particular an adjustment device for setting the orientation of a headlight.

[0058] Additionally or alternatively, the motor vehicle may have a data processing device or a processor circuit configured to perform an embodiment of the method according to the invention. For example, the data processing device or the processor circuit may be configured to determine the orientation of the headlight by determining the rotation matrix. For this purpose, the processor circuit may comprise at least one microprocessor and / or at least one microcontroller and / or at least one FPGA (Field Programmable Gate Array) and / or at least one DSP (Digital Signal Processor). In particular, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an NPU (Neural Processing Unit) may be used as the microprocessor.Furthermore, the processor device can include program code configured to execute the embodiment of the method according to the invention when executed by the processor device. The program code can be stored in a data memory of the processor device. The processor device can be based, for example, on at least one circuit board and / or on at least one SoC (System on Chip).

[0059] The invention also includes further developments of the system and the motor vehicle according to the invention, which have features already described in connection with the further developments of the method according to the invention. For this reason, the corresponding further developments of the system and the motor vehicle according to the invention are not described again here.

[0060] The motor vehicle according to the invention is preferably designed as a motor vehicle, in particular as a passenger car or truck, or as a passenger bus or motorcycle.

[0061] As a further solution, the invention also includes a computer-readable storage medium comprising program code which, when executed by a computer or a computer network, causes it to execute an embodiment of the method according to the invention. The storage medium can be provided at least partially as a non-volatile data storage medium (e.g., as flash memory and / or as an SSD - solid state drive) and / or at least partially as a volatile data storage medium (e.g., as RAM - random access memory). The storage medium can be located within the computer or computer network. However, the storage medium can also be operated, for example, as an app store server and / or cloud server on the internet. The computer or computer network can provide a processor circuit with, for example, at least one microprocessor.The program code can be provided as binary code, assembly code, source code in a programming language (e.g., C), or a program script (e.g., Python). Alternatively, the computer-readable storage medium can be implemented as a signal containing computer-readable data, such as a time-varying voltage signal or a radio signal.

[0062] The invention also includes combinations of the features of the described embodiments. The invention therefore also includes realizations that each exhibit a combination of the features of several of the described embodiments, provided that the embodiments have not been described as mutually exclusive.

[0063] The following are exemplary embodiments of the invention described. This is illustrated by: Fig. 1 an exemplary embodiment of the motor vehicle according to the invention; Fig. 2 two exemplary embodiments of the calibration pattern according to the invention; Fig. 3 a schematic representation of the method according to the invention; Fig. 4 a schematic representation of the method according to the invention.

[0064] The exemplary embodiments described below are preferred embodiments of the invention. In these exemplary embodiments, the described components each represent individual features of the invention, which can be considered independently and each further develops the invention independently. Therefore, the disclosure is intended to include combinations of features of the embodiments other than those shown. Furthermore, the described embodiments can also be supplemented by further features of the invention already described.

[0065] In the figures, identical reference symbols denote functionally equivalent elements.

[0066] Fig. Disclosure 1 discloses at least one motor vehicle 10 with at least one headlight 12 and at least one camera 14. A vehicle coordinate system 16 is assigned to the motor vehicle 10, which is fixed relative to the motor vehicle 10. This means, in particular, that regardless of the position, location, and / or direction of the motor vehicle 10, a point on the motor vehicle 10 is always described by the same vehicle coordinates of the vehicle coordinate system 16. Specifically, the position of the headlight 12 and the position of the camera 14 can be described by the vehicle coordinates of the vehicle coordinate system 16. The position of the headlight 12 and the position of the camera 14 are known relative to the motor vehicle 10. Additionally, the orientation of the camera 14 relative to the motor vehicle 10 is known. This means, in particular, that a calibrated camera 14 is present in the motor vehicle 10.

[0067] Just as the vehicle 10 is assigned a camera coordinate system 18, which is fixed relative to the camera 14, so too is the camera 14. This means, in particular, that within the detection range of the camera 14, a definable point is always described by the same camera coordinates of the camera coordinate system 18. Depending on the environment of the vehicle 10 and thus on the objects detected by the camera 14, the definable point within the detection range of the camera 14 can be part of different environment objects. The camera coordinate system 18 is specifically dependent on the orientation of the camera 14 relative to the vehicle 10. Due to the known and constant position of the camera 14 relative to the vehicle 10, the camera coordinate system 18 is fixed relative to the vehicle coordinate system 16.The camera coordinate system 18 can therefore be transformed into the vehicle coordinate system 16 and / or mapped onto the vehicle coordinate system 16, and / or vice versa, in particular by a transformation that is constant and / or unchanged over time.

[0068] Additionally, a headlight coordinate system 20 is assigned to the headlight 12, which is fixed relative to the headlight 12, meaning that the orientation of the headlight coordinate system 20 relative to the vehicle coordinate system 16 and / or relative to the camera coordinate system 18 can depend on the orientation of the headlight 12 relative to the vehicle 10 and / or to the camera 14.

[0069] The headlight 12 can emit light 22 in the form of a light cone 24. The light cone 24 can have areas of varying brightness in its cross-section. For example, there can be areas of higher brightness, which may appear brighter, and areas of lower brightness, which may appear darker. When the light cone 24 and / or the light 22 from the headlight 12 strikes an object 26 in the vicinity of the vehicle 10, a calibration pattern 28 is projected onto the object 26. The calibration pattern 28 is characterized in particular by the fact that it has areas of higher and lower brightness, i.e., areas of varying brightness, as can also be the case in the cross-section of the light cone 24.

[0070] The lighter and darker areas of the calibration pattern 28, that is, the different brightness levels of the calibration pattern 28, allow individual pattern areas 30 to be defined within the calibration pattern 28, which are characterized by a specific and / or predefinable brightness distribution within the pattern area 30, where, for example, a pattern area 30 is Fig. 1 is shown and / or has been identified. In particular, a sample area 30 is a brightness distribution that is unique in the calibration pattern 28. In the sample area 30, at least one characteristic point can be present, which is referred to as a sample feature 32. A sample feature 32 can be a characteristic point in the calibration pattern 28, which is, in particular, uniquely identifiable. Unique identification of the sample feature 32 can be achieved, for example, by the sample feature 32 being a characteristic point in a uniquely occurring sample area 30, wherein a uniquely occurring sample area 30 is a sample area 30 whose brightness distribution is unique for the calibration pattern 28, i.e., whose brightness distribution does not occur again at any other location in the calibration pattern 28. By way of example, in Fig. 1 the apex of a triangle is represented as pattern feature 32, wherein the triangle represents the pattern area 30 and the triangle was projected onto the object 26 by a corresponding brightness distribution of the light.

[0071] It can be provided that the calibration pattern 28 is distributed over the entire cross-section of the light cone 24 emitted by the headlight 12, such that, in particular, selectable pattern features 32, i.e., especially pattern features 32 that are included in a calibration of the headlight 12, are distributed over the entire cross-section of the light cone 24 and / or over the entire calibration pattern 28. By way of example, Fig. Figure 2 above, under reference numeral 281, shows the cross-section of a light cone 24 with a calibration pattern 28 that extends over the entire cross-section of the light cone 24. This means, in particular, that lighter and darker areas occur over the entire cross-section of the light cone 24.

[0072] Additionally or alternatively, the light cone 24 can be subdivided into an inner region 283 and an edge region 284. The edge region 284 can, for example, be a band running along an edge of the cross-section of the light cone 24. An example of such a subdivision of the cross-section of the light cone 24 into the inner region 283 and the edge region 284 is shown under reference numeral 282 in Figure 2. Fig.2 shown below. It may be provided that the inner area 283 is illuminated as is the case during normal use (in an operating mode) of the headlight 12, that is, as is the case, for example, when using the low beam or high beam of the headlight 12. The outer area 284, on the other hand, may have a brightness distribution and form the calibration pattern 28. In particular, it is provided that only pattern features 32 from the outer area 284 are used to achieve calibration of the headlight 12 of the motor vehicle 10.

[0073] The calibration pattern 28 can be projected onto the object 26 in the vicinity of the motor vehicle 10 to determine the orientation of the headlight 12 relative to the motor vehicle 10. This means, in particular, that the headlight 12 emits the light 22 with a brightness distribution corresponding to the calibration pattern 28, and that the light 22 subsequently strikes the object 26 in the vicinity of the motor vehicle 10. No specific requirements are placed on the object 26 in the vicinity of the motor vehicle 10, except that the brightness distribution of the light 22 emitted by the headlight 12 is visible on the object 26. For example, the object 26 does not need to have a flat surface and / or can be located at any distance from the motor vehicle 10 and / or can have a surface structure that prevents it from being considered flat. In particular, it is not necessary to project the complete calibration pattern 28 onto the object 26.Only a part of the calibration pattern 28 can be projected onto object 26.

[0074] The calibration pattern 28 projected onto object 26 can be captured by camera 14. In particular, camera coordinates can be assigned to each pattern feature 32 of the calibration pattern 28. These camera coordinates describe, within the camera coordinate system 18, where the respective pattern feature 32 is located on a camera projection plane 34. This means, in particular, that camera 14 uses these camera coordinates to describe where, within the camera 14's field of view, the respective pattern feature 32 is depicted. Additionally, headlight coordinates are determined for each pattern feature. That is, the camera determines where the respective pattern feature 32 is located within the calibration pattern 28. Both the camera coordinates and the headlight coordinates are normalized coordinates. This makes the camera and headlight coordinates independent of the distance between the vehicle 10 and object 26.

[0075] In addition to the headlight coordinates and camera coordinates for each of the pattern features 32, a translation vector 36 is provided that maps an origin of the camera coordinate system 18 to an origin of the headlight coordinate system 20, or vice versa. The translation vector 36 describes, in particular, how the origin of the camera coordinate system 18 must be shifted to have the same coordinates and / or vehicle coordinates relative to the motor vehicle 10 and / or the vehicle coordinate system 16 as the origin of the headlight coordinate system 20 has in the vehicle coordinate system 16.

[0076] Using the headlight coordinates and the camera coordinates for the various pattern features 32, as well as the translation vector 36, a system of equations is established, whereby a separate relation between the headlight coordinates and the camera coordinates can be formulated for each of the pattern features 32. This relation is, in particular, a relation and / or equation from epipolar geometry known from the prior art and comprising an essential matrix. The relation can describe a ratio of the camera coordinates to the headlight coordinates as a function of the essential matrix. The essential matrix is, in particular, a cross product of the translation vector 36 and a rotation matrix, which can have three unknown rotation angles.The translation vector 36 and the rotation matrix together can describe a coordinate transformation between the camera coordinate system 18 and the headlight coordinate system 20 and / or vice versa. In particular, this means that by combining the translation vector 36 and the rotation matrix, camera coordinates can be represented in the headlight coordinate system 20 and / or headlight coordinates in the camera coordinate system 18. Thus, the rotation matrix specifically describes the orientation of the headlight coordinate system 20 and / or the headlight 12 relative to the camera coordinate system 18 and therefore relative to the vehicle 10.

[0077] The three unknown rotation angles of the rotation matrix are determined using the system of equations. For this purpose, a relation is established for each pattern feature 32, which might look like this, for example: pc→TEph→=0, where pc→ a vector that describes the camera coordinates of exactly one of the pattern features 32, ph→ a vector that describes the headlight coordinates of the same pattern feature 32, and E is the essential matrix. The essential matrix can be given by a cross product between the translation vector 36 and the rotation matrix.

[0078] The relations together form the system of equations, where each relation can have exactly three unknowns, namely the three rotation angles of the rotation matrix. In particular, each relation in the system of equations has the same unknowns. The system of equations can be a nonlinear system, which can be solved, for example, using a nonlinear optimization approach. An example of a nonlinear optimization approach is the Levenberg-Marquard algorithm, as known from the prior art.

[0079] Knowing the three rotation angles of the rotation matrix, which can be determined by solving the system of equations, the rotation matrix can be calculated. From the rotation matrix, a relative orientation of the spotlight coordinate system 20 to the camera coordinate system 18 is then determined, from which the relative orientation of the spotlight 12 can be derived.

[0080] The various pattern features 32 for the different relations of the single system of equations can originate from calibration patterns 28 recorded and / or captured by the camera 14 at different times, which were projected onto different objects 26 and thus exhibited different distances to the motor vehicle 10 when captured by the camera 14. Additionally or alternatively, different pattern features 32 can describe different characteristic points in the calibration patterns 28.

[0081] It may be provided that the calibration of the headlight 12 takes place when activation of a glare-free high beam by the motor vehicle 10 is proposed, in particular because for the glare-free high beam a particularly precise knowledge of the orientation of the headlight 12 relative to the motor vehicle 10 is required.

[0082] Camera 14 is specifically a mono camera. Additionally or alternatively, camera 14 may be a camera that provides images for at least one driver assistance system.

[0083] A particularly preferred embodiment is described below.

[0084] Headlight calibration, particularly dynamic headlight calibration, can be performed using a monocular camera. This requires a calibrated camera and / or a known projection model of the headlight that can control and / or influence the headlight's light distribution, and / or a known position of the headlight relative to the vehicle, and / or a known calibration pattern generated by the headlight. The calibration pattern, which can be generated by the headlight and whose projection onto an object can be captured by the camera, allows for the correlation of at least one pattern feature (a feature of the calibration pattern) between an image captured by the camera and the calibration pattern.

[0085] The vehicle may be moving through its surroundings. The camera can capture the calibration pattern generated by the headlight, either completely or partially (parts of the calibration pattern), as a projection onto at least one object in the environment. In particular, the projection pattern can be displayed on various objects while the vehicle is moving, allowing the camera to capture projections of the calibration pattern and / or parts of the calibration pattern onto different objects and / or objects at varying distances from the vehicle. These objects could include, for example, a wall, a road, a pillar, or another vehicle (stationary and / or moving).

[0086] The headlight serves primarily as a projection unit, and the camera (front camera) can be used to display the calibration pattern.

[0087] A distinction can be made between the camera coordinate system, which can be converted into a vehicle coordinate system using the calibrated camera (thus revealing the headlight's position within the camera coordinate system), and the headlight coordinate system, in which the headlight's orientation can be known. The primary goal is to determine the headlight's orientation relative to the camera coordinate system. For this purpose, three rotation angles can be determined using a rotation matrix.

[0088] Distortions in the optical systems (camera and / or spotlight) can be compensated. After compensation, a pinhole camera model known from the prior art can be used for the camera and / or a central projection model known from the prior art for the spotlight, where the projection center of the spotlight can form the origin of the spotlight coordinate system. The camera and the spotlight can thus be similar models of perspective projection.

[0089] At least one pattern feature corresponding to the calibration pattern can be extracted from at least one image captured by the camera. Specifically, correspondences between the pattern feature from the camera image and the pattern feature from the calibration pattern are determined. This matching is also possible even if the camera only captures a portion of the calibration pattern.

[0090] Correspondences can be determined for different scenarios, for example, for projections of the calibration pattern onto various objects and / or for projections of the calibration pattern onto objects at different distances from the vehicle. A correspondence specifically represents the assignment of headlight coordinates to camera coordinates and / or vice versa to a single pattern feature. Using these different scenarios results in a particularly accurate calibration outcome.

[0091] The orientation (alignment) of the headlight in the camera coordinate system can be determined using at least one, and in particular at least three, epipolar equations known from the prior art: p→cTEp→h=0

[0092] This includes p→c, p→h Normalized coordinates of the same pattern feature, once in camera coordinates and once in spotlight coordinates. This means, p→c, p→h These are normalized coordinates of the correspondences in the camera coordinate system and the spotlight coordinate system. E = T x R is the essential matrix with the translation vector t→=(txtytz) and with the rotation matrix R, which together describe a coordinate transformation between the spotlight coordinate system and the camera coordinate system and / or vice versa (and / or between the spotlight coordinates and the camera coordinates and / or vice versa), where the rotation matrix depends on three unknown rotation angles: R = R(γ,p,r) with the rotation angles yaw (γ), pitch (p), roll (r). Alternatively, the designations ψ, θ, ϕ can also be used for the rotation angles y, p, r.

[0093] T x is given in particular by: Tx=(0−tztytz0−tx−tytx0) The following relationship results in particular: p→cTTxR(γ,p,r)p→h=0 For each of the pattern features, where the relation can be a nonlinear equation with three variables, describing a single feature correspondence (a single pattern feature) and which can be created for different pattern features (feature correspondences). For n correspondences, one obtains, in particular, n equations and / or relations. For n > 3, an overdetermined nonlinear system of equations with three unknown rotation angles may exist.

[0094] The system of equations can be solved using a known nonlinear optimization method, for example, the iterative Levenberg-Marquardt algorithm.

[0095] Overall, the examples show how dynamic headlight calibration can be provided using a mono camera in a moving vehicle.

Claims

[1] Method for calibrating a headlight (12) of a motor vehicle (10), wherein the motor vehicle (10) comprises at least one camera (14) whose position and orientation relative to the motor vehicle (10) is known, and the motor vehicle (10) comprises the at least one headlight (12) whose position on the motor vehicle (10) is known, characterized by , that a. the headlight (12) emits light (22) and generates a light-based calibration pattern (28) which includes at least one pattern feature (32) and which is projected onto an object (26) in the vicinity of the motor vehicle (10), b. for different projections of at least one pattern feature (32), a mapping of the respective pattern feature (32) onto a camera projection plane (34) in a camera coordinate system (18) and a mapping of the respective pattern feature (32) onto a spotlight projection plane in a spotlight coordinate system (20) are determined by evaluating at least one image taken by the camera (14) and determining a relative position of the pattern feature (32) in the calibration pattern (28), c. from the known position of the camera (14) and the known position of the spotlight (12) a translation vector (36) between an origin of the camera coordinate system (18) and an origin of the spotlight coordinate system (20) is determined, d. from several relations forming a system of equations, a rotation matrix is ​​determined which, together with the translation vector (36), describes a coordinate transformation between the camera coordinate system (18) and the spotlight coordinate system (20) by establishing an essential matrix for each of the different pattern features (32) comprising one of the relations between the camera coordinates of one of the pattern features (32) and the spotlight coordinates of the same pattern feature (32) via an epipolar equation, wherein the essential matrix depends on the rotation matrix and the translation vector (36), and e. the relative orientation of the headlight (12) to the known orientation of the camera (14) is determined using the determined rotation matrix. [2] Method according to claim 1, wherein a. the essential matrix is ​​calculated as a cross product of the translation vector (36) and the rotation matrix, b. one of the relations is established by multiplying a camera vector describing the camera coordinates from one side to the essential matrix for one of the pattern features (32), and by multiplying a headlight vector describing the headlight coordinates from another side to the essential matrix for the same pattern feature (32), and by setting the resulting product equal to zero. c. for different pattern features (32) a relation is established, wherein the totality of the relations forms a nonlinear system of equations, and d. the nonlinear system of equations is solved using a solution approach for nonlinear optimization. [3] Method according to one of the preceding claims, wherein the method is carried out during a journey of the motor vehicle (10) such that at least two different pattern features (32) which are incorporated into the same determination of the same rotation matrix were captured at different times and projected by the headlight (12) onto different objects (26) of the environment and / or captured by the camera (14) onto different objects (26) of the environment. [4] Method according to any of the preceding claims, wherein the method is carried out regardless of the degree of flatness of the object (26) onto which at least part of the calibration pattern (28) is projected, and / or regardless of whether the entire calibration pattern (28) is projected onto the object (26). [5] Method according to any of the preceding claims, wherein a shape and / or an outline of at least one of the pattern features (32) and / or at least one pattern area (30) encompassing the pattern feature (32) is unique in the calibration pattern (28). [6] Method according to one of the preceding claims, wherein calibration is carried out when ambient conditions are detected in which activation of a glare-free high beam (22) by the motor vehicle (10) is proposed. [7] Method according to one of the preceding claims, wherein the at least one headlight (12) emits light (22) in the form of the calibration pattern (28) in a peripheral region (284) of a light cone (24) emitted by the headlight (12) when the low beam and / or high beam is activated, instead of the peripheral region (284) of the light cone (24). [8] System comprising a camera (14) and at least one spotlight (12), wherein the camera (14) and the at least one spotlight (12) have a fixed position relative to each other, wherein the system is configured to perform a method according to any of the preceding claims. [9] Motor vehicle (10) comprising a system according to claim 8. [10] Motor vehicle (10) according to claim 9, wherein the camera (14) is a camera (14) that provides image data for at least one driver assistance system.

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