Systems and methods for detecting seat belt use by a vehicle passenger

Abstract

According to one aspect, the present description relates to a system (100) for detecting seat belt use by at least one passenger of at least one first vehicle (301). The system comprises detection means configured for acquiring, with linear and / or circular polarization, at least one first polarized image of a field of view of said first vehicle, consisting of a plurality of pixels; and determines at least one n-channel enriched image of said field of view of the first vehicle, n ≥ 1, the enriched image consisting of a plurality of pixels comprising n values, at least one of said values ​​being a polarization value determined from pixel values ​​of said at least one first polarized image. The system further determines, from said at least one enriched image, a seat belt use status of said passenger of the first vehicle. Fig. 1B

Description

Title of the invention: Systems and methods for detecting seat belt use by a vehicle passenger technical field

[0001] The invention relates to systems and methods for detecting whether a passenger in a vehicle, and in particular in a moving vehicle, is wearing a seat belt. Prior art

[0002] In a context where road safety remains a major concern, it is important to address the persistent problem of not wearing seat belts despite the legal requirement. Data from the French National Interministerial Road Safety Observatory (ONISR) in 2019 revealed that nearly 23% of victims of fatalities in vehicles were not wearing their seat belts.

[0003] These alarming figures highlight the need to develop a reliable automatic seat belt monitoring system, with a view to encouraging systematic compliance with this fundamental safety measure, with the primary objectives of contributing to the reduction of the number of road accidents and mitigating their severity.

[0004] There is therefore a need to detect and identify with great precision offences relating to the wearing of the seat belt, e.g., the non-wearing, or incorrect wearing of the seat belt by one or more passengers of a vehicle, and in particular of a moving vehicle.

[0005] Seatbelt wear detection systems exist that are commonly integrated into vehicles, as described in US patent application 2007 / 0195990 [Ref. 1]. However, such in-vehicle systems provide information on seatbelt use only to passengers and can be easily ignored or even deceived. Furthermore, this information is not available to the authorities responsible for supervising seatbelt use and therefore cannot be used for enforcement purposes.

[0006] It is known from patent application WO 2020 / 076264 [Ref. 2] a deep learning method using a processing image received from a license plate recognition system camera LPRS (License Plate Recognition System), for the purpose of informing police units about violations concerning the wearing of seat belts.

[0007] Patent application WO 2012 / 160251 [Ref. 3] describes a system for detecting whether passengers are wearing seat belts from a greyscale image of a vehicle.

[0008] Other known examples of security gate control systems for detecting trespass combine an artificial intelligence method with images from RGB and / or near-infrared (NIR) cameras. These known devices are described, for example, in US patent applications 2016 / 0078306 [Ref. 4] and CN 106709443 [Ref. 5].

[0009] Although the devices described above are designed to detect whether a vehicle passenger is wearing a seat belt, a higher level of performance is always desirable. In particular, a high level of confidence in seat belt detection is required, including under degraded conditions such as, but not limited to, a moving vehicle traveling at high speeds (over 100 km / h), detection at night and / or in adverse weather conditions, or for vehicles with tinted and / or opaque windows.

[0010] One objective of the present description is to propose a new system and a new method enabling the determination of the state of wearing a seat belt by a passenger of a vehicle at rest or in motion with a very high level of confidence, including in degraded conditions. Summary of the invention

[0011] In this description, the term "include" has the same meaning as "include" or "contain," and is inclusive or open-ended and does not exclude other elements not described or depicted. Furthermore, in this description, the term "approximately" or "substantially" is synonymous with (means the same as) a lower and / or upper margin of 10%, for example, 5%, of the respective value.

[0012] According to a first aspect, the present description relates to a system for detecting whether a passenger in at least one vehicle is wearing a seat belt, said system comprising: - detection means configured for the acquisition of at least one first polarized image of a field of view of said at least one first vehicle, the at least one polarized image being made up of a plurality of pixels and being acquired according to a linear and / or circular polarization; - a processing unit configured for: - to determine, from said at least one polarized image, at least one n-channel enhanced image of said field of view of said at least one first vehicle, n > 1, the enhanced image being made up of a plurality of pixels, each pixel comprising n values, at least one of said values ​​being a polarization value determined from pixel values ​​of said at least one first polarized image, - determine, from said at least one enriched image, a state of the wearing of the seat belt by said passenger of said at least one first vehicle.

[0013] The applicant has shown that such a system makes it possible to determine the seat belt wearing status of a vehicle passenger with excellent reliability. This reliability is based on determining, from at least one polarized image of a field of view of said first vehicle, the seat belt wearing status of said passenger.

[0014] For the purposes of this description, an image is defined as a plurality of pixels, each pixel comprising one or more values. An n-channel image is an image consisting of a plurality of pixels, each containing n values. The number n is also called the image depth. A two-channel image is called a two-channel image, and a three-channel image is called a three-channel image. In this description, an image whose number of channels is not specified will be understood as a one-channel image. An n-channel image can always be processed as n one-channel images.

[0015] Thus, in the system according to the first aspect, the enriched image determined by the processing unit contains n channels, that is to say, it is made up of a plurality of pixels, each comprising n values. The number n is greater than or equal to 1, and corresponds to the depth of the enriched image.

[0016] At least one of the n values ​​of each pixel constituting the enhanced image is a value determined from pixel values ​​of said at least one polarized image acquired with linear and / or circular polarization. It is referred to as the "polarization value" in this description. Thus, the enhanced image contains additional information compared to an image acquired by conventional optical detection means, such as, for example, an intensity camera, which is not polarized. Such additional information is related to said at least one polarization value, and its use in determining, from the enhanced image, the status of seat belt use contributes to improving the detection of seat belt use by a vehicle passenger.

[0017] Indeed, the applicant has shown that the detection system described in the first aspect can verify that the passenger's seat belt is correctly fastened, even in degraded conditions, both day and night. The applicant has shown that this capability offered by the system described herein results in particular from the difference between the woven materials from which seat belts are generally made and the clothing worn by passengers.

[0018] Among other advantages, the detection system according to the first aspect can operate in real time, that is to say, it is capable of generating a message of an offense within a predetermined time from the acquisition of said at least one first polarized image, e.g., less than a few minutes, for example, less than approximately 10 minutes, advantageously less than approximately 5 minutes, advantageously less than approximately 3 minutes. The detection system according to the first aspect can also guarantee optimal protection of passenger privacy by strictly adhering to data confidentiality and security standards, for example, by blurring the faces of identifiable individuals in the images. The system can also be compatible with the specific characteristics of all types of vehicles, e.g., passenger cars, light commercial vehicles, vans, and heavy goods vehicles, and allow for monitoring at both low and high speeds.

[0019] According to one or more embodiments, the seat belt wearing status corresponds to the correct wearing, non-wearing, or incorrect wearing of the seat belt by said passenger in at least one vehicle. According to one or more embodiments, the system may simply determine whether the passenger's seat belt is fastened or not. In some embodiments, the system is also capable of detecting incorrect seat belt wearing by the passenger. Incorrect wearing may, for example, correspond to a state in which the upper part of the seat belt is detected below the passenger's shoulder, instead of being detected above it.

[0020] Of course, the system may not be limited to detecting the seat belt wearing status of a single passenger in the first vehicle. According to one or more embodiments, the system's processing unit is configured to determine, from said at least one enhanced image, the seat belt wearing status of one or more passengers in said at least one first vehicle, said one or more passengers being selected from the group comprising a driver, a front passenger, a rear passenger, and combinations thereof.

[0021] According to one or more embodiments, the detection means are configured for the acquisition of at least a first plurality of p polarized images of the field of view of said at least a first vehicle, p > 2, each polarized image being acquired with linear and / or circular polarization. According to one or more embodiments, the acquisition of said at least a first plurality of p polarized images is simultaneous or quasi-simultaneous.

[0022] For the purposes of this description, quasi-simultaneous acquisition means that the images are acquired by said detection means within a time interval of less than approximately 5 ms, for example, less than approximately 3 ms. The first plurality of p polarized images may thus include images acquired simultaneously or quasi-simultaneously.

[0023] The detection means may include one or more optical detectors.

[0024] An optical detector as defined in this description generally comprises an optical detection surface and a lens comprising one or a plurality of optical elements configured to form an image of a scene on the optical detection surface. Each optical detector includes an optical axis defined by said lens. The field of view of an optical detector is the portion of space that the optical detection surface can capture. The field of view is, for example, an angular field of view, defined by the optical axis and a field angle. The field angle is calculated from the focal length of the lens and the size of the detection surface.

[0025] According to the present description, at least one first polarized image acquired by the detection means is acquired with linear and / or circular polarization. According to one or more embodiments, the detection means comprise at least one polarizing filter.

[0026] A polarizing filter configured for acquiring an image polarized with linear polarization may, in a known manner, include a liquid crystal filter. Such a liquid crystal filter includes, by one example, an arrangement of aligned liquid crystals configured to block unpolarized light while allowing polarized light to pass through in a predetermined direction of the filter.

[0027] A polarizing filter configured for the acquisition of an image polarized according to circular polarization may include, for example, in a known manner, a retarder film associated with a linear polarizing filter, and which introduces a predetermined phase shift between the polarization components of the light, thus transforming a linear polarization into a circular polarization.

[0028] The detection means may include a plurality of polarizing filters as defined above, each polarizing filter being able to be associated with an optical detector included in the detection means or with a part of an optical detector, for example a sensor, or a pixel of an optical detector sensor.

[0029] According to one or more embodiments, the detection means configured for acquiring at least a first plurality of p polarized images of the field of view of said first vehicle, p > 2, include a focal plane division polarimetric camera.

[0030] A division of focal plane (DoFP) polarimetric camera is a type of optical sensor capable of capturing polarization information from a scene. In a DoFP polarimetric camera, the image sensor is equipped with a pixel array, where each pixel is subdivided into n subpixels, n > 1, each subpixel being sensitive to a specific polarization of light. This division of the focal plane allows the The camera simultaneously captures multiple polarization components for each point in the scene. This results in an n-channel polarized image.

[0031] According to one or more embodiments, the detection means configured for the acquisition of at least a first plurality of p polarized images of the field of view of said first vehicle, p > 2, comprise a plurality of optical detectors, each optical detector being configured for the acquisition of an image polarized according to a different polarization.

[0032] In embodiments where the detection means comprise a plurality of optical detectors, it is possible for the optical detectors to acquire polarized images of the first vehicle with slightly different fields of view. According to one or more embodiments, the system further comprises image registration means for converting the polarized images acquired by the plurality of optical detectors into a plurality of polarized images of the same field of view of said first vehicle.

[0033] According to one or more embodiments, n > 2 and each pixel of said enhanced image comprises a plurality of polarization values. The enhanced image is thus a multi-channel image, each channel corresponding to a polarization value. Each polarization value is determined from pixel values ​​of said at least one polarized image. Each polarization value may correspond directly to a pixel value of a polarized image, and / or result from a calculation performed from pixel values ​​of the at least one polarized image.

[0034] According to one or more embodiments, at least one polarization value is determined from a linear combination of pixel values ​​of two or more of said polarized images. A linear combination of pixel values ​​of polarized images is understood to mean that the value of each pixel of the enhanced image corresponding to a given point in the field results from said linear combination of the pixel values ​​of said polarized images at the same point in the field. Such a linear combination may, for example, include a sum, difference, and / or multiplication by a constant of pixel values ​​of polarized images.

[0035] According to one or more embodiments, said at least one polarization value is selected from the group comprising: a Stokes parameter, a polarization angle, a degree of polarization.

[0036] According to one or more embodiments, said enhanced image is selected from the group consisting of: a two-layer image in which each pixel includes a value for the polarization angle and a value for the degree of polarization; a two-layer image in which each pixel includes a value for the polarization angle or a value for the degree of polarization and an intensity value independent of the polarization; and a multi-layer image in which each pixel includes a value of the angle of polarization, a value of the degree of polarization, and an intensity value independent of the polarization.

[0037] The Stokes parameters are a set of four known values, S0, S1, S2, and S3, which describe the polarization state of an electromagnetic wave. The parameters are expressed as a function of the total beam intensity, its degree of polarization, and parameters related to the shape of the polarization ellipse. They allow for the description of unpolarized, partially polarized, and fully polarized light.

[0038] One or more Stokes parameters can be calculated in a known manner by linear combination of pixel values ​​from two or more of said polarized images. In exemplary embodiments, a Stokes parameter is chosen from So, Si, or S2, with, for example, So = Io + I90; Si = Io - I90; and S2 = 2I45 - So. Io, I45, and I90 are linearly polarized images with polarization angles equal to α, α+45°, and α+90°, respectively, where α [0, 180[. Of course, the Stokes parameters can be determined by linear combination of pixel values ​​from other polarized images.

[0039] The angle of polarization of light, or degree of polarization, is defined for linearly polarized light as the angle of deviation of the axis of vibration from a reference axis. More precisely, when light is linearly polarized, its vibrations occur in a specific plane, along an axis of vibration. The angle of polarization measures the deviation of the axis of vibration from a reference axis, in a plane perpendicular to the plane of vibration.

[0040] The degree of polarization of light is defined as the proportion of polarized light relative to the total light. The degree of polarization thus indicates the extent to which light is polarized compared to unpolarized light. Completely unpolarized light will have a zero degree of polarization. Completely polarized light will have a maximum degree of polarization. The degree of polarization is, for example, expressed as a percentage, ranging from 0% (unpolarized) to 100% (completely polarized).

[0041] The angle of polarization and the degree of polarization can in particular (but not exclusively) be determined in a known way from the Stokes parameters, and in particular from the parameters So, Si, or S2.

[0042] According to one or more embodiment examples, n >2 and each pixel of said enriched image includes an intensity value independent of polarization.

[0043] According to one or more embodiments, said intensity value is determined from the acquisition of an unpolarized image by an optical detector included in the detection means, said optical detector not being associated with a polarizing filter.

[0044] According to one or more embodiments, said intensity value is determined from pixel values ​​of a plurality of polarized images acquired by the detection means. For example, said intensity value is determined by a sum of pixel values ​​of two orthogonal polarized images from among at least one first polarized image acquired by the detection means. In other embodiments, the intensity value is determined by summing the normalized intensities of all the polarized images from among at least one first polarized image. In still other embodiments, said intensity value is determined by a sum of pixel values ​​of two left-circular and right-circular polarized images.

[0045] According to one or more embodiments, the detection means are configured for the acquisition of at least 3 polarized images of the field of view of said at least one first vehicle, each polarized image being acquired with a different linear polarization. According to one or more embodiments, the polarized images of said at least one first plurality are acquired for polarization angles equal respectively to α, α+45°, and α+90°, where αe [0, 180[. According to one or more embodiments, the polarized images of said at least one first plurality are acquired for polarization angles equal respectively to α, α+45°, α+90°, and α+135°, where αe [0, 180[.

[0046] According to one or more embodiments, the processing unit is configured to trigger the acquisition of said at least one polarized image of the first vehicle's field of view over time, repeatedly, for example, at a given rate. This results in a plurality of acquisitions of said at least one polarized image over time, or a "burst" of acquisitions, each acquisition generating at least one enhanced image from which the status of a passenger's seat belt use can be determined. The acquisitions in the burst of acquisitions may be spaced at the same predetermined interval, for example, less than approximately 1 minute, advantageously less than approximately 30 seconds, advantageously less than approximately 10 seconds, advantageously less than approximately 5 seconds.In some implementation examples, the acquisition burst rate can be controlled according to the vehicle's speed. The higher the speed, the shorter the interval between acquisitions, and conversely, the lower the speed, the longer the interval between acquisitions. The acquisition burst might consist of, for example, between 3 and 20 acquisitions. Such an acquisition burst makes it possible to further robustly determine the seatbelt wearing status of a passenger and / or to determine the seatbelt wearing status of multiple passengers in the vehicle.

[0047] According to one or more embodiment examples, the system is configured to control a plurality of vehicles.

[0048] Thus, according to one or more embodiments, the detection means are configured for acquiring at least one second polarized image of a field of view of a second vehicle. According to one or more embodiments, the detection means may comprise the first optical detector configured for acquiring said at least one polarized image of the first vehicle and at least one second optical detector configured for acquiring at least one second polarized image of a field of view of a second vehicle.

[0049] According to one or more embodiments, when the system is mounted on mobile equipment, e.g., an unmarked traffic control vehicle, the detection means can be configured to acquire at least one polarized image of the first vehicle overtaken on the right (by said control vehicle incorporating the detection system) and / or the first vehicle overtaken on the left and / or a crossing vehicle. When the system is part of fixed equipment intended for monitoring multiple lanes, e.g., highway lanes, the system can, in certain embodiments, contain as many optical devices as there are lanes on the highway, for example, 6 optical detectors for a 3x3 lane highway, 4 optical detectors for a 2x2 lane highway.

[0050] According to one or more embodiments, the system further comprises at least one vehicle illumination source. For example, the vehicle illumination source is configured for near-infrared illumination, beyond a predetermined near-infrared value, for example, beyond approximately 850 nm. The illumination source comprises, for example, an infrared light source and / or may comprise a broad-spectrum source with a high-pass near-infrared filter, i.e., allowing only wavelengths above said predetermined near-infrared value to pass through.

[0051] According to one or more embodiments, the system further comprises a lux meter configured to measure the ambient light intensity. Based on a predetermined light intensity threshold measured by the lux meter, the processing unit can be configured to trigger the activation of the light source.

[0052] In exemplary embodiments, the illumination source is polarized, i.e., the light emanating from the illumination source is polarized. For example, the light emanating from the illumination source may be linearly and / or circularly polarized. For example, the illumination source may produce light in the near-infrared and include a polarizing filter as defined above with reference to the detection means. Polarized light illumination may enable a further improved seat belt detection. In some embodiments, two enriched images can be determined almost simultaneously, one with and the other without vehicle illumination, and the detection of a seat belt wearing status can take into account an enriched image resulting from the subtraction between the image with illumination and the image without illumination.

[0053] According to one or more embodiments, the system further comprises a detection module configured to detect an entry of the vehicle into a control zone and / or an exit of the vehicle from a control zone, the processing unit being configured to trigger and / or stop the acquisition of said at least one polarized image when the first vehicle enters said control zone and / or exits the control zone.

[0054] In the case of a detection system mounted on fixed equipment, the control area can be, in exemplary embodiments, a predetermined control area, for example an area defined by ground detection cables or laser barriers.

[0055] In the case of a detection system mounted on mobile equipment, for example a vehicle, or fixed but configured to be moved, the control zone can be a virtual zone projected onto the ground and defined by optical and / or radar means mounted on the equipment.

[0056] According to one or more embodiments, for example when the detection system according to the first aspect is mounted on mobile equipment, for example a car, said detection module may include a vehicle presence sensor, for example using LiDAR light detection and ranging technology or ToF time of flight technology (according to the abbreviations, respectively, of the Anglo-Saxon expressions "Laser Imaging Detection And Ranging", and "Time of Flight").

[0057] According to one or more embodiments, the system further comprises an identification module for said at least one first vehicle, said identification module being configured for example for the determination of a registration plate for said at least one first vehicle and / or the determination of the type of said at least one first vehicle and / or for the determination of the color of said at least one first vehicle.

[0058] The identification module may, for example, include one or more ANPR (Automatic Number Plate Recognition) systems using technology designed to identify vehicle license plates by means of optical character recognition. The identification module may alternatively or additionally include a system for determining the vehicle type and / or the vehicle color. The identification module can use at least one initial polarized image of a field of view of the vehicle acquired by the detection means. Alternatively or additionally, the identification module can use another image or plurality of images, for example, acquired by a context camera optionally included in the seat belt detection system, according to one or more embodiments of this description.

[0059] According to one or more embodiments, the processing unit includes an artificial intelligence (AI) module configured to determine, from at least one enhanced image, the seatbelt wearing status of said passenger in the first vehicle. According to one or more embodiments, the AI ​​module includes a neural network.

[0060] According to a second aspect of this description, one or more embodiments relate to mobile and / or fixed equipment comprising the seat belt wear detection system as defined in the first aspect. According to one or more embodiments, the equipment comprises at least one mobile part and one fixed part.

[0061] According to one or more embodiments, the mobile equipment which integrates a security wearing detection system according to the first aspect can be an unmarked control vehicle which travels on traffic lanes taking pictures of the vehicles around it.

[0062] According to one or more embodiments, the equipment incorporating a safety-wearing detection system according to the first aspect is fixed. It is configured, for example, to be placed on one or both sides of a road, e.g., on a median strip, a sidewalk, etc. The fixed equipment can be placed above a road, e.g., attached to a traffic light, a highway overpass, etc. Such fixed equipment, according to one or more embodiments, can advantageously be configured to be easily movable.

[0063] According to a third aspect, the present description relates to a method for detecting the wearing of the seat belt by at least one passenger of at least a first vehicle by means of one or more examples of embodiment of a detection system according to the first aspect.

[0064] Thus, one or more embodiments relate to a method for detecting whether at least one passenger in at least one vehicle is wearing a seat belt, said method comprising: - the acquisition of at least one polarized image of a field of view of said at least one first vehicle, the at least one polarized image being made up of a plurality of pixels and being acquired according to a linear and / or circular polarization; - the determination, from said at least one polarized image, of at least one n-channel enriched image of said field of view of said at least one first vehicle, n >1, the enriched image being made up of a plurality of pixels, each pixel comprising n values, at least one of said values ​​being a polarization value determined from pixel values ​​of said at least one polarized image, - the determination, from said at least one enriched image, of a state of the wearing of the seat belt by said passenger of said at least one first vehicle.

[0065] According to one or more embodiments, the method further comprises a step of illuminating said at least a first vehicle, synchronized with the acquisition step.

[0066] According to one or more embodiments, the method further includes the detection of the entry of said at least one first vehicle into a control zone, the acquisition being triggered when said at least one first vehicle enters the control zone.

[0067] According to one or more embodiments, the method further includes the detection of an exit of said at least one first vehicle from the control zone and the cessation of the acquisition following the exit of said at least one first vehicle. Brief description of the figures

[0068] Other features and advantages of the invention will become apparent from the following description, illustrated by the following figures:

[0069] Fig. 1A represents a diagram of an example of a seat belt wearing detection system according to this description;

[0070] Fig. 1B represents a diagram of an example of mobile equipment, in this example a car, equipped with an example of a seat belt wear detection system according to the present description;

[0071] Fig. 2A represents a diagram of an example of mobile equipment, in this example a control vehicle, seen from above, equipped with an example of a seat belt wear detection system according to the present description, and in which several variants for the location of optical detectors of the detection means are illustrated;

[0072] Fig. 2B represents a diagram of an example of mobile equipment, in this example a control vehicle, seen from above, equipped with an example of a seat belt wear detection system according to the present description, and in which several variants for the location of optical detectors of the detection means are illustrated;

[0073] Figure 3A represents a first diagram illustrating, in top view, the control of seat belt wearing by means of a detection system according to the present description, mounted on mobile equipment, in this example a control vehicle;

[0074] Fig. 3B represents a second diagram illustrating, in top view, the control of the wearing of the seat belt by means of a detection system according to the present description, mounted on a mobile equipment, in this example a control vehicle;

[0075] Fig. 3C represents a third diagram illustrating, in top view, the control of the wearing of the seat belt by means of a detection system according to the present description, installed on a fixed piece of equipment;

[0076] Figure 4 illustrates a step diagram of an example of a port detection method. of the seat belt as described herein;

[0077] Fig. 5A represents, by way of illustration, an intensity image of seat belts (polarization independent image), an angle of polarization (AOP) image of the seat belts shown on the intensity image, a degree of polarization (DOLP) image of the seat belts shown on the intensity image;

[0078] Fig. 5B represents, by way of illustration, an intensity image of a conductor of a moving vehicle (polarization independent image), an angle of polarization (AOP) image of the same conductor shown on the intensity image, a degree of polarization (DOLP) image of the same conductor shown on the intensity image;

[0079] Figure 6 illustrates a diagram of a focal plane division polarimetric camera adapted for detection means of a seat belt wear detection system according to the present description. Detailed description

[0080] In the figures, the elements are not shown to scale for better visibility.

[0081] [Fig.1A] shows a diagram of an example of a seat belt wear detection system according to this description, referenced 100 on [Fig.1A], and [Fig.1B] shows a diagram of an example of a mobile equipment 200, in this example a control vehicle, equipped with a seat belt wear detection system according to this description.

[0082] The system 100 illustrated in [Fig. 1A] comprises detection means 110 configured for acquiring at least one first polarized image of a field of view of a first vehicle controlled by the system 100. The system 100 further comprises a processing unit 150 configured to trigger the acquisition of said at least one first polarized image, for example when said first vehicle enters a predetermined control zone. The processing unit 150 is further configured to determine, from said at least one first polarized image, at least one enriched image, and to determine, from said at least one enriched image, a seatbelt wearing status by a passenger of the first vehicle.

[0083] In the embodiment illustrated in [Fig. IA], the detection means 110 comprise one or more optical detectors. According to one or more embodiments, the detection means comprise at least one focal-plane split-polarimetric camera, a schematic of which is shown in [Fig. 6]. A focal-plane split-polarimetric camera is configured for the simultaneous acquisition of a plurality of images polarized according to different linear polarizations, for example, a plurality of 4 images polarized according to 4 linear polarizations, as described in [Fig. 6].

[0084] As illustrated in [Fig.1A], the system 100 can further include one or more elements selected from an illumination source 120, a lux meter 121, a detection module 130, an interface module 140, a modulator-demodulator 141 in order to provide, for example, internet access to the system, and an electrical power source 142 in order to power the system, e.g., a battery.

[0085] The illumination source 120, intended to illuminate one or more vehicles controlled by the system 100, can be configured for near-infrared illumination beyond a predetermined near-infrared value, for example, beyond approximately 850 nm. The illumination source 120 includes, for example, a high-pass near-infrared filter, i.e., allowing only wavelengths above said predetermined near-infrared value to pass through. The lux meter 121 is configured to measure the ambient light intensity. Based on a predetermined light intensity threshold measured by the lux meter 121, the processing unit 150 can be configured to trigger the activation of the illumination source 120.

[0086] The detection module 130 can, for example, be configured to detect the entry and / or exit of a vehicle into a predetermined control zone. The detection module 130 may include one or more vehicle presence sensors. Such sensors may, for example, use LIDAR and / or ToF technology.

[0087] Figure 1B shows a diagram of an example of mobile equipment 200, in this example a control vehicle, equipped with a seat belt detection system as described herein. The detection system mounted on the control vehicle 200 illustrated in Figure 1B may be similar to that shown in Figure 1A. It comprises detection means including, in this example, a camera 110 for acquiring polarized images of vehicles being monitored. by the car 200, for example a polarimetric camera. As illustrated in [Fig. 1B], the camera 110 can be fixed, for example, on a bracket mounted on the roof of the car 200, as can an illumination source 120 and a lux meter 121 as described above. In one embodiment, the system may further include a vehicle detection module comprising two vehicle presence sensors 130, which can be placed at the front and rear of the vehicle 200 as shown in [Fig. 1B].

[0088] Generally, the processing modules, processing units, or control units referred to in this description may comprise one or more physical entities and be housed in one or more computers. Where reference is made in this description to calculation or processing steps for the implementation of process steps, it is understood that each calculation or processing step may be implemented by software, hardware, firmware, microcode, or any appropriate combination of these technologies. When software is used, each calculation or processing step may be implemented by computer program instructions or software code.These instructions can be stored or transmitted to a storage medium readable by the processing unit and / or executed by the processing unit in order to implement these calculation or processing steps.

[0089] The processing unit 150 can, for example, be part of a computer that may also integrate a modem 141. The modem 141 can allow the computer to access online resources and / or resources stored in a cloud or data cloud. An interface module 140 can optionally be integrated into the driver's compartment of the vehicle 200 and provide an interface between an operator and the seat belt detection system. For example, the interface module 140 can, among other things, allow the operator to manually trigger the acquisition of polarized images or context images of vehicles being monitored, or to activate or deactivate the illumination of vehicles by the illumination source 120.

[0090] The system embedded on a mobile device may have its own source of electrical power 142, as illustrated in [Fig.1A] and [Fig.1B], or alternatively be powered by electricity from said mobile device, in cases where the latter has a battery.

[0091] Figure 2A shows a diagram of an example of mobile equipment 200, in this example a control vehicle, seen from above, equipped with an example of a seat belt wear detection system according to this description, and illustrating several variants for the location of optical detectors 110 of the detection means. The optical detectors 110A, 110B, HOC and 110D In this example, the cameras are configured for acquiring polarized images of vehicles to be monitored. The detection system can include one or more of the 110A to 110D cameras, whose positions illustrate variations depending, for example, on the driver's seat position (i.e., right-hand or left-hand), which varies by country. As mentioned above, according to one or more embodiments, the system can be configured to detect seat belt use by one or more passengers selected from the group comprising a driver, a front passenger, a rear passenger, and combinations thereof. Furthermore, the system can be configured to monitor a plurality of vehicles, for example, vehicles being overtaken, vehicles overtaking, and / or vehicles crossing paths.The number, axis direction, and position of the optical detectors 110 can therefore be fixed in a predetermined manner, according to requirements, for example, in view of the constraints related to the country in which the inspection is carried out. According to one or more embodiments, the axis of the optical detectors is adjustable, for example, during inspection at high speed. An operator can adjust the axis of at least one optical detector via, for example, the interface module 140 described above.

[0092] Figure 2B shows a diagram of an example of mobile equipment 200, in this example a control vehicle, viewed from above, equipped with an example of a seat belt detection system as described herein, and illustrating several variants for the location of optical detectors 170 of the detection means. Optical detectors 170A and 170B, unlike optical detectors 110A-110D illustrated in Figure 2A, are not configured for acquiring polarized images of vehicles to be monitored, but are optionally included in the detection means in order to acquire context images of the potential infraction scene.Such context images, independently of the polarized images acquired by optical detectors 110, or according to one or more variants, in addition to said polarized images, can be used by the detection system to detect and identify monitored vehicles by determining, for example, the license plate, type, and / or color of a monitored vehicle. The detector(s) 170 can, for example, be placed in a central position relative to the width of the monitoring vehicle 200 in order to acquire context images for detecting and identifying monitored vehicles. In the example illustrated in [Fig. 2B], two optical detectors 170A and 170B are advantageously placed at the front and rear of the roof of the monitoring vehicle 200, in order to acquire context images of monitored vehicles respectively overtaking (or crossing) and overtaken.

[0093] As illustrated in [Fig. 3A] and [Fig. 3B], the seatbelt wear detection system according to this description can, for example, be integrated into a vehicle of unmarked control 200 which travels on traffic lanes taking pictures of the vehicles 301, 302 that surround it. Alternatively, the detection system can be installed on fixed equipment, as in the particular example of fixed equipment illustrated in [Fig.3C].

[0094] In some embodiments (not shown), the detection system can be integrated both into a fixed part of a piece of equipment and into a moving part of the same equipment.

[0095] As indicated above with reference to [Fig.2A], the means of detection may vary, for example depending on the type of equipment integrating the system which is envisaged.

[0096] According to one or more embodiments, when a mobile equipment is used, for example a control vehicle 200 traveling on one or more traffic lanes as illustrated in [Fig.3A] and [Fig.3B], the detection means of the system may include one or more optical detectors, e.g., among those 110A-110D shown in [Fig.2A], positioned so as to optimize the acquisition of polarized images of fields of view of vehicles 301, 302 in the vicinity of said control vehicle 200.

[0097] Figure 3A represents a first diagram illustrating, in top view, the control of seat belt use by means of a detection system according to the present description, mounted on a mobile device 200, in this example a control vehicle. In Figure 3A, the control vehicle 200 is traveling on a lane 32 of a 2x2 highway 30 (31, 32, 33, 34), and is in a configuration enabling it to control both an overtaken vehicle 301 traveling in the slow lane 31 in the same direction of travel as lane 32, and an oncoming vehicle 302 traveling in the fast lane 33 in the opposite direction.

[0098] Figure 3A further illustrates two control zones 131, 132, delimited by dashed lines. Such zones, in the case of a mobile unit 200, are relative to the control vehicle 200 in that they vary in space with respect to the movement of the mobile unit. When the controlled vehicles 301, 302 enter these zones, the processing unit of the detection system triggers the acquisition of polarized images of the fields of view of the controlled vehicles.

[0099] Figure 3B shows a second diagram illustrating, in top view, the control of seat belt use by means of a detection system according to this description, mounted on a mobile device 200, in this example a car. The control vehicle 200 shown in Figure 3B may be the same as or different from the one shown in Figure 3A.

[0100] In [Fig. 3B], the control vehicle 200 is travelling on a lane 32 of motorway 30 which has 3x3 lanes, of which only 4 are shown (31, 32, 33, 34), and is located in a configuration allowing it to control both an overtaken vehicle 301 and an overtaken vehicle 302, travelling, respectively, on the slow lane 31 and on the fast lane in the same direction of travel as lane 32, which in this example is the middle lane of the 3 lanes (31, 32, 33).

[0101] The optimization of the acquisition of polarized images of the fields of view of vehicles 301, 302 near the control vehicle 200 can, for example, be based on the proximity of an optical detector of the detection means to the driver's seat of one or more vehicles being monitored. The shorter the distance between the optical detector and the driver's seat of the vehicle being monitored, the more the reliability of the detection system can be considered optimized for detecting, as a priority, whether a driver is wearing a seat belt. Of course, the optimization of the positioning of one or more optical detectors of the detection means can also be carried out to detect, as a priority, whether a passenger other than the driver is wearing a seat belt.

[0102] In the exemplary case illustrated in [Fig.3A], two cameras having orientations such as those of the optical devices 110B and HOC of [Fig.2A] were placed on the roof of the control vehicle 200, in order to optimize the acquisition of images of the driver of overtaken vehicles such as vehicle 301, or crossing vehicles such as vehicle 302.

[0103] In the exemplary case illustrated in [Fig.3B], two cameras having orientations such as the optical devices 110C and 110D of [Fig.2A] were placed on the roof of the control vehicle 200, in order to optimize the acquisition of images of the driver of overtaken vehicles such as vehicle 301, or overtaking vehicles such as vehicle 302.

[0104] Of course, the detection means of the on-board system of the control vehicle 200 may include fewer or more optical devices than those of [Fig. 2A], [Fig. 2B], and [Fig. 3A], [Fig. 3B], [Fig. 3C], with identical or different positions. It should be noted, for example, that the configurations illustrated in [Fig. 3A] and [Fig. 3B], which aim to optimize the detection of seatbelt use by the driver of the controlled vehicles, are adapted when the driver's seat is on the left (as in Germany, France, etc.), and not when the driver's seat is on the right (as, for example, in India, Japan, the United Kingdom, etc.).

[0105] The system according to the first aspect of this description can also be integrated into fixed equipment, intended for example to be placed on one side, or on both sides of a road, e.g., on a median strip, a sidewalk, etc.

[0106] Figure 3C shows a third diagram illustrating, in top view, the control of seat belt use by means of a detection system according to this description, installed on a fixed piece of equipment 400. The example of fixed equipment 400 The device illustrated in [Fig. 3C] is located on the central reservation 34 of a 3x3 lane motorway 30, of which only 3 lanes are shown (31, 32, 33). Positioned in this way, the device 400 can prioritize the checking of passengers in a vehicle 302 traveling on the motorway 33. The fixed device can take any form suitable for detecting seat belt use, for example, the form of a speed radar. The fixed device can be adapted to the specific characteristics of all types of vehicles to be checked. For example, in order to check heavy goods vehicles (HGVs), at least one optical device included in the system's detection means can be mounted at a minimum height, for example, greater than 2 m, greater than 3 m, greater than 4 m, or greater than 5 m.The fixed equipment and / or all or part of the system's detection means being integrated therein, may in certain embodiments be placed above one or more traffic lanes, e.g., attached to a traffic light, a motorway bridge, etc.

[0107] According to one or more embodiment examples, the fixed equipment can be advantageously configured to be easily movable, for example to avoid its degradation or to facilitate its maintenance or redeployment in order to prioritize a new area to be controlled.

[0108] Figure 4 illustrates a step diagram of an example of a method for detecting seat belt use according to this description.

[0109] The method described in [Fig. 4] comprises an acquisition step 402 of at least one polarized image of a field of view of a first vehicle, the at least one polarized image being composed of a plurality of pixels and being acquired with linear and / or circular polarization, for example, when the vehicle enters a predetermined control zone. The method further comprises, in accordance with this description, a determination step 403, from said at least one polarized image, of at least one enhanced image as defined above, and a determination step 406, from said at least one enhanced image, of the seatbelt wearing status of a passenger of the first vehicle. Said processing module 403 may incorporate a software function retrieving part or all of the polarized image(s) made available by the detection means.Such treatment is described in more detail below with reference to [Fig.5A] and [Fig.5B].

[0110] As illustrated in [Fig. 4], the method may include a detection step 401 of the first vehicle in the control zone. This (optional) step may, for example, be carried out by one or more detection modules 130 described above with reference to Figs. 3A and 3B, and configured to detect an entry and / or exit of a vehicle from said control zone.

[0111] Once produced, at least one enhanced image can be made available to a seat belt status determination module 406. Module 406 can determine, or contribute to determining, from the at least one enhanced image, the seat belt status of the passenger in the first vehicle. For example, module 406 can be configured to detect, from the at least one enhanced image, a vehicle, a vehicle passenger, and / or a seat belt covering the surface of a vehicle passenger.

[0112] Module 406 integrates, for example, an artificial intelligence (AI) module. Module 406 may advantageously include one or more neural networks.

[0113] The neural network(s) may, for example, be convolutional neural networks such as those described, e.g., in the article by J. Redmon et al. [Ref. 6]. A convolutional neural network is a mathematical function consisting of successive layers of sub-functions called neurons. The neural network takes as input a vector consisting of the intensity values ​​of each pixel in an image to be analyzed. The network can successively apply filtering (or "activation") operations to all the pixels provided to it. The activation of each neuron determines a "weight" that has been previously determined by learning; a weight is a synaptic coefficient that establishes contact between two neurons above a certain threshold.The weight can then determine a value of the image associated with a label, for example: "seat belt", "vehicle", "truck", "passenger", "van", "vehicle brand", "passenger shoulder", "driver", "child", etc.

[0114] According to one or more embodiments, the weights of the neurons in the network are determined through supervised learning of the neural network. This learning involves feeding a large quantity of labeled images into the network, for example, thousands or millions, which allows the network to adjust these weights. According to one or more embodiments, the AI ​​module uses a deep learning technique, an algorithm employing image processing techniques, solid-state scanning (SSD), multiple convolutional neural networks, and combinations thereof.

[0115] Thus, in exemplary embodiments, the network can successively perform calculations on all the values ​​provided to it. Each neuron calculates the features using the "weights" previously determined by learning, then introduces all the information associated with the features into the feature fusion layer and classifies them. The weights can then determine the image values ​​associated with the labels, for example, "person," "person wearing a seatbelt," "person not wearing a seatbelt," etc. According to one exemplary embodiment, as described above, the The network's weights are determined through supervised learning. This learning process involves feeding thousands of labeled images into the network to allow it to adjust the weights. In this way, the step of determining whether a seatbelt is worn in each enhanced image of each enhanced image series identifies one or more people and their coordinates within the images, and whether they are wearing a seatbelt.

[0116] The detection method according to this description may optionally include an acquisition step 404 of at least one background image, as illustrated in [Fig. 4]. The at least one background image may, for example, be acquired by one or more optical detectors, such as optical detectors 170A and 170B illustrated in [Fig. 2B], included in the detection means but independent of optical detector(s) configured for the acquisition 402 of the at least one polarized image, e.g., detectors 110A to 110D illustrated in [Fig. 2A].

[0117] At least one background image may be made available to a license plate determination module 405, for example an ANPR (Automatic License Plate Recognition) module, as illustrated in [Fig. 4]. In the illustrated method example, the ANPR module 405 also uses at least one enhanced image. Alternatively or additionally, the ANPR module 405 may also use one or more polarized images from among the at least one polarized image acquired by the detection means.

[0118] More generally, the method may include an identification module 405 comprising one or more elements selected from an ANPR module, a vehicle type determination system, a vehicle colour determination system and / or other vehicle characteristics, and combinations thereof.

[0119] In the method example illustrated in [Fig.4], the LAPI 405 module detects and extracts a license plate from the first vehicle, e.g., its license plate number.

[0120] In the example of a process illustrated in [Fig.4], the information extracted from the AI ​​406 and LAPI 405 modules is made available to a module 407 for generating an offence message.

[0121] Said violation message generator 407 can be configured to generate a violation message containing evidence and / or images of the violation, as well as a means of identifying the offending vehicle, for example, its license plate number. In exemplary embodiments, the generation module 407 receives vehicle position identification data, for example, GPS data, provided for example by the vehicle detection module 401.

[0122] The infringement message thus generated can be sent, for example, to a 408 monitoring system, e.g., a monitoring system for control equipment. The The monitoring system can be independent, or part of the detection system or equipment integrating the detection system.

[0123] Fig. 5A represents, by way of illustration, an intensity image 51 of seat belts (polarization independent image), an angle of polarization (AOP) image 52 of the seat belts shown in intensity image 51, and a degree of polarization (DOLP) image 53 of the seat belts shown in intensity image 51.

[0124] Fig. 5B represents, by way of illustration, an intensity image 54 of a conductor of a moving vehicle (polarization independent image), an angle-of-polarization (AOP) image 55 of the same conductor shown in the intensity image 54, and a degree-of-polarization (DOLP) image 56 of the same conductor shown in the intensity image.

[0125] In exemplary embodiments, the detection system detects incorrect seat belt use by the passenger. Incorrect use may, for example, correspond to a state in which the upper part of the seat belt is detected below the passenger's shoulder, instead of being detected above it.

[0126] The detailed description below gives two illustrative examples of the determination of images in AOP or images in DOLP such as those 52, 55 (AOP) and 53, 56 (DOLP) represented on [Fig.5A] and [Fig.5B].

[0127] According to one or more embodiments, the detection means are configured to acquire three polarized images of the field of view of said first vehicle, each polarized image being acquired with linear polarization. The polarized images (Io, I45, I90) of said at least a first plurality can, for example, be acquired for polarization angles equal to α, α +45°, and α +90°, respectively, where αe [0, 180[. According to one or more embodiments, the processing unit is then configured to determine, from the polarized images (Io, I45, I90), at least three images of the Stokes parameters (S0, S1, S2), where S0 = Io +190; S1 = Io - I90; and S2 = 2I45 - S0. The Stokes parameter S0 in these embodiments corresponds to the intensity value S0 defined above.At least one polarization value among the n values ​​of each pixel constituting the enriched image can then be determined from the Stokes parameter images.

[0128] According to one or more exemplary embodiments, said at least one polarization value is a polarization angle and / or a degree of polarization. For example, the degree of polarization (DOLP) can be determined according to the following formula (1):

[0129] [Math.l] DOLP = ^~~

[0130] in which DOLP e [0, 1].

[0131] As for the polarization angle (AOP), it can for example be determined according to the following formula (2):

[0132] [Math.2] AOP = arctan^f

[0133] in which AOP e [ - 90°, 90°].

[0134] According to one or more embodiments, the detection means are configured to acquire four polarized images of the field of view of said first vehicle, each polarized image being acquired with linear polarization. The polarized images (Io, I45, I90, I135) of said at least one first plurality can, for example, be acquired for polarization angles equal to α, α+45°, α+90°, and α+135°, respectively, where αe [0, 180[. According to one or more embodiments, the processing unit is then configured to determine, from the polarized images (Io, I45, I90, I135), at least three Stokes parameters (S0, S1, S2), where S0 = Io + I90; S1 = Io - 190; and S2 = I45 - 1135. The Stokes parameter S0 in these embodiments corresponds to the intensity value S0 defined above.At least one polarization value among the n values ​​of each pixel constituting the enhanced image can then be determined from the Stokes parameters. In these embodiments, when said at least one polarization value includes or consists of a polarization angle (AOP) and / or a degree of polarization (DOLP), these values ​​can also be determined according to the mathematical formulas (1) and (2) indicated above.

[0135] Figure 6 illustrates a diagram of a focal plane division polarimetric camera adapted for detection means of a seat belt wear detection system according to the present description.

[0136] At least one focal plane-splitting polarimetric camera can be schematically represented as illustrated in [Fig. 6]. Only part 1100 of the camera is shown in [Fig. 6].

[0137] Generally, in a polarimetric focal plane division (DoFP) camera, each pixel 60 of a camera detection surface arranged in a focal plane contains the same number and arrangement of polarizers with different orientations, for example, four polarizers with different polarization angles as in the example illustrated in [Fig. 6], namely 0°, 45°, 90°, and 135°. The polarization state of the incident light can thus be determined. The camera sensor shown in [Fig. 6] comprises four identical pixels 60, and therefore allows the simultaneous acquisition of four polarized images 601, 602, 603, 604 of the field of view of said first vehicle according to four different linear polarizations. These robust and easy-to-use cameras allow for the instantaneous acquisition of a polarimetric image. Furthermore, since the polarizing filters are integrated directly onto the sensor, their properties are very stable, which simplifies their calibration. In the example illustrated in [Fig. 6], the polarizing filters associated with each pixel of the camera sensor are linear polarizers.

[0138] Although described through a number of embodiment examples, the system and method for detecting seat belt use according to the present description include various variants, modifications and improvements which will be obvious to those skilled in the art, it being understood that these various variants, modifications and improvements form part of the scope of the invention as defined by the following claims. References

[0139] Ref. 1: US 2007 / 0195990

[0140] Ref. 2: WO 2020 / 076264

[0141] Ref. 3: WO 2012 / 160251

[0142] Ref. 4: US 2016 / 0078306

[0143] Ref. 5: CN 106709443

[0144] Ref. 6: J. Redmon et al., “You Only Look Once: Unified, Real-Time Object Detection”, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (27-30 June 2016), Section 2 “Unified Detection” DOI: 10.1109 / CVPR.2016. 91

Claims

Demands

1. System (100) for detecting the wearing of seat belts by at least one passenger of at least one first vehicle (301), the system comprising: - detection means configured for the acquisition of at least one first polarized image of a field of view of said at least one first vehicle (301), the at least one first polarized image being made up of a plurality of pixels and being acquired according to linear and / or circular polarization; - a processing unit (150) configured to: - trigger the acquisition of said at least one first polarized image;- determine, from said at least one first polarized image, at least one n-channel enriched image of said field of view of said at least one first vehicle (301), n ​​>1, the enriched image being made up of a plurality of pixels, each pixel comprising n values, at least one of said values ​​being a polarization value determined from pixel values ​​of said at least one first polarized image, - determine, from said at least one enriched image, a state of the wearing of the seat belt by said passenger of said at least one first vehicle (301).;

2. System according to claim 1, wherein: - the detection means (110) are configured for the simultaneous or quasi-simultaneous acquisition of at least a first plurality of p polarized images (601 - 604) of the field of view of said at least a first vehicle, p > 2, each polarized image being acquired according to a linear and / or circular polarization.

3. System according to claim 2, wherein at least one polarization value is determined from a linear combination of pixel values ​​of two or more of said polarized images (601-604).

4. System according to claim 3, wherein said at least one polarization value is selected from the group comprising: a polarization angle, a degree of polarization.

5. A system according to claim 4, wherein said enhanced image is selected from the group consisting of: a bilayer image in which each pixel includes a value of the polarization angle and a value of the degree of polarization; a two-layer image in which each pixel includes a value of the polarization angle or a value of the degree of polarization and an intensity value independent of polarization; and a multi-layer image in which each pixel includes a value of the polarization angle, a value of the degree of polarization and an intensity value independent of polarization.

6. System according to any one of claims 2 to 5, wherein the detection means are configured for the simultaneous acquisition of 4 polarized images of the field of view of said at least one first vehicle (301), according to 4 different linear polarizations, for example, the polarized images (Io, I45, I90, I135) of said at least one first plurality are acquired for polarization angles equal to respectively a, a+45°, a+90° and a+135° in which ae [0, 180[.

7. System according to any one of claims 2 to 6, wherein the detection means comprise a focal plane-splitting polarimetric camera (1100), configured for acquiring said at least a first plurality of p polarized images.

8. System according to any one of the preceding claims, wherein: - n >2 and - each pixel of said enriched image comprises an intensity value (So) independent of polarization.

9. System according to any one of the preceding claims, wherein the detection means are configured for the acquisition of at least one second polarized image of a field of view of a second vehicle (302).

10. System according to any one of the preceding claims, wherein the system comprises a detection module (130) configured to detect an entry and / or exit of said at least one first vehicle (301) from a control zone (131), the processing unit being configured to trigger and / or stop the acquisition of said at least one polarized image when said at least one first vehicle (301) enters said control zone (131) and / or exits the control zone.

11. System according to any one of the preceding claims, wherein the processing unit (150) is configured to trigger the acquisition of said at least one polarized image of the field of view of said at least one first vehicle over time, repeatedly, for example with a given rate.

12. System according to any one of the preceding claims, further comprising at least one illumination source (120) of said at least one first vehicle (301).

13. System according to any one of the preceding claims, further comprising an identification module (405) for said at least one first vehicle, said identification module being configured for example for the determination of a registration plate for said at least one first vehicle and / or the determination of the type of said at least one first vehicle and / or for the determination of the color of said at least one first vehicle.

14. System according to any one of the preceding claims, wherein the processing unit (150) comprises an artificial intelligence (AI) module configured to determine, from at least one enhanced image, the seat belt wearing status of said passenger of said at least one first vehicle (301).

15. Mobile (200) and / or fixed (400) equipment comprising the seat belt wearing detection system (100) as defined in any one of the preceding claims.

16. A method for detecting the wearing of a seat belt by at least one passenger of at least one first vehicle (301), said method comprising: - the acquisition (402) of at least one polarized image of a field of view of said at least one first vehicle (301), the at least one polarized image being composed of a plurality of pixels and being acquired according to linear and / or circular polarization; - the determination (403), from said at least one polarized image, of at least one n-channel enriched image of said field of view of said at least one first vehicle (301), n ​​> 1, the enriched image being composed of a plurality of pixels, each pixel comprising n values, at least one of said values ​​being a polarization value determined from pixel values ​​of said at least one polarized image, - the determination (406), from said at least one enhanced image, of a state of the wearing of the seat belt by said passenger of said at least one first vehicle (301).

17. Method according to claim 16, further comprising an illumination step of said at least a first vehicle, synchronized with the acquisition step (402).

18. A method according to claim 16 or 17, further comprising the detection of an entry and / or exit of said at least one first vehicle (301) from a control zone (131), and the triggering and / or stopping of the acquisition of said at least one polarized image when said at least one first vehicle (301) enters said control zone (131) and / or exits the control zone.

Images