WO2024003110A1

WO2024003110A1 - Method for detecting the overall concavity of a polygonal line

Info

Publication number: WO2024003110A1
Application number: PCT/EP2023/067589
Authority: WO
Inventors: Laura PASCAL; Boris Lugez; Artur MALIGO
Original assignee: Continental Autonomous Mobility Germany GmbH
Priority date: 2022-06-28
Filing date: 2023-06-28
Publication date: 2024-01-04
Also published as: FR3137202B1; FR3137202A1

Abstract

The invention relates to a method for detecting the overall concavity of a polygonal line (L1), which method is characterised in that it comprises at least a first step (E1) of detecting corners which executes an algorithm for simplifying the polygonal line (L1) aimed at limiting the number of points belonging to the polygonal line (L1), the retained points being considered corners, a corner being considered concave if the angle it forms is directed inwards relative to the image acquisition sensor (16); a second step (E2) of detecting noise which executes a noise detection algorithm consisting in identifying the corners of the polygonal line (L1) that are considered to be noise, from among the corners identified during the first step (E1); and a third step (E3) of identifying the overall concavity which consists in successively calculating the area of each of the triangles delimited by a concave-identified corner, the previous corner and the following corner of the polygonal line (L1); if the calculated area is greater than a reference area, the concave-identified corner is considered to be sufficiently concave.

Description

DESCRIPTION

TITLE: Method for detecting a global concavity on a polygonal line

[Technical area]

[1] The present invention relates to the field of detection of target objects delimited by a polygonal line from a cloud of points captured by a three-dimensional data acquisition device, and more particularly to the detection of a concavity global on a polygonal line.

[2] Also, the present invention is particularly suitable for implementation by a computer which equips a vehicle, in particular an automobile.

[State of the prior art]

[3] It is known to equip a motor vehicle with a driver assistance system commonly called by the English acronym ADAS for “Advanced Driver Assistance System”.

[4] Such an assistance system comprises, in known manner, at least one image acquisition sensor which is mounted on the vehicle and which makes it possible to generate a series of images representing the environment of the vehicle.

[5] Generally, the image acquisition sensor is a three-dimensional data acquisition device such as a Lidar (English acronym for “Light Detection And Ranging”).

[6] The acquired images are used by a computer in order to assist the driver, for example by detecting an “object” (pedestrians, stationary vehicle, objects on the road, etc.), and by calculating by example the time before collision with the detected object.

[7] Lidar is an active optical sensor which emits a laser beam along an optical axis of sight in the direction of a target object.

[8] The reflection of the laser beam from the surface of the target object is detected by a receiving surface arranged in the lidar.

[9] This receiving surface records the time between when the laser pulse is emitted and when it is received by the lidar to calculate the distance between the lidar and the object.

[10] The distance measurements collected by the lidar, associated with positioning information, are transformed into measurements of real three-dimensional points of the target object, each image acquired by the lidar forming a set of three-dimensional points, or point cloud , which are considered a sample of a surface. [11] By three-dimensional point we mean a point which is associated with coordinates in space, in a given three-dimensional reference frame.

[12] Also, the surface of the detected objects can be represented by a two-dimensional polygonal line which is formed by a series of successive points, which come from the points collected by the lidar.

[13] We speak of a polygon when the polygonal line is closed.

[14] But generally, an object observed by an image acquisition sensor is not visible in its entirety and will therefore be represented by a polygonal line, and not by a closed polygon.

[15] The points which form the polygonal line are connected by consecutive line segments which each connect two consecutive points of the polygonal line.

[16] Two consecutive straight line segments form a concave angle, or a concave corner, if this angle is re-entrant, from the point of view of the image acquisition sensor, that is to say oriented towards the inside of the object drawn by polygonal line.

[17] Conversely, an angle is convex if it is outward, from the point of view of the image acquisition sensor, that is to say oriented towards the outside of the object drawn by the polygonal line .

[18] Also, it is known to detect a concave angle on a polygonal line in order to differentiate two objects drawn by a common polygonal line.

[19] Indeed, it is important to determine whether the polygonal line represents a single object or several objects, particularly in the field of assistance in driving a motor vehicle, in order to interpret the nature of the target objects correctly.

[20] A concave angle on the polygonal line, that is to say an angle which goes towards the interior of the object, is generally considered as a break between two neighboring objects.

[21] Existing techniques for detecting a concave angle on a polygonal line are local approaches, i.e. the angle is calculated between three consecutive points on the polygonal line.

[22] In other words, with a local approach, the angle is calculated between two consecutive segments of the polygonal line.

[23] A disadvantage of this type of concave angle detection method using a local approach is the risk of errors caused by misinterpretation of a calculated concave angle.

[24] Indeed, a polygonal line can sometimes present a locally concave angle, without this concave angle materializing a break between two neighboring objects. [25] For example, a polygonal line which represents the outline of a truck may include a locally concave angle which materializes the break between the cab and the trailer of the truck, while the cab and the trailer belong to a single object.

[26] Also, it is common to note that certain points of the polygonal line are parasitic points which form noise and which mix with the so-called useful points of the polygonal line representing the target object.

[27] These parasitic points can form concave angles locally which can lead to a misinterpretation of the geometry of the object represented by the polygonal line.

[Disclosure of the invention]

[28] The present invention aims in particular to resolve the drawback of the aforementioned prior art by proposing a method which makes it possible to detect a global concavity on a polygonal line while ignoring local concavities and noise.

[29] This objective, as well as others which will appear on reading the following description, is achieved with a method for detecting a global concavity on a polygonal line, said polygonal line being formed by a series of successive points which are connected two by two by a straight line segment and which come from an image captured by an image acquisition sensor, characterized in that it comprises at least:

• a first corner detection step, which executes a polygonal line simplification algorithm aimed at limiting the number of points belonging to the polygonal line, the retained points being considered as corners, a corner being considered concave if the angle that it forms is re-entrant, from the point of view of said image acquisition sensor, oriented towards the interior of the object drawn by the polygonal line

• a second noise detection step which executes a noise detection algorithm consisting of identifying the corners of the polygonal line considered to be noise, among the corners identified during the first step, and

• a third step of identifying a global concavity, a portion of the polygonal line (L1) which is sufficiently concave to represent a break between two objects, which consists of successively calculating the area of each of the triangles delimited by a corner identified as concave, the previous corner and the following corner of the polygonal line, ignoring the corners identified as being of noise, if the calculated area is greater than a reference area, then said concave identified corner is considered sufficiently concave, and

• if the corner is considered sufficiently concave, then said corner is considered to mark a break between two distinct adjacent objects to be differentiated.

[30] Thus, the method according to the invention makes it possible to detect a sufficiently concave corner which is representative of a break between two objects drawn by the polygonal line.

[31] The reference area can be determined according to the degree of concavity that we wish to detect with the present method.

[32] According to other optional characteristics of the invention, taken alone or in combination:

[33] - the simplification algorithm executed during the first step consists of:

• select the first point, forming a first terminal, and the last point, forming a second terminal, of the polygonal line,

• determine the distal point which is the point of the polygonal line farthest from a first basic straight line segment which connects the first terminal and the second terminal,

• calculate the distance between the distal point and said first base line segment, if said calculated distance is greater than a reference distance, then the distal point is considered to be a corner,

[34] and in that the simplification algorithm is called recursively on sub-parts of the polygonal line, if a corner is found. The reference distance can be determined according to the degree of simplification of the polygonal line that we wish to obtain at the end of the first simplification step;

[35] - during the second stage:

• we measure the length of a second base line segment connecting the first point and the last point of the polygonal line,

• we successively measure the length of a third base line segment connecting the first corner and the last corner of each of the triangles which are delimited by three successive corners of the polygonal line,

• if the length of the second associated base line segment is greater than a first predetermined reference length, and if the length of the third base line segment is less than a second predetermined reference length, then said three successive corners associated with said third base line segment are considered noise. The first reference length and the second reference length are determined according to the desired degree of noise reduction; [36] - the first step is executed again following the second step, ignoring the corners identified as noise during the second step;

[37] - said reference area used during the third step of identifying a global concavity is determined as a function of the length of a fourth basic straight line segment which connects the first corner and the last corner of the polygonal line;

[38] - said reference area used during the third step of identifying a global concavity is equal to:

• a first value if the length of the fourth basic straight line segment which connects the first corner and the last corner of the polygonal line is greater than 8 meters,

• a second value if the length of said fourth base line segment is between 8 meters and 5.5 meters,

• a third value if the length of said fourth base line segment is between 5.5 meters and 2.75 meters,

• a fourth value if the length of said fourth base line segment is between 2.75 meters and 1.5 meters, and

• a fifth value if the length of said fourth base line segment is less than 1.5 meters;

[39] - said first value of the reference area is equal to 1.5 square meters, said second value of the reference area is equal to 0.75 square meters, said third value of the reference area is equal to 0.56 square meters, said fourth value of the reference area is equal to 0.4 square meters, said fifth value of the reference area is equal to 0.3 square meters;

[40] The invention also relates to a computer for a vehicle, in particular an automobile, configured to implement the method described above.

[41] Finally, the invention also relates to a vehicle, in particular an automobile, comprising a computer described above and at least one image acquisition sensor.

[Description of the designs]

[42] Other characteristics and advantages of the invention will emerge on reading the description which follows, with reference to the appended figures, which illustrate:

[43] [Fig. 1] a schematic view of a motor vehicle equipped with a computer which implements the method according to the invention, and a polygonal line connecting several points and drawing a truck and a safety guardrail;

[44] [Fig. 2] a schematic view of the polygonal line of Figure 1 including a distal point; [45] [Fig. 3] a schematic view of the polygonal line of Figure 1 comprising a plurality of corners detected during the first step of the method;

[46] [Fig. 4] a schematic view of the polygonal line of Figure 1 reduced by three corners considered as noise during the second step of the process;

[47] [Fig. 5] a flowchart representing the steps of the process according to the invention.

[Description of embodiments]

[48] Figure 1 shows schematically a truck 10 forming a first object to be detected, a safety guardrail 12 forming a second object, and a motor vehicle 14 equipped with an image acquisition sensor 16 and 'a calculator 17.

[49] The image acquisition sensor 16 is for example a laser remote measurement device known by the English acronym LIDAR for “Light Detection And Ranging”.

[50] Non-limitatively, the image acquisition sensor 16 can be formed by any sensor adapted to generate a cloud of points and to represent objects by a polygonal line.

[51] The truck 10 includes a cockpit 18 and a trailer 20.

[52] With reference to Figure 1, a polygonal line L1 draws a portion of the outline of the truck 10 and a portion of the guardrail 12, seen by the image acquisition sensor 16.

[53] For this purpose, the image acquisition sensor 16 captures three-dimensional points in space which are transformed into image points in a two-dimensional reference frame R(Z,X) visible in Figure 1, these image points allowing to form the polygonal line L1.

[54] Thus, the polygonal line L1 comprises a series of consecutive points, referenced P1 to P18 in Figure 1.

[55] Also, the polygonal line L1 includes a series of consecutive line segments.

[56] We speak of a segment to designate a straight line which connects two successive points of the polygonal line L1, and we speak of successive, or adjacent, segments to designate two segments which have an end point in common and which n They have nothing else in common.

[57] We speak of an angle to designate an angular sector delimited by two successive segments.

[58] An angle can be concave, that is to say entering towards the interior of the object delimited by the polygonal line L1, such as the angle delimited by the points P5, P6, P7.

[59] Conversely, an angle can be convex, that is to say extending outwards from the object delimited by the polygonal line L1, such as the angle delimited by the points P12, P13, P14. [60] The invention relates to a method for detecting a global concavity on a polygonal line, such as the polygonal line L1, with the aim of differentiating adjacent objects.

[61] Indeed, it is expected that an object, in particular an object on a road, is represented by a polygonal line which presents convex portions, that is to say portions which present angles leaving the point of view of the image acquisition sensor 16, such as the shape of the truck 10 illustrated in Figure 1.

[62] Conversely, it is expected that a break, or a separation, between two objects is represented by a portion of the polygonal line which has a concave shape, that is to say a portion which has a re-entrant angle .

[63] We speak of “global” concavity to designate a portion of a polygonal line which is sufficiently concave to represent a break between two objects.

[64] For example, the polygonal line L1 has an overall concavity between the points P5 and P7, a concavity which represents a break between the truck 10 and the safety guardrail 12.

[65] Conversely, a “local” concavity is not interpreted as being a break between two objects.

[66] A local concavity is interpreted as coming from a parasitic point, or as representing a local recess on the contour of one, and only one, object represented by the polygonal line L1.

[67] For example, with reference to Figure 1, the angle formed by the points P15 to P17 is a locally concave angle which materializes the break between the cabin 18 and the trailer 20 of the truck 10 drawn by the polygonal line L1, the cabin 18 and the trailer 20 belonging to the same object.

[68] We will understand that the difference between a local concavity and a global concavity is a difference in scale and interpretation.

[69] The method according to the invention aims to distinguish a local concavity from a global concavity.

[70] For this purpose, the method according to the invention successively comprises a first step E1 of detecting corners on the polygonal line L1, a second step E2 of detecting noise and a third step E3 of identifying an overall concavity , illustrated in Figure 5.

[71] The first corner detection step E1 executes a simplification algorithm of the polygonal line L1 aimed at limiting the number of points belonging to the polygonal line L1, the retained points being considered as corners.

[72] A corner is an angle that can be concave or convex. [73] According to a preferred embodiment of the invention, the simplification algorithm is based on an algorithm known as “Ramer-Douglas-Peucker”.

[74] More particularly, the simplification algorithm executed during the first step E1 consists of selecting the first point P1 of the polygonal line L1, forming a first terminal A1, and the last point P18 of the polygonal line L1, forming a second terminal A2.

[75] As can be seen in Figure 2, the first terminal A1 and the second terminal A2 of the polygonal line L1 are connected by a first straight line segment with base Db1.

[76] Then, still during the first step E1, we determine the distal point Pdist which is the point of the current polygonal line L1 farthest from the first base straight segment Db1, following a direction perpendicular to the first segment of basic line Db1.

[77] After determining the distal point Pdist, represented by the point P13 according to the example illustrated in Figure 2, we calculate the distance Dmax between the distal point Pdist and the first base line segment Db1, this distance Dmax corresponding at the height of the triangle having as its base the first base line segment Db1.

[78] If the calculated distance Dmax is greater than a predetermined reference distance, then the distal point Pdist is considered to be a corner.

[79] Conversely, if the distance Dmax is less than the predetermined reference distance, then the points of the polygonal line L1 remain considered as points.

[80] If a corner is detected during the first step E1, then the simplification algorithm is called recursively on a first sub-part and on a second sub-part of the current polygonal line, until the The simplification algorithm no longer detects corners.

[81] By current polygonal line we mean the polygonal line, or subpart of a polygonal line, which is concerned by the simplification algorithm at a defined instant, since the polygonal line concerned by the simplification algorithm evolves with the recursion of the first step E1.

[82] It will be understood that the value chosen for the reference distance makes it possible to more or less simplify and “smooth” the polygonal line L1.

[83] According to the example illustrated in Figure 2, we consider that the distance Dmax is greater than the reference distance, so that the simplification algorithm is called again on a first sub-part of the polygonal line L1 between the first terminal A1 and the distal point Pdist represented by the point P13 which forms a new second terminal, and on a second sub-part between the distal point Pdist represented by the point P13 which forms a new first terminal, and the second terminal A2.

[84] Calculating the distance Dmax amounts to successively calculating the area A of each of the triangles formed by the first base line segment Db1 and each of the points of the polygonal line L1, the triangle which has the greatest area large determining the distal point Pdist.

[85] The area A of each triangle can be calculated by the following equation:

[87] with A1 the first terminal of the current polygonal line L1, A2 the second terminal of the current polygonal line L1, x the coordinate along the axis Pn the current point of one of the n points of the current polygonal line L1.

[88] Figure 3 shows the corners detected during the first step E1, the corners being represented by square pellets, while the points are represented by round pellets.

[89] Note that a corner is considered concave if the angle it forms is re-entrant, from the point of view of the image acquisition sensor 16.

[90] Also, a corner is considered concave if the area A of the triangle composed of the current point and the first base line segment Db1 is positive.

[91] Following the first simplification step E1, the method according to the invention executes a second noise detection step E2.

[92] The second step E2 executes a noise detection algorithm consisting of identifying the corners of the polygonal line L1 considered to be noise, among the corners identified during the first step E1.

[93] Note that the corners identified as noise are ignored by the following steps of the process.

[94] During the second noise detection step E2, the length of a second base line segment Db2 connecting the first point and the last point of the polygonal line L1 is measured.

[95] According to the exemplary embodiment of the invention illustrated in Figure 3, the second base line segment Db2 joins point P1 and point P18.

[96] Also, we successively measure the length of a third base line segment Db3 connecting the first corner and the last corner of each of the triangles which are delimited by three successive corners of the polygonal line L1.

[97] In other words, during the second step E2, the corners of the polygonal line L1 are traversed in groups of three, each group forming a triangle comprising the third base Qb3. For the sake of clarity, in Figure 3, only the bases Db3 connecting the corners C10 and C12, on the one hand, and C15 and C17, on the other hand.

[98] If the length of the second base line segment Db2 is greater than a first predetermined reference length, and if the length of the current third base line segment Db3 is less than a second predetermined reference length, then the three Successive corners associated with the third current base line segment Db3 are identified as noise.

[99] During the second step E2, all the corners are covered and then each is identified as being noise, or not.

[100] According to the example illustrated in Figure 3, the three corners C10, C11, C12 which correspond to the three points P10, P11, P12 are considered as noise because the length of the second base line segment Db2 is greater than the first predetermined reference length and the length of the associated third base line segment Db3 is less than the second reference length.

[101] Conversely, the three corners C15, C16, C17 which correspond to the three points P15, P16, P17 are not considered as noise because the length of the third associated base line segment Db3 is greater than the second reference length.

[102] The first reference length and the second reference length are defined in relation to the dimensions of the vehicles likely to be crossed on a road.

[103] According to a preferred embodiment of the invention, the second step E2 of the method aims to apply only to large vehicles greater than 2.75 meters in length.

[104] Also, the second reference length can be established at 0.4 meters, for example.

[105] It will be noted that the choice of the first reference length and the second reference length makes it possible to filter more or less the noise present on the polygonal line L1.

[106] Following the second noise detection step E2, the first corner detection step E1 is executed again, then the second occurrence of the first step E1 is followed by the third step E3.

[107] However, without limitation, it is possible to repeat the second noise detection step E2 again following the second occurrence of the first step E1.

[108] The third step E3 of identifying a global concavity is executed by ignoring the corners identified as being noise during the second step E2. [109] The third step E3 consists of successively calculating the area of each of the triangles delimited by three corners of the polygonal line L1, each of the triangles comprising a first corner identified as concave during the first step E1, a second corner which precedes directly said first corner, and a third corner which directly succeeds said first corner.

[110] If the calculated area is greater than a reference area, then said first identified concave corner which is associated with the calculated area is considered sufficiently concave.

[111] The reference area used during the third step E3 is determined according to the length of a fourth base line segment Db4 which connects the first corner and the last corner of the polygonal line L1.

[112] According to the exemplary embodiment of the invention illustrated in Figure 4, the fourth base line segment Db4 joins point P1 and point P18.

[113] According to a preferred embodiment, the reference area used during the third step E3 can take five different values.

[114] A first value if the length of the fourth base line segment Db4 is greater than 8 meters, a second value if the length of the fourth base line segment Db4 is between 8 meters and 5.5 meters, a third value if the length of the fourth base line segment Db4 is between 5.5 meters and 2.75 meters, a fourth value if the length of the fourth base line segment Db4 is between 2.75 meters and 1.5 meter, and a fifth value if the length of the fourth base line segment Db4 is less than 1.5 meters.

[115] Thus, the first value generally corresponds to the length of a large truck, the second value corresponds to the length of a truck, the third value corresponds to the length of a car or a van, the fourth value corresponds to the length of a motorcycle and the fifth value corresponds to the length of an object smaller than a motorcycle.

[116] Also, the first value of the reference area is equal to 1.5 square meters, the second value of the reference area is equal to 0.75 square meters, the third value of the reference area is equal to 0.56 square meters, the fourth value of the reference area is equal to 0.4 square meters, the fifth value of the reference area is equal to 0.3 square meters.

[117] According to the exemplary embodiment of the invention illustrated in Figure 4, we consider that the polygonal line L1 comprises two concave corners, namely the corner C6 and the corner C16.

[118] We also consider that the area of the triangle delimited by the concave corner C6, the directly preceding corner C1 and the directly following corner C7, is greater than the reference area defined as a function of the length of the fourth line segment basic Db4. [119] Consequently, corner C6 is considered sufficiently concave and therefore as marking a break between two objects, here between truck 10 and guardrail 12.

[120] Conversely, we consider that the area of the triangle delimited by the concave corner C16, the directly preceding corner C15 and the directly following corner C17 is less than the reference area defined as a function of the length of the fourth basic line segment Db4.

[121] Consequently, corner C16 is not considered sufficiently concave, it does not mark a break between two distinct objects.

[122] Note that the larger the fourth base line segment Db4, the greater the area of the triangle including a concave corner must be for said corner to be considered sufficiently concave.

[123] According to another aspect of the invention, it will be noted that the computer 17 which equips the automobile vehicle 14 is configured to implement the method according to the invention.

[124] Naturally, the invention is described in the above by way of example. It is understood that those skilled in the art are able to carry out different variants of the invention without departing from the scope of the invention.

Claims

[Claim 1] Method for detecting a global concavity on a polygonal line (L1), said polygonal line (L1) being formed by a series of successive points which are connected two by two by a straight line segment and which come from 'an image captured by an image acquisition sensor (16), characterized in that it comprises at least:

• a first corner detection step (E1), which executes an algorithm for simplifying the polygonal line (L1) aimed at limiting the number of points belonging to the polygonal line (L1), the retained points being considered as corners, a corner being considered concave if the angle it forms is reentrant, from the point of view of said image acquisition sensor (16), oriented towards the interior of the object drawn by the polygonal line,

• a second noise detection step (E2) which executes a noise detection algorithm consisting of identifying the corners of the polygonal line (L1) considered to be noise, among the corners identified during the first step (E1) , And

• a third step (E3) of identifying a global concavity, a portion of the polygonal line (L1) which is sufficiently concave to represent a break between two objects, which consists of successively calculating the area of each of the delimited triangles by a concave identified corner, the previous corner and the following corner of the polygonal line (L1) ignoring the corners identified as noise, if the calculated area is greater than a reference area, then said concave identified corner is considered sufficiently concave, and

[Claim 2] Method according to claim 1, characterized in that the simplification algorithm executed during the first step (E1), consists of:

• select the first point, forming a first terminal, and the last point, forming a second terminal, of the polygonal line (L1),

• determine the distal point (Pdist) which is the point of the polygonal line (L1) furthest from a first basic straight line segment (Db1) which connects the first terminal and the second terminal,

• calculate the distance between the distal point (Pdist) and said first base line segment (Db1), if said calculated distance is greater than one reference distance, then the distal point (Pdist) is considered to be a corner, and in that the simplification algorithm is called recursively on sub-parts of the polygonal line (L1), if a corner is found .

[Claim 3] Method according to any one of the preceding claims, characterized in that during the second step (E2):

• we measure the length of a second base line segment (Db2) connecting the first point and the last point of the polygonal line (L1),

• we successively measure the length of a third base line segment (Db3) connecting the first corner and the last corner of each of the triangles which are delimited by three successive corners of the polygonal line (L1),

• if the length of the associated second base line segment (Db2) is greater than a first predetermined reference length, and if the length of the third base line segment (Db3) is less than a second predetermined reference length, then said three successive corners associated with said third basic line segment (Db3) are considered to be noise.

[Claim 4] Method according to any one of the preceding claims, characterized in that the first step (E1) is executed again following the second step (E2) while ignoring the corners identified as being noise during of the second stage (E2).

[Claim 5] Method according to any one of the preceding claims, characterized in that said reference area used during the third step (E3) of identifying a global concavity is determined as a function of the length of a fourth basic line segment (Db4) which connects the first corner and the last corner of the polygonal line (L1).

[Claim 6] Method according to claim 5, characterized in that said reference area used during the third step (E3) of identifying a global concavity is equal to:

• a first value if the length of the fourth basic straight line segment (Db4) which connects the first corner and the last corner of the polygonal line (L1) is greater than 8 meters,

• a second value if the length of said fourth base line segment (Db4) is between 8 meters and 5.5 meters,

• a third value if the length of said fourth base line segment (Db4) is between 5.5 meters and 2.75 meters, • a fourth value if the length of said fourth basic straight line segment (Db4) is between 2.75 meters and 1.5 meters, and

• a fifth value if the length of said fourth base line segment (Db4) is less than 1.5 meters. said first value of the reference area is equal to 1.5 square meters, said second value of the reference area is equal to 0.75 square meters, said third value of the reference area is equal to 0, 56 square meter, said fourth value of the reference area is equal to 0.4 square meter, said fifth value of the reference area is equal to 0.3 square meter. [Claim 7] Computer (17) for an automobile vehicle (14), configured to implement the method according to any one of the preceding claims. [Claim 8] Motor vehicle (14) comprising a computer (17) according to claim 7 and at least one image acquisition sensor (16).