Authentication system and method for vehicle

Abstract

A method for accessing a vehicle and / or a function of the vehicle, the method comprising: illuminating an object with patterned infrared illumination; -generating at least one patterned image of the object while the object is illuminated by the patterned infrared illumination; -determining whether the subject corresponds to a living human based on the at least one pattern image; and-allowing the subject to access the vehicle and / or a function of the vehicle based on a determination that the subject corresponds to the living human.

Description

Technical Field

[0001] The present invention relates to a non-transitory computer-readable medium, a method for accessing a vehicle and / or functions of the vehicle, a method for performing in-vehicle payments, a system for accessing a vehicle and / or functions of the vehicle, a system for performing in-vehicle payments, a vehicle, the use of the system for accessing functions of the vehicle and / or the vehicle, the use of the system for performing in-vehicle payments, a computer-readable medium, a method for verifying the qualifications of a driver of a vehicle, and a system for verifying the qualifications of a driver of a vehicle. Background Art

[0002] Vehicles should only be started or accessed by people authorized by the vehicle's owner to drive them. Typically, vehicles can be opened and started using a key, regardless of the person using the key. Examples of people who should not be able to control a vehicle include children or thieves. Preventing these people from controlling a vehicle requires reliable and accurate authentication of the person authorized by the vehicle's owner to drive the vehicle.

[0003] Therefore, it is desirable to authenticate qualified individuals who enter, start, and control a vehicle. Summary of the Invention

[0004] Any disclosures, embodiments, and examples described herein relate to the methods, systems, devices, chemical products, and computer elements listed above and below. Advantageously, the benefits provided by any embodiment and example are also applicable to all other embodiments and examples.

[0005] In one aspect, the present disclosure relates to a non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method according to any of the preceding method-related claims.

[0006] In another aspect, the present disclosure relates to a system for performing in-vehicle payments, the system comprising:

[0007] - an input terminal configured to receive a payment request,

[0008] - an illumination source configured to illuminate the object with patterned infrared illumination;

[0009] - an image generation unit configured to generate at least one pattern image of the object while the object is illuminated by patterned infrared radiation;

[0010] - a processor configured to determine whether the object corresponds to a living human being based on the at least one pattern image; and release payment based on determining that the object corresponds to a living human being.

[0011] In another aspect, the present disclosure relates to a method for verifying the qualifications of a driver of a vehicle, the method comprising:

[0012] - illuminating the driver with patterned infrared illumination while the driver is using a function of the vehicle;

[0013] - generating at least one patterned image of the driver while the driver is illuminated by patterned infrared radiation;

[0014] - determining whether the driver is eligible to continue using the vehicle function based on the at least one pattern image; and

[0015] - Based on determining that the driver is eligible to continue using the vehicle's functions, allowing or denying continued use of the vehicle's functions.

[0016] In another aspect, the present disclosure relates to a system for verifying the qualifications of a driver of a vehicle, the system comprising:

[0017] - an illumination source configured to illuminate the driver with patterned infrared illumination while the driver is using a function of the vehicle;

[0018] - an image generation unit configured to generate at least one pattern image of the driver while the object is illuminated by the patterned infrared illumination;

[0019] - a processor configured to determine whether the driver is eligible to continue using the function of the vehicle based on the at least one pattern image; and to allow or deny continued use of the function of the vehicle based on determining that the object corresponds to a living human.

[0020] In another aspect, the present disclosure relates to a computer-readable medium having instructions that, when executed on a processing device, are configured to perform the steps of the method as disclosed herein.

[0021] In another aspect, the present disclosure relates to a method for accessing a vehicle and / or a function of the vehicle, the method comprising:

[0022] - triggering to illuminate the object with patterned infrared illumination;

[0023] - triggering to generate at least one pattern image of the object while the object is illuminated by the patterned infrared illumination;

[0024] - determining whether the object corresponds to a living human being based on the at least one pattern image; and

[0025] - allowing the subject access to the vehicle and / or functionality of the vehicle based on determining that the subject corresponds to a living human being.

[0026] In another aspect, the present disclosure relates to a method for determining a condition of a driver, the method comprising:

[0027] - triggering to illuminate the driver with patterned infrared illumination;

[0028] - triggering to generate at least two pattern images of the object while the object is illuminated by patterned infrared illumination, wherein the at least two pattern images are generated at at least two different points in time,

[0029] - providing an indication of at least one interval between at least two different points in time,

[0030] - determining a condition measure associated with the condition of the driver based on the at least two pattern images and the indication of the at least one interval.

[0031] A measure of the condition is provided.

[0032] In another aspect, the present disclosure relates to uses of the systems as disclosed herein.

[0033] In another aspect, the present disclosure relates to a system for accessing a vehicle and / or a function of the vehicle, the system comprising:

[0034] - an input terminal configured to receive a payment request,

[0035] - an illumination source configured to illuminate the object with patterned infrared illumination,

[0036] - an image generation unit configured to generate at least one pattern image of the object while the object is illuminated by the patterned infrared illumination;

[0037] - a processor configured to determine whether the object corresponds to a living human based on the at least one pattern image; and to allow the object access to the vehicle and / or a function of the vehicle based on determining that the object corresponds to a living human.

[0038] In another aspect, the present disclosure relates to a method for accessing a vehicle and / or a function of the vehicle, the method comprising:

[0039] - illuminating the object with patterned infrared illumination;

[0040] - generating at least one patterned image of the object while the object is illuminated by the patterned infrared illumination;

[0041] - determining whether the object corresponds to a living human being based on the at least one pattern image; and

[0042] - allowing the subject to access the vehicle and / or functionality of the vehicle based on determining that the subject corresponds to a living human being.

[0043] To allow only qualified individuals to enter, start, or control a vehicle, reliable and accurate authentication of qualified individuals is required. Typically, authentication can be spoofed by spoofed objects (e.g., masks, images, etc.). Relying on a key to open and start a vehicle creates an opportunity for key misuse, for example by a thief. Conventional authentication relies heavily on high-quality images of the person and requires the person to behave in a certain way, such as positioning themselves relative to a camera. Therefore, reliable, secure, and flexible authentication is needed. The present invention provides a fast and user-friendly way to allow only qualified individuals to access, start, and / or control a vehicle. This is achieved by verifying the user's legitimacy—that is, determining whether a real person or a spoofed object is present. To this end, an object (i.e., a real person or a spoofed object) is illuminated with patterned light. The interaction of the patterned light with the object depends on the object's material. Therefore, a spoofed object made of silicon provides a pattern image that differs from a living person. Subsequently, determining whether the object corresponds to a living person based on at least one pattern image allows distinguishing between a spoofed object (e.g., a mask) and a real person. Because the present invention does not rely solely on 2D images, it has the added benefit of allowing the user to move more freely. This in turn increases the user's flexibility in authentication, reduces the number of authentication attempts, and therefore enables frictionless opening, starting, and control of the vehicle.

[0044] The following will summarize the embodiments of the present disclosure by way of examples. It should be understood that the present disclosure is not limited to the embodiments and / or examples.

[0045] In an embodiment, determining whether an object corresponds to an authorized person based on the flood image may be referred to as authenticating the object based on the flood image. Authentication of the object based on the flood image may be verified based on the extracted material data.

[0046] In an embodiment, a person, in particular an authorized person and / or user, may refer to a registered person and / or a registered person. A registered person may be a person who has undergone a registration process. The registration process may be a process for generating a template, in particular a template suitable for comparison with an image of a person recorded by a camera placed behind a transparent display.

[0047] In an embodiment, the illumination and / or recording may be initiated and / or triggered by an authentication request, preferably a payment request. In particular, the illumination and / or recording may be initiated and / or triggered by a payment terminal. Preferably, the illumination and / or recording may be initiated and / or triggered by at least one of a person, a device associated with the person, an application on the device associated with the person, or a combination thereof. The device associated with the person may be a mobile electronic communication device, such as a smartphone.

[0048] In an embodiment, the occupants may be illuminated by patterned infrared illumination from an illumination source. The illumination source may comprise a projector. The projector may be adapted to emit and / or project patterned infrared illumination. The projector may comprise a metasurface element and / or a vertical cavity surface emitting laser (VCSEL) array. The metasurface element may be adapted to replicate a light beam, in particular for replicating emitted patterned infrared illumination. The VCSEL may emit patterned infrared illumination. The projector may be adapted to emit patterned infrared illumination and / or flood illumination. The flood illumination may be adapted to illuminate a continuous area. In particular, the flood illumination may have a substantially constant irradiance. The patterned infrared illumination may be adapted to illuminate at least two continuous areas. The continuous areas may have any shape. The continuous areas may be spots of any size. The patterned infrared illumination may be adapted to project at least two spots.

[0049] In an embodiment, at least one pattern image may be generated by an image generation unit. The image generation unit may be a camera. The term "camera" may refer to at least one unit of an optoelectronic device configured to generate at least one image. The image may be generated via a hardware and / or software interface, which may be considered a camera.

[0050] A camera may include at least one optical sensor, particularly at least one pixelated optical sensor. The camera may include at least one CMOS sensor and / or at least one CCD chip. For example, the camera may include at least one CMOS sensor that may be sensitive in the infrared spectral range. The term "image" may refer to data recorded using an optical sensor, such as multiple electronic readings from a CMOS or CCD chip. The image may include raw image data or a pre-processed image. For example, pre-processing may include applying at least one filter and / or at least one background correction and / or at least one background subtraction to the raw image data. The camera may have a field of view between 10°×10° and 75°×75°, preferably 55°×65°. The camera may have a resolution of less than 2 MP, preferably between 0.3 MP and 1.5 MP. The camera may include other components, such as one or more optical elements, for example, one or more lenses. As an example, the optical sensor may be a fixed-focus camera, at least one lens of which is fixed relative to the camera's adjustment. Alternatively, however, the camera may include one or more variable lenses that can be adjusted automatically or manually. However, other camera options are also possible.

[0051] In embodiments, a payment request may be associated with a payment account, a good or service to be purchased, a vendor or service provider, an amount, and the like. The service may be an entertainment service and / or a navigation service. The payment request may be triggered by a passenger, an app store associated with the vehicle, a toll booth, and / or a gas station. The payment request may be triggered by establishing a connection between the vehicle and a device. The device may be an electronic device, particularly a mobile electronic device. The device may be adapted to connect to at least a portion of the vehicle. The device may be adapted to connect to at least a portion of the vehicle via near-field communication, radio frequency identification, Bluetooth, LAN, WLAN, Ethernet, and the like. The vehicle may be adapted to connect to the device via near-field communication, radio frequency identification, Bluetooth, LAN, WLAN, Ethernet, and the like. The device may be integrated into a roadway, a pillar, a sign, a gas pump, and the like.

[0052] In embodiments, the payment request and / or illumination may be triggered by a driver, a passenger, an app store associated with a vehicle, a toll booth, and / or a gas station.

[0053] In an embodiment, the input end may include one or more of the following: a serial or parallel interface or port, a USB, a Centronics port, a FireWire, an HDMI, an Ethernet, a Bluetooth, an RFID, a Wi-Fi, a USART or an SPI, or an analog interface or port (such as one or more of an ADC or a DAC), or a standardized interface or port to other devices. In an embodiment, the interface may be a shared boundary between at least two components of a processing unit. The interface may be a part of a processing unit. The interface may allow information to be exchanged between at least two components. The processing unit may include at least one processor. At least two components of a processing unit may correspond to a decentralized computing environment, a distributed computing environment, a centralized computing environment, a system comprising multiple devices (such as a computer, a laptop computer, a smart phone, a database, etc.). The interface may be a network interface or a user interface. The user interface may be an interface to a user, wherein the user can input information and / or the user interface may be used to provide information to the user. The network interface may be a virtual network interface.

[0054] In embodiments, a processor may refer to any logic circuit configured to perform the basic operations of a computer or system, and / or generally refers to a device configured to perform computational or logical operations. In particular, a processor or computer processor may be configured to process the basic instructions that drive a computer or system. A processor may be a semiconductor-based processor, a quantum processor, or any other type of processor configured to process instructions. As an example, a processor may be or may include a central processing unit ("CPU"). ” The processor can be (“GPU ” ) Graphics Processing Unit, (“TPU ” ) tensor processing unit, ("CISC ” ) Complex instruction set computing microprocessors, reduced instruction set computing ("RISC ” ) microprocessors, very long instruction words (VLIW ” ) microprocessor, or a processor implementing other instruction sets or multiple processors implementing a combination of instruction sets. The processing means may also be one or more special-purpose processing devices, such as application-specific integrated circuits ("ASICs") ” ), Field Programmable Gate Array (“FPGA ” ), Complex Programmable Logic Devices (CPLDs ” ), digital signal processor ("DSP ”), network processors, etc. The methods, systems and devices described herein may be implemented as software in a DSP, microcontroller or any other auxiliary processor, or as hardware circuits within an ASIC, CPLD or FPGA. It should be understood that the term processor may also refer to one or more processing devices, such as a distributed processing device system located on multiple computer systems (e.g., cloud computing), and is not limited to a single device, unless otherwise specified. The processor may also be an interface to a remote computer system such as a cloud service. The processor may include or may be a secure isolation processor (SEP). The SEP may be a secure circuit configured to process spectra. A "secure circuit" is a circuit that protects isolated internal resources from direct access by external circuits. The processor may be an image signal processor (ISP) and may include circuits suitable for processing images, particularly images with personal and / or confidential information.

[0055] In an embodiment, determining whether an object corresponds to a living human being may include extracting material data from a pattern image. Material data may be extracted from the pattern image. The material data may indicate a type of material. In particular, the material data may indicate whether the object associated with the pattern image at least partially comprises skin. The material data may be associated with the object, in particular associated with the object shown in the pattern image. Extracting material data from the pattern image may include generating a material type and / or data derived from the material type. Preferably, extracting material data may be based on the pattern image, more preferably based on a partial image. Material data may be extracted by using a model. Extracting material data may include providing the pattern image to the model and / or receiving material data from the model. Providing the pattern image to the model may include and may be followed by receiving the pattern image at an input layer of the model. The model may be a data-driven model.

[0056] In an embodiment, accessing the vehicle may comprise at least one of: controlling unlocking of the vehicle, opening of the vehicle, in particular a door of the vehicle, removing a blocking element or the like.

[0057] In an embodiment, the functionality of the vehicle may include at least one of: starting the vehicle, controlling a portion of the vehicle, such as lights, speed, gear, display, heating, connection (such as internet connection), etc.

[0058] In an embodiment, the data driven model may include a convolutional neural network and / or at least a partially encoder-decoder structure, such as an autoencoder. Other examples for generating representations may be FFTs, wavelets, deep learning (such as CNNs), energy-based models, normalized flows, GANs, visual transformers or transformers for natural language processing, autoregressive image modeling. GANs, autoregressive image modeling, normalized flows, deep autoencoders, deep energy-based models, visual transformers. Supervised or unsupervised schemes may be applicable to generating representations, and also to generating embeddings in, for example, Euclidean space. In another embodiment, extracting material data may include providing a pattern image to the model and / or receiving material data from the model.

[0059] In another embodiment, a data-driven model may be trained based on a training dataset comprising at least one pattern image and material data. In another embodiment, a data-driven model may be parameterized based on a training dataset comprising at least one pattern image and material data. The data-driven model may be parameterized based on a training dataset comprising at least one pattern image and material data. The data-driven model may be parameterized based on the training dataset to receive a pattern image and provide material data based on the received pattern image. The data-driven model may be trained based on the training dataset to receive a pattern image and provide material data as output based on the received pattern image. The training dataset may include at least one pattern image and material data (preferably material data associated with the at least one pattern image). The pattern image may include a representation of the pattern image. The representation may be a low-dimensional representation of the pattern image. The representation may include at least a portion of the data or information associated with the pattern image. The representation of the pattern image may include a feature vector. In an embodiment, determining the representation, particularly the low-dimensional representation, may be based on a principal component analysis (PCA) mapping or a radial basis function (RBF) mapping. Determining the representation may also be referred to as generating a representation. Generating the representation based on the PCA mapping may include clustering based on features in the pattern image and / or a portion of the image. Additionally or alternatively, generating the representation can be based on a neural network structure suitable for reducing dimensionality. The neural network structure suitable for reducing dimensionality can include an encoder. In an example, the neural network structure can be an autoencoder. In an example, the neural network structure can include a convolutional neural network (CNN). The CNN can include at least one convolution layer and / or at least one pooling layer. The CNN can reduce the dimensionality of the partial image and / or the pattern image by applying convolution (e.g., based on a convolution layer) and / or by pooling. Applying convolution can be suitable for selecting features related to the material information of the pattern image, in particular the partial image.

[0060] In an embodiment, extracting material data from a pattern image using a data-driven model may include providing the pattern image to the data-driven model. Additionally or alternatively, extracting material data from a pattern image using a data-driven model may include generating an embedding associated with the pattern image based on the data-driven model. An embedding may refer to a low-dimensional representation associated with the pattern image, such as a feature vector. The feature vector may be suitable for suppressing background while maintaining a material signature indicative of material data. In this context, background may refer to information independent of the material signature and / or material data. Further, background may refer to information related to biometric features such as facial features. Based on the embedding associated with the pattern image, the material data may be determined using the data-driven model. Additionally or alternatively, extracting material data from a pattern image by providing the pattern image to the data-driven model may include transforming the pattern image into material data, in particular, a material feature vector indicative of the material data. Therefore, the material data may further include a material feature vector and / or the material feature vector may be used to determine the material data.

[0061] In an embodiment, determining whether an object corresponds to a living human being based on at least one pattern image may be referred to as verification. Releasing payment may be based on verification. Verification may be based on determining that the object corresponds to a living human being. Verifying based on extracted material data may include determining whether the extracted material data corresponds to expected material data. The expected material data may refer to predetermined material data. The predetermined material data may refer to material data associated with an authorized user.

[0062] In an embodiment, payment may be further released based on determining that the object corresponds to an authorized user. Determining that the object corresponds to an authorized user may include determining whether the object corresponds to an authorized user. Determining whether the object corresponds to an authorized person based on the flood image may include matching the flood image to a template. Matching the flood image to the template may include determining a match score between the flood image and the template. The template may be generated during a registration process for the authorized user. The template may be associated with the authorized user. Determining a match score between the template and the flood image may include determining a similarity between the template and the flood image. The template may include template features and / or may be represented by template features. The template features may be template vectors. The flood image may include image features and / or may be represented by image features. The image features may be feature vectors. Determining the similarity between the template and the flood image may include determining a distance between the template vector and the feature vector. The feature vector may be a facial feature vector.

[0063] In an embodiment, the authentication object may be facial authentication, the feature vector may be a facial feature vector, and the template may show, include, and / or represent the face of an authorized user.

[0064] In an embodiment, the illumination and / or generation can be triggered based on a timer, an event caused by the use of a vehicle function, a change in conditions related to driving the vehicle, a request from an occupant, and / or a request from a government agency. The event can be, for example, an accident. This is beneficial because it enables frictionless or passive verification of the driver's eligibility to continue using the vehicle function.

[0065] In an embodiment, the function of determining whether a driver is eligible to continue using a vehicle based on at least one image may include at least one of the following: extracting material data based on a pattern image, determining a blood perfusion measure based on a pattern image, determining a head posture based on a floodlight image and / or a pattern image, and determining occlusion, in particular occlusion of the driver's eyes, based on a floodlight image and / or a pattern image.

[0066] In an embodiment, the pattern image can be generated within the vehicle. The illumination source and / or image generation unit can be located within the vehicle. Prior to generating the pattern image, the authorized user may have already been allowed access to the vehicle while the authorized user was outside the vehicle. Therefore, security authentication of the subject has already been performed while the authorized user was outside the vehicle. The event can occur after the authorized user outside the vehicle has been authenticated. Therefore, the additional authentication before starting the engine and controlling it increases security and prevents thieves, children, or other unauthorized users from controlling the vehicle.

[0067] In an embodiment, extracting material data may include determining a similarity between the extracted material data and expected material data. Determining the similarity between the extracted material data and the expected material data may include comparing the extracted material data with the expected material data. In an instance, the expected material data may be skin. It may be determined whether the material data may correspond to the expected material data. In an instance, the material data may be a non-skin material or silicon. Determining whether the material data corresponds to the expected material data may include comparing the material data with the expected material data. Comparing the material data with the expected material data may result in allowing and / or denying the subject from performing at least one operation requiring authentication. In an instance, skin as the expected material data may be compared with a non-skin material or silicon as the material data, and the result may be biased because silicon or the non-skin material may differ from skin.

[0068] In an embodiment, the infrared light may include near infrared light, mid infrared light, and / or far infrared light. The infrared light may be in the range of 750 nm to 1000 μm. The near infrared light may be in the range of 780 nm to 3000 nm, excluding the value of 3000 nm. The mid infrared light may be in the range of 3 μm to 15 μm, excluding the value of 15 μm. The far infrared light may be in the range of 15 μm to 1000 μm. The patterned infrared irradiation may include coherent patterned infrared irradiation. The visible irradiation may be in the range of 380 nm to 750 nm, excluding the value of 750 nm.

[0069] In an embodiment, the patterned infrared illumination may be coherent patterned infrared illumination, and determining whether the object corresponds to a living human may include determining a blood perfusion measure based on the pattern image. Determining the blood perfusion measure may include determining a speckle contrast of the pattern image and determining the blood perfusion measure based on the determined speckle contrast. The speckle contrast may represent a measure of the average contrast of the intensity distribution within a region of the speckle pattern. In particular, the speckle contrast K over the speckle pattern region may be expressed as the product of a standard deviation σ and an average speckle intensity. The ratio of, that is,

[0070]

[0071] The speckle contrast may include a speckle contrast value. The speckle contrast value may be distributed between 0 and 1. A blood perfusion measure is determined based on the speckle contrast. Therefore, a vital sign measurement may depend on the determined speckle contrast. If the speckle contrast changes, the blood perfusion measure derived from the speckle contrast may also change accordingly. The blood perfusion measure may be a single number or value that may indicate the likelihood that the subject is alive. Preferably, a full pattern image may be used to determine the speckle contrast. Alternatively, a portion of the pattern image may be used to determine the speckle contrast. Preferably, the portion of the pattern image represents a smaller area of ​​the pattern image than the area of ​​the full pattern image. The portion of the pattern image may be obtained by cropping the pattern image.

[0072] In an embodiment, a data-driven model may be used to determine a blood perfusion measure. The data-driven model may be parameterized and / or trained based on a training dataset. The training dataset may include pattern images and blood perfusion measures. The data-driven model may be parameterized and / or trained based on the training dataset to output a blood perfusion measure based on received pattern images.

[0073] In embodiments, patterned infrared radiation may be emitted by an radiation source, and the radiation source may be at least partially covered by a transparent display, and / or wherein at least one pattern image may be generated by an image generation unit, and the image generation unit may be at least partially covered by a transparent display, and / or wherein a flood image may be generated by an image generation unit, and the image generation unit may be at least partially covered by a transparent display.

[0074] In an embodiment, a data-driven model may be used to determine whether an object corresponds to a living human based on at least one pattern image and / or to determine whether an object corresponds to an authorized user based on a floodlight image. The data-driven model for determining whether an object corresponds to a living human based on at least one pattern image may be parameterized and / or trained based on a training data set. The training data set for determining whether an object corresponds to a living human may include a pattern image and a corresponding label indicating whether the object corresponds to a living human. The data-driven model may be parameterized and / or trained based on the training data set to output a label indicating whether the object corresponds to a living human based on the received pattern image. The data-driven model for determining whether an object corresponds to an authorized user based on a floodlight image may be parameterized and / or trained based on a training data set. The training data set for determining whether an object corresponds to an authorized user may include a floodlight image and a corresponding label indicating whether the object corresponds to an authorized user.

[0075] In an embodiment, determining whether an object corresponds to a live human being based on at least one pattern image may include providing the pattern image to a material data driven model, wherein the material data driven model is parameterized and / or trained based on historical pattern images and corresponding indications of whether objects associated with the historical pattern images correspond to live human beings. The material data driven model may be parameterized and / or trained to provide an indication of whether an object associated with the pattern image corresponds to a live human being. In an embodiment, determining whether an object corresponds to an authorized user based on a flood image may include providing the flood image to an authentication data driven model, wherein the material data driven model is parameterized and / or trained based on historical flood images and corresponding indications of whether objects associated with the historical flood images may correspond to live human beings. The authentication data driven model may be parameterized and / or trained to provide an indication of whether an object associated with the flood image corresponds to an authorized user.

[0076] In an embodiment, a flood image associated with an object may be received and / or generated. Generating the flood image may include capturing flood from the object. The flood image may show at least a portion of an outline of the object.

[0077] In embodiments, the flood image may be associated with visible illumination and / or flood infrared illumination.

[0078] In an embodiment, the infrared radiation may be in the range between 750 nm and 1000 nm.

[0079] In an embodiment, it may be determined based on the flood image whether the object corresponds to an authorized user, and payment may be further released based on determining that the object corresponds to the authorized user based on the flood image.

[0080] In embodiments, the subject may be a fraudulent subject, a user of a vehicle, an owner of a vehicle, an authorized person, and / or an occupant of a vehicle. The subject may be determined to be an authorized person. Before determining that the subject is likely an authorized person, the term "subject" is used to include the possibility of a fraudulent subject (e.g., a mask, image, etc. presented during the authentication process).

[0081] In an embodiment, an occupant's head posture can be detected based on a floodlight image, and payment can be further released based on the occupant's head posture. Detecting the head posture may include determining a pitch angle and / or a yaw angle based on the floodlight image. The outline of an object can indicate the head posture. The outline can indicate the position of one part of the object relative to another part of the object. The distance between these two parts of the object can indicate the head posture. For example, the outline can indicate the position of the nose and the position of the eyes. If the driver is essentially looking at a camera located, for example, in the dashboard, while observing the road, the distance between the right eye and the nose is similar to the distance between the left eye and the nose. If the driver turns to the left, the distance between the right eye and the nose may be significantly higher than the distance between the left eye and the nose, or the left eye may no longer be visible. Therefore, the outline of the driver's face includes information about the driver's head posture. Based on the determined head posture, payment can be released. If the determined head posture corresponds to an allowed head posture, payment can be released based on the determined head posture. The allowed head posture can enable determination of whether the object corresponds to a living human based on at least one pattern image and / or determination of whether the object corresponds to an authorized user based on the floodlight image. The allowed head poses may be defined by a range of pitch and / or yaw angles. Determining that the pitch and yaw angles associated with the flood image correspond to the ranges defined by the pitch and / or yaw angles may result in release of payment.

[0082] In an embodiment, releasing the payment may be followed by performing a transaction associated with the payment and / or enabling use of a product associated with the payment request, providing a product associated with the payment request, and / or providing a service associated with the payment request.

[0083] In an embodiment, the occupant may be the driver of the vehicle.

[0084] In an embodiment, the pattern image may show an object, in particular it may show the object under illumination of patterned infrared light.

[0085] In an embodiment, a system for accessing a vehicle and / or vehicle functions can be integrated into both the exterior and interior of the vehicle. This enables secure passive access and passive starting without the driver's attention. Furthermore, the driver is relieved of the burden of unlocking and starting the vehicle on their own. This is also known as frictionless access. The same technical effects are achieved when implementing the methods for accessing a vehicle and accessing vehicle functions.

[0086] In an embodiment, a pattern image may be generated while an object may have been illuminated by patterned infrared light and is outside a vehicle. A second pattern image may be received in response to allowing the object access to the vehicle based on the pattern image generated outside the vehicle. The second pattern image may be generated while the object may have been illuminated by patterned infrared light and is inside the vehicle. The second pattern image may be generated by an image generation unit covered by a transparent display. The second pattern image may show an occupant under the patterned infrared light illumination. It may be determined based on the second pattern image whether the occupant is likely to be a living human. Based on determining that the occupant is likely to be a living human, the occupant is allowed to access functions of the vehicle, such as starting the engine. This embodiment shows how frictionless access can be achieved without compromising safety.

[0087] In an embodiment, determining that the object corresponds to a living human being may include determining that the object associated with the pattern image is perfused with blood and / or determining that the object includes skin.

[0088] In an embodiment, the image generation unit and / or projector can be at least partially covered by a transparent display. This makes the authentication process less obvious from the outside. Since this is invisible to potential imposters, the opportunity for fraud is reduced. A transparent display is at least partially transparent. The term "at least partially transparent" can refer to the property of the display that allows light, particularly light in a specific wavelength range (such as light in the infrared spectral region, particularly light in the near-infrared spectral region), to at least partially pass through. For example, the display can be semi-transparent in the near-infrared region. For example, the display can have a transparency of 20% to 50% in the near-infrared region. The display can have different transparency for other wavelength ranges. For example, the display can have a transparency of >80% for the visible spectrum range, preferably >90% for the visible spectrum range. A transparent display can be at least partially transparent over the entire display area or only over a portion of it. Typically, it is sufficient that the portions of the display area through which light from the projector or light to the camera is transmitted are at least partially transparent. In particular, in case the projector and / or camera is covered by the display, the transparent display may be at least partially transparent.

[0089] In an embodiment, patterned infrared radiation may be emitted by an illumination source, and a pattern image may be generated by an image generation unit, wherein the illumination source and / or the image generation unit may be at least partially covered by a transparent display. The display may include a display area. The term "display area" may refer to the active area of ​​the display, particularly an activatable area. The display may have additional areas, such as recesses or cutouts. The display may have a first area associated with a first pixel per inch (PPI) value and a second area associated with a second PPI value. The first PPI value may be lower than the second PPI value, preferably the first PPI value is equal to or lower than 400 PPI, and more preferably the second PPI value may be equal to or higher than 300 PPI. The first PPI value may be associated with at least one continuous area that is at least partially transparent. The transparent display may be attached to a vehicle. It may be placed in various locations, such as outside or inside the vehicle. When placed outside the vehicle, it may be integrated into the vehicle body, doors, windows, reflectors, or between windows, such as in the B-pillars of a car. When placed inside a vehicle, it can be integrated into the steering wheel, in place of the speedometer, located in the center of the dashboard, in a mirror or in a window.

[0090] In an embodiment, providing the determined condition metric may include: determining whether the determined condition metric may correspond to a target condition metric; and allowing the driver to control at least one function of the vehicle in response to determining that the determined condition metric may correspond to the target condition metric.

[0091] In an embodiment, determining a condition measure associated with the driver's condition based on the at least two pattern images and the indication of the at least one interval may include providing the at least two pattern images and the indication of the at least one interval to a condition model. The condition model may be a data-driven model, particularly based on statistical distributions between the pattern images, the indication of the intervals, and the condition measure. The condition model may be parameterized and / or trained based on historical pattern images, historical indications of the intervals, and historical condition measures. The condition model may be parameterized and / or trained to determine the condition measure in response to being provided with the at least two pattern images and the at least one indication of the intervals.

[0092] A condition metric may be a metric suitable for determining the condition of a living organism. The condition of a living organism may be physical and / or mental. Physical condition may be associated with physical stress levels, fatigue, arousal, suitability for performing a specific task of the living organism, and the like. Mental condition may be associated with mental stress levels, attention span, concentration, arousal, suitability for performing a specific task of the living organism, and the like. Such specific tasks may require the living organism to be focused, attentive, alert, calm, or similar. Examples of such tasks may include: controlling machinery, vehicles, mobile devices, etc.; operating other living creatures; sports-related activities; playing games; emergency tasks; making decisions, and the like. The condition metric indicates the condition of the living organism. The condition metric may be one or more of the following: heart rate, blood pressure, respiratory level, and the like. In some embodiments, the condition of the living organism may be a critical condition corresponding to a high value of the condition metric, and the condition of the living organism may be a non-critical condition corresponding to a low value of the condition metric. Therefore, according to these embodiments, a critical condition metric may be equal to or below a threshold, and a non-critical condition metric may be below a threshold. In other embodiments, the condition of the living organism may be a critical condition corresponding to a low value of the condition metric, and the condition of the living organism may be a non-critical condition corresponding to a high value of the condition metric. Thus, according to these embodiments, the critical condition metric may be equal to or above a threshold value, and the non-critical condition metric may be below a threshold value. The critical condition metric may be associated with a high stress level, low attention, low concentration, high fatigue, high arousal, low fitness for performing a particular task of the living organism, etc. The non-critical condition metric may be associated with a low stress level, high attention, high concentration, low fatigue, low arousal, high fitness for performing a particular task of the living organism, etc.

[0093] A condition measurement of a living organism can be determined based on the movement of bodily fluid, preferably blood, most preferably red blood cells. The movement of bodily fluid is not constant over time, but rather varies due to the activity of parts of the living organism (e.g., the heart). This change in movement can be determined based on changes in feature contrast over time. Large differences between feature contrast values ​​at different time points can be associated with rapid changes in movement. Small differences between feature contrast values ​​at different time points can be associated with slow changes in movement. Changes in the movement of bodily fluid, preferably blood, can be periodically associated with a corresponding movement frequency. Therefore, the feature contrast can vary periodically with the corresponding movement frequency. The movement frequency can correspond to the length of a period associated with the periodic change in feature contrast. In some embodiments, at least two reflection images can include half a period. In other embodiments, at least two reflection images can include one or more periods. Preferably, pattern features associated with the same part of the living organism can be used to determine the condition of the living organism. This is advantageous because different parts of the body have different blood perfusions, and therefore different feature contrasts. In some embodiments, at least one condition measure may be determined based on feature contrast. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Hereinafter, the present disclosure will be further described with reference to the accompanying drawings. In the accompanying drawings and the present disclosure, the same reference numerals are intended to refer to the same or similar elements, components and / or parts.

[0095] Figure 1 Elements of a system for accessing a vehicle and / or vehicle functions are shown positioned behind a transparent display.

[0096] Figure 2 and Figure 3 Potential placement of systems for accessing a vehicle and / or functionality of a vehicle is illustrated.

[0097] Figure 4 It shows how to allow the driver to access the vehicle and / or vehicle functions. Figure 4 An example of how in-car payments may be made is shown. DETAILED DESCRIPTION BRIEF DESCRIPTION OF THE DRAWINGS

[0098] The following embodiments are merely examples for implementing the methods, systems, or application devices disclosed herein and should not be considered limiting.

[0099] Figure 1 The diagram shows elements of a system 100 attached to a vehicle for accessing the vehicle and / or its functions. It includes a transparent display 101 that allows light 120 to pass from an illumination source 102 to a person 110. The light can be infrared light, in particular patterned infrared light, which is invisible to the person. The transparent display 101 can be transparent only at the locations where the light 120, 130 passes through. Transparent can mean that at least 30% or at least 50% of the incident light passes through the transparent display 101. The transparent display 101 further allows reflected light 130 reflected by the person 110 to pass to a camera 103. The light 120 can be incident on the person's face, but it can also be incident on the entire head including the hair, the upper part of the body (including the head, neck and shoulders), or even the entire body. The camera 103 generates an image in an optical range that matches the wavelength emitted by the projector 102, for example, an image in the infrared range. The image can be a grayscale image (i.e., each pixel contains only total intensity information) or an RGB image (i.e., different pixels indicate the intensity of specific wavelengths). The image is passed to processor 104. Processor 104 can be a microcontroller, i.e., one that includes memory and IO controller functionality, or it can be a CPU connected to a memory and IO controller. Processor 104 determines whether the person is an authorized person and / or whether the person is a real human. Determining whether the person is authorized can involve vectorizing the image into features. This feature vector can be compared to a stored template. If the difference between the feature vector and the stored template is below a predefined threshold, the processor can determine that the person in the vehicle is authorized. The processor can further determine whether the image truly shows a human being and not a spoofing mask. This can be achieved by evaluating the reflective properties of the reflected light to classify the material of the face in the image. Another option for determining whether the pattern image shows a real person is to detect blood perfusion, for example, in the facial area. If no skin or blood perfusion is detected, the processor can determine that the person in front of the transparent display is unauthorized or is presenting a spoofing object. If an authorized user is present, the processor may generate a signal 140 indicating that the person in the vehicle is authorized. The signal 140 may be forwarded to a controller, for example via a wireless communication interface, to unlock the vehicle, start the engine, grant access to an onboard computer, or enable secure payment.

[0100] Figure 2 Indicates that the system for accessing the function of a vehicle and / or a vehicle can be attached to a potential location on the exterior of a vehicle (e.g., car 200). The system for accessing the function of a vehicle and / or a vehicle can be placed between the windows in the B-pillar 201. Alternatively or additionally, the system for accessing the function of a vehicle and / or a vehicle can be placed in the side mirror 202. The system for accessing the function of a vehicle and / or a vehicle can be integrated in the B-pillar and inside the vehicle to achieve frictionless access. Frictionless access includes accessing the vehicle without the user having to unlock the vehicle, and starting the engine of the vehicle without the user having to start the engine of the vehicle.

[0101] Figure 3 Indicates potential locations inside a vehicle where a system for accessing a vehicle and / or vehicle functions can be attached. The figure shows the dashboard 301 and windshield of a car as seen from inside the car. The system for accessing a vehicle and / or vehicle functions can be integrated into an interior mirror 302. This could be particularly useful if the mirror function were simply mimicked by a display showing a rear view recorded by a camera. Another possibility is the space behind the steering wheel 303, where meters such as a speedometer are typically placed. In addition, the system for accessing a vehicle and / or vehicle functions could also be integrated into the steering wheel 304. The center console 305 is another option, as replacing traditional controls with displays is becoming increasingly popular. In an embodiment, the space behind the steering wheel 303 and the center console can be combined into a continuous display.

[0102] Figure 4 A system for accessing a vehicle and / or vehicle functions is shown inside a car. System 401 for accessing a vehicle and / or vehicle functions is positioned behind the steering wheel, within the dashboard. Light 402 is emitted onto the face of driver 403. Light reflected by person 403 may pass through system 401 for accessing a vehicle and / or vehicle functions, where it is recorded by a camera, which generates an image that is analyzed by a processor to determine whether the person is an authorized person and / or whether the object associated with the pattern image is a living human.

[0103] The present disclosure has also been described with reference to various preferred embodiments and examples. However, other variations can be understood and effected by those skilled in the art and those practicing the claimed invention from a study of the drawings, the present disclosure, and the claims.

[0104] Any steps presented herein may be performed in any order. The methods disclosed herein are not limited to a particular order of steps. They are not required to be performed in a particular location or on a particular computing node in a distributed system. In other words, each step may be performed on a different computing node using different equipment / data processing.

[0105] As used herein, “determining” also includes “initiating or causing a determination,” “generating” also includes “initiating and / or causing generation,” and “providing” also includes “initiating or causing determination, generation, selection, sending, and / or receiving.” “Initiating or causing performance of an action” includes any processing signal that triggers a computing node or device to perform a corresponding action.

[0106] In the claims and the description, "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude other elements or steps. ” or "an ” ) does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage in an embodiment.

[0107] Any disclosure and embodiment described herein may relate to the above-listed methods, systems, apparatus, computer program elements, and vice versa. Advantageously, the benefits provided by any embodiment and example also apply to all other embodiments and examples, and vice versa.

[0108] All terms and definitions used herein are to be understood broadly and have their ordinary meanings.

Claims

1. A method for accessing a vehicle and / or a function of the vehicle, the method comprising: - illuminating the object with patterned infrared illumination; - generating at least one patterned image of the object while the object is illuminated by the patterned infrared illumination; - determining whether the object corresponds to a living human being based on the at least one pattern image; as well as - allowing the subject access to the vehicle and / or functionality of the vehicle based on determining that the subject corresponds to a living human being.

2. A method for performing in-vehicle payment, the method comprising: - receiving payment requests, - illuminating the object with patterned infrared illumination; - generating at least one patterned image of the object while the object is illuminated by the patterned infrared illumination; - determining whether the object corresponds to a living human being based on the at least one pattern image; as well as - Releasing the payment based on determining that the object corresponds to a living human being.

3. The method according to claim 2, wherein: The payment request and / or the illumination is triggered by the driver, passenger, an app store associated with the vehicle, a toll booth, and / or a gas station.

4. The method according to claim 1, further comprising receiving and / or generating a flood image associated with the subject, and detecting a head pose of the subject based on the flood image, and wherein: The subject is allowed access to the vehicle and / or functionality of the vehicle based on the head gesture.

5. The method according to claim 2 and 3, further comprising receiving and / or generating a flood image associated with the subject, and detecting the subject's head pose based on the flood image, and wherein: The payment is further released based on the subject's head posture.

6. The method of claims 2, 3 and 5, further comprising receiving and / or generating a flood image associated with the object and determining whether the object corresponds to an authorized user based on the flood image, and wherein: The payment is further released based on a determination that the object corresponds to an authorized user based on the flood image.

7. The method according to claims 1 and 4, further comprising receiving and / or generating a flood image associated with the object and determining whether the object corresponds to an authorized user based on the flood image, and wherein Based on determining that the subject corresponds to an authorized user based on the floodlight image, the subject is permitted access to the vehicle and / or functions of the vehicle.

8. A method according to any one of the preceding claims, wherein The patterned infrared radiation is emitted by an radiation source, and the radiation source is at least partially covered by a transparent display, and / or wherein the at least one pattern image is generated using an image generation unit, and the image generation unit is at least partially covered by a transparent display, and / or wherein the flood image is generated using an image generation unit, and the image generation unit is at least partially covered by a transparent display.

9. The method according to claims 2 to 6, wherein: Releasing the payment is followed by performing a transaction associated with the payment and / or enabling use of a product associated with the payment request, providing the product associated with the payment request, and / or providing a service associated with the payment request.

10. A method according to any one of the preceding claims, wherein The data-driven model is used to determine whether the object corresponds to a living human being based on the at least one pattern image and / or whether the object corresponds to an authorized user based on the flood image.

11. A method according to any one of the preceding claims, wherein Determining whether the object corresponds to a living human based on the at least one pattern image includes extracting material data from the pattern image, and / or determining whether the object corresponds to a living human based on the at least one pattern image includes determining a blood perfusion measure, wherein the patterned infrared radiation is coherent patterned infrared radiation.

12. A method according to any one of the preceding claims, wherein The infrared radiation is in the range between 750 nm and 1100 nm.

13. A system for accessing a vehicle and / or a function of the vehicle, the system comprising: - an input terminal configured to receive a payment request, - an illumination source configured to illuminate the object with patterned infrared illumination, - an image generation unit configured to generate at least one pattern image of the object while the object is illuminated by the patterned infrared illumination; - a processor configured to determine whether the object corresponds to a living human based on the at least one pattern image; and to allow the object access to the vehicle and / or a function of the vehicle based on determining that the object corresponds to a living human.

14. A vehicle comprising the system according to claim 13.

15. Use of the system according to claim 13 for authenticating a user for in-vehicle payment, vehicle access and / or vehicle start-up.

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