Patent Publication Number: US-2023143446-A1

Title: Apparatus for detecting a specular surface in a scene and method for controlling an apparatus for detecting a specular surface in a scene

Description:
CROSS REFERENCE TO RELATED APPLICATION 
     This application claims priority to European Patent Application No. 21207802 filed on Nov. 11, 2021, the content of which is incorporated by reference herein in its entirety. 
     TECHNICAL FIELD 
     The present disclosure relates to detection of a specular surface. Examples relate to an apparatus for detecting a specular surface in a scene and a method for controlling an apparatus for detecting a specular surface in a scene. 
     BACKGROUND 
     Detecting a specular surface in a scene may be useful for lots of applications, e.g., for detection of water on roadways in automotive applications or sweat detection as feature of fitness devices. However, a conventional imaging system capturing an image of the scene is not capable of differentiating between specular and non-specular surfaces in the scene. Hence, there may be a demand for improved imaging. 
     SUMMARY 
     Example implementations described herein may relate to one or more imaging systems and/or one or more methods capable of differentiating between specular and non-specular surfaces in a scene. 
     An example relates to an apparatus for detecting a specular surface in a scene. The apparatus includes an illumination device configured to emit polarized light towards the scene. The apparatus further includes an imaging system configured to capture a first image of the scene based on light emanating from the scene. The light emanating from the scene includes one or more reflection of the emitted polarized light. The imaging system is further configured to capture a second image of the scene based on filtered light. The apparatus further includes a polarization filter configured to generate the filtered light by filtering the light emanating from the scene. The apparatus further includes processing circuitry configured to determine presence of the specular surface in the scene based on a comparison of the first image and the second image. 
     Another example relates to a method for operating an apparatus for detecting a specular surface in a scene. The apparatus for detecting the specular surface includes an illumination device, an imaging system, a polarization filter, and processing circuitry. The method includes emitting polarized light towards the scene and capturing a first image of the scene based on light emanating from the scene. The light emanating from the scene includes one or more reflection of the emitted polarized light. The method further includes generating filtered light by filtering the light emanating from the scene through the polarization filter and capturing a second image of the scene based on the filtered light. The method further includes determining presence of the specular surface in the scene based on a comparison of the first image and the second image. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Some examples of apparatuses and/or methods will be described in the following by way of example only, and with reference to the accompanying figures, in which 
         FIG.  1    illustrates an example of an apparatus for detecting a specular surface in a scene; 
         FIG.  2    illustrates another example of an apparatus for detecting a specular surface in a scene; 
         FIG.  3    illustrates another example of an apparatus for detecting a specular surface in a scene; 
         FIGS.  4   a  and  4   b    illustrate a side view and a front view of another example of an apparatus  100  for detecting a specular surface in a scene; 
         FIGS.  5   a  and  5   b    illustrate an example first image and an example second image of a scene; 
         FIGS.  6   a - 6   c    illustrate example light intensity histograms; 
         FIG.  7    illustrates an example of a vehicle comprising an apparatus for detecting a specular surface in a scene; 
         FIG.  8    illustrates a flowchart of an example of a method for operating an apparatus for detecting a specular surface in a scene; 
         FIG.  9    illustrates an example of an apparatus for classifying a material in a scene; and 
         FIG.  10    illustrates a flowchart of an example of a method for operating an apparatus for classifying a material in a scene. 
     
    
    
     DETAILED DESCRIPTION 
     Some examples are now described in more detail with reference to the enclosed figures. However, other possible examples are not limited to the features of these implementations described in detail. Other examples may include modifications of the features as well as equivalents and alternatives to the features. Furthermore, the terminology used herein to describe certain examples should not be restrictive of further possible examples. 
     Throughout the description of the figures same or similar reference numerals refer to same or similar elements and/or features, which may be identical or implemented in a modified form while providing the same or a similar function. The thickness of lines, layers and/or areas in the figures may also be exaggerated for clarification. 
     When two elements A and B are combined using an “or”, this is to be understood as disclosing all possible combinations, e.g., only A, only B as well as A and B, unless expressly defined otherwise in the individual case. As an alternative wording for the same combinations, “at least one of A and B” or “A and/or B” may be used. This applies equivalently to combinations of more than two elements. 
     If a singular form, such as “a”, “an” and “the” is used and the use of only a single element is not defined as mandatory either explicitly or implicitly, further examples may also use several elements to implement the same function. If a function is described below as implemented using multiple elements, further examples may implement the same function using a single element or a single processing entity. It is further understood that the terms “include”, “including”, “comprise” and/or “comprising”, when used, describe the presence of the specified features, integers, steps, operations, processes, elements, components and/or a group thereof, but do not exclude the presence or addition of one or more other features, integers, steps, operations, processes, elements, components and/or a group thereof. 
       FIG.  1    illustrates an example of an apparatus  100  for detecting a specular surface in a scene  110 . The specular surface is to be understood as a light-reflecting surface, e.g., light impinging on the specular surface is at least partly reflected from the specular surface and a resulting reflection retains its parallelism according to the law of reflection. The specular surface may exhibit a specific roughness or unevenness to be considered specular. For instance, the specular surface may have an average roughness that is limited to a specific maximum value relative to a wavelength of impinging light to be specular for the light. The specular surface may be, e.g., a surface of a liquid or a mirroring, even surface of a solid. For instance, the specular surface may be a surface of water, glass, or metal. 
     The apparatus  100  comprises an illumination device  120  configured to emit polarized light  130  towards the scene  110 . The illumination device  120  may comprise one or more light source such as one or more Light-Emitting Diode (LED) and/or one or more laser diode (e.g., one or more Vertical-Cavity Surface-Emitting Laser, VCSEL) for radiating the polarized light  130 . The illumination device  120  may emit polarized light of any wavelength, e.g., infrared light, visible light, or mixtures thereof. 
     The polarized light  130  is light oscillating (mainly) in a specific geometrical orientation, e.g., light exhibiting a specific polarization. The polarization refers to a direction of an electric field or magnetic field of the polarized light  130 . The emitted polarized light  130  may exhibit a linear (planar), circular, or elliptic polarization. In case of the linear polarization, the electric/magnetic field of the polarized light  130  oscillates at least mainly in a specific direction perpendicular to a direction of propagation of the polarized light  130 . The linear polarization may be described as an angle between the specific direction and a reference direction. 
     In case of the circular or elliptical polarization, the electric/magnetic field of the polarized light  130  rotates at a (mainly) constant rate in a plane perpendicular to the direction of propagation. During propagation of the polarized light  130 , a tip of a field vector of the electric/magnetic field describes a circle or an ellipse on the plane, respectively. The circular or elliptical polarization may be described based on a sense of rotation of the electric/magnetic field. If the electric/magnetic field rotates in a right-hand sense (clockwise) with respect to the direction of propagation, the polarized light  130  exhibits a right-handed circular polarization, while if the electric/magnetic field rotates in a left-hand sense (anticlockwise), the polarized light  130  exhibits a left circular polarization. 
     The polarization of the polarized light  130  may be predefined or configurable due to a type, an operation mode, or an arrangement of the illumination device  120 . For instance, a polarization filter of the illumination device  120  may be placed in front of a light source of the illumination device  120 . The light source may radiate unpolarized light at least partly towards the polarization filter. The polarization filter may attenuate light not exhibiting a predefined (linear/circular/elliptic) polarization depending on a type of the polarization filter. An arrangement of the polarization filter regarding a reference plane may influence the angle or rotation sense of the polarization of the polarized light  130  regarding the reference plane. Thus, the polarization filter may be configured with regard to the type and arrangement of the polarization filter such that the polarization filter allows the polarized light  130  to pass. 
     The polarization filter may then direct the polarized light  130  to the scene  110 . The type or arrangement of the polarization filter may be changed or adjusted during an operation of the illumination device  120 , e.g., resulting into different operation modes of the illumination device  120 . Then, the polarization of the polarized light  130  may be configurable by switching between the different operation modes. 
     In some examples, the illumination device  120  may additionally comprise optical elements such as a waveplate (retarder) or an optical lens. In some examples, the illumination device  120  may comprise a first light source configured to emit the polarized light  130  towards the scene  110  a second light source configured to emit unpolarized light towards the scene  110 . For instance, the first light source and the second light source may illuminate the scene  110  independently, one with polarized and the other one with unpolarized light. 
     It is to be noted, that the scene  110  shown in  FIG.  1    is meant for illustration. In other examples, the scene  110  may be of a different shape or arranged differently regarding the apparatus  100  than shown in  FIG.  1   . The scene  110  may comprise objects of which one may have a specular surface. 
     Referring back to  FIG.  1   , the apparatus  100  further comprises an imaging system  140  configured to capture a first image of the scene  110  based on light emanating from the scene  110 . The imaging system  140  may be any optical instrument capable of capturing (digital) images of the scene  110 . The imaging system  140  may comprise various components such as e.g., optics (e.g., one or more lenses) and electronic circuitry. In particular, the electronic circuitry may comprise one or more image sensor comprising each at least one photosensitive element or pixel (e.g., comprising a Photonic Mixer Device, PMD, or a Charge-Coupled Device, CCD). For example, each image sensor may comprise a plurality of photosensitive elements or pixels. For instance, the imaging system  140  may comprise one or more camera such as a digital camera or a time-of-flight camera. The imaging system  140  may be mainly sensitive to light of a wavelength of the polarized light  130 . 
     The light emanating from the scene  110  comprises one or more reflection  132 ,  134  of the emitted polarized light  130 . The reflections  132 ,  134  may be a directed or diffuse reflection (e.g., remission) of the emitted polarized light  130 . The reflections  132 ,  134  result from the emitted polarized light  130  being reflected or backscattered from objects in the scene  110 . Characteristics of the reflections  132 ,  134  such as polarization or light intensity may depend on physical or chemical properties of the objects, e.g., roughness of a surface of the objects, transparency, translucence of the object, or absorption of light by the objects. The characteristics of the reflections  132 ,  134  may be specific for a material of the objects. 
     In case a specular surface is present in the scene  110  on which the emitted polarized light  130  impinges, a resulting reflection (e.g., reflection  132 ,  134 ) may exhibit a polarization corresponding to (but not necessarily matching) a polarization of the emitted polarized light  130 . For instance, if the emitted polarized light exhibits a right-handed circular polarization (as provided by the illumination device  120 ) and impinges on the specular surface, then, the resulting reflection exhibits a left-handed circular polarization, thus, exhibiting a mirrored sense of rotation relative to the emitted polarized light  130 . The reversal of the sense of rotation is due to a reverse direction of propagation in comparison to the emitted polarized light  130 . Similarly, if the emitted polarized light exhibits a left-handed circular polarization (as provided by the illumination device  120 ) and impinges on the specular surface, then, the resulting reflection exhibits a right-handed circular polarization. In other examples, the emitted polarized light  130  may exhibit a predefined linear polarization. If the emitted polarized light  130  with the predefined linear polarization impinges on the specular surface, then, the resulting reflection exhibits the predefined linear polarization, e.g., linear polarizations may be maintained after reflection. 
     By contrast, when the emitted polarized light  130  impinges on a non-specular surface, portions of the emitted polarized light  130  may be scattered (diffusely reflected). A resulting reflection (e.g., reflection  132 ,  134 ) may have an undefined or mixed polarization. 
     By way of illustration, in  FIG.  1   , the polarized light  130  and the reflections  132 ,  134  are indicated by light rays along example optical paths between the apparatus  100  and the scene  110 . In other examples, the polarized light  130  may comprise more light rays than shown in  FIG.  1   . The light rays may run along different optical paths between the apparatus  100  and the scene  110  than shown in  FIG.  1   . In other examples, the light emanating from the scene  110  may comprise less or more reflections than the ones shown in  FIG.  1   . In general, the light emanating from the scene  110  may comprise n ≥ 1 reflections. 
     The imaging system  140  is further configured to capture a second image of the scene  110  based on filtered light  136 . The apparatus  100  further comprises a polarization filter  150  configured to generate the filtered light  136  by filtering the light emanating from the scene  110 . The polarization filter  150  may filter the one or more reflection  132 ,  134  of the emitted polarized light  130 . A data acquisition time for capturing the first image and the second image of the scene  110  may be synchronized with an emission time of the polarized light  130 . 
     The polarization filter  150  is an optical filter or polarizer that lets light exhibiting a specific polarization (the filtered light  136 ) pass through while attenuating light of other polarizations. For instance, the polarization filter  150  may filter light of undefined or mixed polarization into light exhibiting a well-defined (predefined) polarization. The polarization filter  150  may be, for instance, of a dichroic, reflective, birefringent, scattering, or diffractive type. In case of a dichroic type, the polarization filter  150  may be a macromolecular foil plastically stretched into one direction. The direction of stretching may decide which polarization light exhibits that passes the polarization filter. Alternatively, the polarization filter  150  may be a wire grid polarizer or a polarizing prism, for instance. 
     The polarization filter  150  may direct the filtered light  136  to the imaging system  140  for capturing the second image. For instance, the polarization filter  150  may be placed in front of the imaging system  140  - at least from time to time. 
     Referring back to  FIG.  1   , the apparatus  100  further comprises processing circuitry  160  configured to determine presence of the specular surface in the scene  110  based on a comparison of the first image and the second image. Example approaches of how the processing circuitry  160  may determine the presence of the specular surface in the scene  110  based on the comparison is explained with reference to  FIG.  5   a    and  FIG.  5   b   . 
     The processing circuitry  160  may be a single dedicated processor, a single shared processor, or a plurality of individual processors, some of which or all of which may be shared, a digital signal processor (DSP) hardware, an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The processing circuitry  160  may optionally be coupled to, e.g., read only memory (ROM) for storing software, random access memory (RAM) and/or non-volatile memory. The processing circuitry  160  is communicatively coupled to the imaging system  140  for transferring the first image and the second image from the imaging system  140  to the processing circuitry  160 . 
     The first image and the second image may relate to a digital image, e.g., a bitmapped or vector image. The first image and the second image may comprise pixels representing a discrete quantity of a property (such as light intensity, color) of light being captured by the imaging system  140 . The first image and the second image may comprise reflection data of a respective view of the scene  110 . A view represented by the first image may at least partly correspond to a view represented by the second image. The first image and the second image may be captured at the same time or at different times but at quick succession. 
     In order to infer presence of the specular surface from the comparison of the first image and the second image, the imaging system  140  captures the first image and the second image with different sensitivities to specular reflections of the emitted polarized light  130 . For instance, if specular reflections occur, they may be captured in the first image but be mainly omitted in the second image. The different sensitivities may be realized by, e.g., capturing the first image without the polarization filter  150  and the second image with the polarization filter  150 . The polarization filter  150  may be selected and adjusted in accordance with a polarization of the emitted polarized light  130 . Furthermore, the apparatus  100  may be configured to pursue a specific filtering strategy. 
     For instance, a first filtering strategy may specify that the polarization filter  150  is intended to block specular reflections of the emitted polarized light  130 . Thus, the imaging system  140  may be intended to “omit” the specular reflections for capturing the second image, e.g., the second image is intended to not represent the specular reflections. For the first filter strategy, the polarization filter  150  may be selected or adjusted such that the polarization filter  150  attenuates (blocks) light exhibiting a polarization equal to the polarization of specular reflections of the emitted polarized light  130 . The polarization filter  150  may let pass light exhibiting a polarization differing from the polarization of the specular reflections. For instance, the emitted polarized light  130  may exhibit one of a right-handed circular polarization and a left-handed circular polarization. Pursuing the first filtering strategy, the polarization filter  150  may be configured to filter the other one of the right-handed circular polarization and the left-handed circular polarization out of the light emanating from the scene  110 . In other examples, the emitted polarized light  130  may exhibit a predefined linear polarization. Then, the polarization filter  150  may be configured to filter the light emanating from the scene  110  by attenuating light exhibiting the predefined linear polarization. In other words, the polarization filter  150  may be a circular polarization filter, or a linear polarization filter which filters light with a complementary polarization relative to the emitted polarized light  130  such that direct reflections of the emitted polarized light  130  are blocked. 
     A second filtering strategy may specify that the polarization filter  150  is intended to block non-specular reflections of the emitted polarized light  130 . Thus, the second image may be intended to represent specular reflections of the emitted polarized light  130  but to neglect at least partly the non-specular reflections. For instance, the emitted polarized light  130  may exhibit a circular polarization. Pursuing the second filtering strategy, the polarization filter  150  may be configured to filter the circular polarization out of the light emanating from the scene  110 . In other examples, the emitted polarized light  130  may exhibit a predefined linear polarization. Then, the polarization filter  150  may be configured to filter the light emanating from the scene  110  by attenuating light not exhibiting the predefined linear polarization. 
     Optionally, the imaging system  140  may be further configured to capture the first image of the scene based on light filtered differently than the filtered light  136 , e.g., filtered based on a different filtering strategy. The imaging system  140  may comprise, e.g., a second polarization filter to generate the differently filtered light. For instance, the imaging system  140  may capture the first image based on the first filtering strategy and the second image based on the second filtering strategy. 
     In conclusion, a difference between the first image and the second image may indicate presence of specular reflection. For instance, the apparatus  100  may detect water or other objects with specular surfaces in a scene. For this purpose, the apparatus  100  may combine conventional imaging and polarization imaging. 
     In some examples, the apparatus  100  may be applied for determining presence of water on a roadway. For instance, the processing circuitry  160  may be further configured to determine reflection characteristics of the specular surface based on a comparison of the first image and the second image. If presence of a specular surface is determined, the processing circuitry  160  may classify a material forming the specular surface based on the reflection characteristics. The processing circuitry  160  may be configured to classify the material as, e.g., water, snow, oil, metal, or glass. The processing circuitry  160  may be further configured to determine whether the specular surface is located on a roadway. If it is determined that the specular surface is located on the roadway, the processing circuitry  160  may estimate a friction coefficient of a vehicle on the roadway based on the classified material. 
     Furthermore, the apparatus  100  may distinguish water levels based on a comparison of polarized and non-polarized images of a scene. The apparatus  100  may determine the presence of water on the roadway to predict a friction coefficient of vehicles on the roadway for driving assistance applications or traffic management, for instance. Similarly, the apparatus  100  may be used to distinguish snow from rain droplets when monitoring driving conditions of the roadway. 
     In other examples, the apparatus  100  may be applied for detecting sweat on a skin of a human. For instance, the processing circuitry  160  may be further configured to, if presence of the specular surface is determined, determine whether the specular surface is located on the skin of the human. If it is determined that the specular surface is located on the skin of the human, the processing circuitry  160  may classify the specular surface as sweat. Sweat detection may be an additional feature for smartphones, HVAC (heating, ventilation, and air conditioning) devices, or fitness devices. 
       FIG.  2    illustrates another example of an apparatus  200  for detecting a specular surface in a scene (not shown). The scene may be located right of the apparatus  200  (in  FIG.  2   ). The apparatus  200  comprises an illumination device  220  configured to emit polarized light towards the scene. The illumination device  220  is oriented to the right (in  FIG.  2   ) to emit the polarized light towards the scene. 
     The apparatus  200  further comprises an imaging system comprising a first camera  240   a . The first camera  240   a  is placed above the illumination device  220  (in  FIG.  2   ). The first camera  240   a  is configured to capture a first image of the scene. The first camera  240   a  may be any type of camera, e.g., a conventional camera or a time-of-flight camera. 
     An aperture  242   a  is placed in front of the first camera  240   a . The aperture  242   a  may be an optical device with an opening to limit light emanating from the scene to a bundle of light rays that focus on an image plane of the first camera  240   a . The opening may determine a first field of view, e.g., a field of view of the first camera  240   a . In other words, the first camera  240   a  is configured to capture the first image of the scene by capturing light emanating from the scene in the first field of view. The light emanating from the scene comprises one or more reflection of the emitted polarized light. 
     The imaging system further comprises a second camera  240   b . The second camera  240   b  is placed below the illumination device  220  (in  FIG.  2   ). The second camera  240   b  is configured to capture a second image of the scene. The second camera  240   b  may be any type of camera, e.g., a conventional camera or a time-of-flight camera. 
     An aperture  242   b  is placed in front of the second camera  240   b . The aperture  242   b  may determine a second field of view, e.g., a field of view of the second camera  240   b . The second camera  240   b  is configured to capture the second image of the scene by capturing light emanating from the scene in the second field of view. The second camera  240   b  is configured to capture the second image based on filtered light. 
     The first camera  240   a  and the second camera  240   b  are oriented to the right (in  FIG.  2   ) such that the first camera  240   a  and the second camera  240   b  capture the first image and the second image, respectively, based on light emanating from right of the apparatus  200 . In other words, the illumination device  220 , the first camera  240   a  and the second camera  240   b  are aligned to the scene right of the apparatus  200 . Thus, the first camera  240   a  and the second camera  240   b  may mainly capture direct reflections of the emitted polarized light. The first field of view and the second field of view may at least partly overlap, e.g., the first camera  240   a  and the second camera  240   b  may be at least partly oriented to a common section of the scene. 
     The apparatus  200  further comprises a polarization filter  250  which is placed in front of the second camera  240   b , more specifically, in front of the aperture  242   b  of the second camera. The polarization filter  250  is configured to generate the filtered light by filtering the light emanating from the scene. The polarization filter  250  may block specular reflections occurring in the scene. A difference (comparison) between the first image and the second image may indicate presence of the specular reflections. 
     The apparatus  200  may represent a simple setup for detecting specular surfaces: two imagers, the first camera  240   a  and the second camera  240   b , one without a polarization filter and one with a polarization filter ( 250 ), looking at nearly the same field of view. The illumination device  220  is configured to illuminate the scene with polarized light. A first image is captured without a polarization filter, a second image is captured with a polarization filter. 
     The setup of the apparatus  200  may enable a simultaneous capture of the first image and the second image. This may be beneficial for applications in dynamic environments where the apparatus  200  moves relative to the scene, such as automotive applications. 
     In other examples, an arrangement of the first camera  240   a , the second camera  240   b , and the illumination device may be different than the one shown in  FIG.  2   . For instance, a position of the first camera  240   a  and a position of the second camera  240   b  may be swapped. 
       FIG.  3    illustrates another example of an apparatus  300  for detecting a specular surface in a scene (not shown). The scene may be located right of the apparatus  300  (in  FIG.  3   ). An illumination device (not shown in  FIG.  3   ) of the apparatus  300  is configured to emit polarized light towards the scene. 
     The apparatus  300  comprises a first camera  340   a  rotated 90 degrees relative to a second camera  340   b . A polarization filter  350  is placed in front of the aperture of the second camera  340   b . The polarization filter  350  generates filtered light by filtering the second portion of light and directs the filtered light to the second camera  340   b . 
     The apparatus  300  further comprises a beam splitter  370 . The first camera  340   a  and the second camera  340   b  are oriented (with their apertures) towards the beam splitter  370 . The beam splitter  370  is configured to direct a first portion of the light emanating from the scene to the first camera  340   a  and direct a second portion of the light emanating from the scene to the polarization filter  350 . In other words, the beam splitter  370  directs an image of the scene to both cameras, the first camera  340   a  and the second camera  340   b . The beam splitter  370  may be an optical device for splitting a beam of the light emanating from the scene into two beams. The beam splitter  370  may, e.g., comprise a half-silvered mirror or two triangular glass prisms glued together at their base. 
     The first camera  340   a  is configured to capture a first image of the scene based on the first portion of the light emanating from the scene. The light emanating from the scene comprises one or more reflection of the emitted polarized light. The second camera  340   b  is configured to capture a second image of the scene based on the filtered light. The first camera  340   a  and the second camera  340   b  may be any type of camera, e.g., a conventional camera or a time-of-flight camera. 
     The apparatus  300  further comprises a focusing lens  380  and an aperture  382  placed in front of the focusing lens. The focusing lens  380  is placed in front of the beam splitter  370  such that it focuses light emanating from the scene onto the beam splitter. The aperture  382  is oriented towards the scene. The aperture  382  may limit the light entering the focusing lens  380  and, therefore, determine a field of view of the first camera  340   a  and the second camera  340   b . 
     In other examples, the apparatus  300  may comprise other optical elements than the focusing lens  380  and the aperture  382  shown in  FIG.  3   . The first camera  340   a  and the second camera  340   b  may be arranged otherwise than shown in  FIG.  3   , for example, their positions may be swapped. 
     The apparatus  300  may further comprise processing circuitry configured to determine presence of the specular surface based on a comparison between the first image and the second image. 
     A setup of the apparatus  300  shown in  FIG.  3    may be advantageous since a field of view of the first camera  340   a  may correspond to a field of view of the second camera  340   b , e.g., the first image and the second image may show the same view of the scene. This may be helpful since only sections of the scene that are represented in both images may be taken into consideration for a comparison of the first image and the second image for detecting the specular surface in the scene. Furthermore, in the setup shown in  FIG.  3   , the first camera  340   a  and the second camera  340   b  may share common optical elements, such as the lens  380 . Therefore, the setup may be cost-efficient. 
       FIG.  4   a    and  FIG.  4   b    illustrate a side view and a front view of another example of an apparatus  400  for detecting a specular surface in a scene. The scene may be located right of the apparatus  400  in  FIG.  4   a   . The apparatus  400  comprises an illumination device (not shown) configured to emit polarized light towards the scene. 
     The apparatus  400  comprises a camera  440  oriented (with its aperture) to the scene. The camera  440  is configured to capture a first image and a second image of the scene. The apparatus  400  may switch between a first configuration for capturing the first image and a second configuration for capturing the second image. 
     For the first configuration which is shown in  FIG.  4   a   , a polarization filter  450  is placed in front of the camera  440 , e.g., between the aperture of the camera  440  and the scene. While the first configuration is set, the camera  440  captures the second image of the scene based on light emanating from the scene and being filtered by the polarization filter  450 . Thus, the polarization filter  450  is placed in front of the camera  440  while capturing the second image of the scene. The light emanating from the scene comprises one or more reflection of the emitted polarized light. In some examples, the polarization filter  450  may be configured to attenuate specular reflections of the emitted polarized light such that the camera  440  captures mainly non-specular reflections of the emitted polarized light and/or unpolarized light emanating from the scene in the first configuration. 
     For the second configuration, the polarization filter  450  is placed offset to the front of the camera  440  while capturing the first image of the scene. Consequently, the camera  440  captures the first image based on light emanating from the scene and not being filtered by the polarization filter  450 . Instead, a conventional aperture  442  is placed in front of the camera  440 . 
     To change between the first configuration and the second configuration, the apparatus  400  comprises a mechanical assembly configured to move the polarization filter  450  with respect to the camera  440 . The mechanical assembly comprises a first aperture (the conventional aperture  442 ) and a second aperture  444  mechanically coupled to a rotatable shaft  490 . The polarization filter  450  is integrated into the second aperture  444 . The first aperture  442  and the second aperture  444  are attached to the rotatable shaft  490  via a disc  446 . The first aperture  442  and the second aperture  444  are integrated on opposite sides of the disc  446 . A motor  492  may rotate the shaft  490  relative to an axis a which points towards the scene. A rotation of the shaft  490  may cause the disc  446  to rotate relative to the axis a. Rotating the disc  446  may cause the polarization filter  450  to shift its position relative to the camera  440 . 
     A setup of the apparatus  400  shown in  FIG.  4   a    and  FIG.  4   b    may be advantageous since only one camera is needed for capturing the first image as well as the second image. Hence, an alignment of several cameras in order to capture a common section of the scene in the first image and in the second image may be unnecessary. 
     When changing to the first configuration, the motor  492  may be controlled to rotate the disc  446  to a position where the polarization filter  450  is placed in front of the camera  440 . The camera  440  may be synchronized with a controller of the motor  492  such that the camera  440  captures the second image when the polarization filter  450  is placed in front of the camera  440 . Similarly, when changing to the second configuration, the motor  492  may be controlled to rotate the disc  446  to a position where the first aperture  442  is placed in front of the camera  440 . 
     In other examples, the mechanical assembly of the apparatus  400  may be arranged differently than shown in  FIG.  4   a    and  FIG.  4   b   . For instance, the mechanical assembly may move the first aperture  442  and the second aperture  444  linearly along an axis parallel to the scene. The disc  446  may be of a different shape than shown in  FIG.  4   b   , e.g., elongated, or rectangular. 
       FIG.  5   a    and  FIG.  5   b    illustrate an example first image  500   a  ( FIG.  5   a   ) and an example second image  500   b  ( FIG.  5   b   ). The first image  500   a  and the second image  500   b  are to be understood as a visualization of a first image and a second image captured by an imaging system of an apparatus for detecting a specular surface in a scene, e.g., apparatus  100 ,  200 ,  300 , or  400 , e.g., the first image  500   a  and the second image  500   b  show a simplified data structure of image data generated by the apparatus. Pixels of the image data are shown as a two-dimensional structure in  FIG.  5   a    and  FIG.  5   b   . The pixels may be arranged in the two-dimensional structure according to coordinates associated with the pixels. 
     The first image  500   a  and the second image  500   b  are captured at the same time or nearly at the same time (e.g., within a few milliseconds of time difference) by the imaging system. The first image  500   a  and the second image  500   b  represent at least partly a common section of the scene, e.g., for capturing the first image  500   a  the imaging system may have a field of view at least partly overlapping a field of view of the imaging system for capturing the second image  500   b . In case a view recorded by the first image  500   a  is shifted relative to a view recorded by the second image  500   b , the shift between the two views may be taken into consideration for comparing the first image  500   a  and the second image  500   b . 
     In the example of  FIG.  5    and  FIG.  5   b   , the first image  500   a  and the second image  500   b  are captured based on a filtering strategy corresponding to the first filtering strategy described above, e.g., the first image  500   a  is captured by the imaging system without filtering a polarization of light emanating from the scene, wherein the light emanating from the scene comprises one or more reflection of polarized light emitted by the apparatus. The second image  500   b  is captured by the imaging system based on filtered light. The filtered light is generated by a polarization filter of the apparatus by attenuating specular reflections of the polarized light. In other words, the first image  500   a  is captured without the polarization filter and the second image  500   b  is captured with polarization filter. In other examples of the present disclosure, the first image  500   a  and second image  500   b  may be captured based on a different filtering strategy. 
     The first image  500   a  comprises a structure  510   a  exhibiting a certain light intensity, represented by a dark area in  FIG.  5   a   . The structure  510   a  may correspond to a reflection of the polarized light at a specular surface in the scene. The second image  500   b  comprises a structure  510   b  of less light intensity than the structure  510   a , indicated by a dotted area in  FIG.  5   b   . Pixel coordinates of the structure  510   a  may correspond to pixel coordinates of the structure  510   b , e.g., the structure  510   a  and the structure  510   b  may represent the same section of the scene. The structure  510   b  may correspond to a reflection of unpolarized light at the specular surface in the scene or to a reflection of the polarized light and/or the unpolarized light at a non-specular surface beneath the specular surface (in case a material forming the specular surface is transparent). A decrease of light intensity of the structure  510   b  relative to the structure  510   a  may be due to the polarization filter that decreases an amount of light impinging on a sensitive area of the imaging system. 
     A processing circuitry of the apparatus may compare the first image  500   a  and the second image  500   b  for determining presence of a specular surface in the scene. The processing circuitry may determine the presence of the specular surface in the scene by determining a difference between a light intensity distribution in the first image  510   a  and a light intensity distribution in the second image  510   b . In the example of  FIG.  5   a    and  FIG.  5   b   , the processing circuitry may compare a light intensity of the structure  510   a  and a light intensity of the structure  510   b . If a difference between the light intensity of the structure  510   a  and the light intensity of the structure  510   b  exceeds a certain threshold, the processing circuitry may generate data indicating that a specular surface is detected. 
     The processing circuitry may, e.g., compare reflection characteristics derived from the first image  500   a  and reflection characteristics derived from the second image  500   b . For instance, if water is present in the scene, a reflection of the polarized light on a surface of the water may cause different reflection characteristics recorded in the first image  500   a  and the second image  500   b . 
     In some examples, the processing circuitry may generate a light intensity histogram based on the first image  500   a  and the second image  500   b . The processing circuitry may sort light intensity values of the first image  500   a  and the second image  500   b  by size resulting in a first light intensity distribution of the first image  500   a  and a second light intensity distribution of the second image  500   b . 
       FIG.  6   a   ,  FIG.  6   b    and  FIG.  6   c    illustrate example light intensity histograms  600   a ,  600   b  and  600   c  for a dry scene ( 600   a ), a moist scene ( 600   b ) and a wet scene ( 600   c ). The light intensity histograms  600   a ,  600   b  and  600   c  show a number of occurrences (pixels) on the vertical axis over a light intensity value (pixel value) on the horizontal axis, e.g., they illustrate how many pixels of an image of the (dry, moist, or wet) scene represent a certain light intensity value or range of light intensity values. 
     The light intensity histograms  600   a ,  600   b  and  600   c  comprise a first light intensity distribution  610 - 1  and a second light intensity distribution  610 - 2 . The first light intensity distribution  610 - 1  refers to a first image of the (dry, moist, or wet) scene captured without a polarization filter, such as the first image  500   a , and the second light intensity distribution  610 - 2  refers to a second image of the scene captured with a polarization filter, such as the second image  500   b . The polarization filter may attenuate specular reflections of polarized light. 
     The dry scene may show objects with a mainly non-specular surface. The moist scene may show at least some objects with a specular surface (e.g., water). The wet scene may show objects with a larger specular surface compared to the moist scene. 
     In all three light intensity histograms  600   a ,  600   b  and  600   c , the first light intensity distribution  610 - 1  results in a broader curve compared to the second light intensity distribution  610 - 2 , e.g., a standard deviation of the first light intensity distribution  610 - 1  is higher. Secondly, the curve of the first light intensity distribution  610 - 1  results in a more flattened curve compared to the second light intensity distribution  610 - 2 , e.g., a peak of the curve of the first light intensity distribution  610 - 1  is lower. Thirdly, the curve of the first light intensity distribution  610 - 1  is shifted to a higher light intensity range compared to the second light intensity distribution  610 - 2 , e.g., a mean value of the first light intensity distribution  610 - 1  is higher. This may be due to the light intensity values corresponding to a specular reflection of the polarized light being mainly dropped (filtered out) in the second image. In some examples, the deviations in the first light intensity distribution  610 - 1  compared to the second light intensity distribution  610 - 2  may indicate that a specular surface in the scene is transparent and, therefore, the second image may comprise light intensity values corresponding to a non-specular surface beneath the specular surface of the scene which may lead to more occurrences of the light intensity values corresponding to a non-specular surface in the second image. 
     A shift of the curve of the first light intensity distribution  610 - 1  along the horizontal axis relative to a curve of the second light intensity distribution  610 - 2  is bigger in the light intensity histogram  600   a  than in the light intensity histograms  600   b  and  600   c . Besides, the curve of the first light intensity distribution  610 - 1  is more pointed in the light intensity histograms  600   b  and  600   c  than in the light intensity histogram  600   a . This may be due to a larger total area of specular surfaces in the moist scene ( 600   b ) and the wet scene ( 600   c ) compared to the dry scene ( 600   c ). 
     There may be mathematical relation between the total area of specular surface in the scene and a difference between a mean value, a peak and/or a standard deviation of the first light intensity distribution  610 - 1  and the second light intensity distribution  610 - 2 . Thus, a processing circuitry may use the mathematical relation to infer from a comparison of the first light intensity distribution  610 - 1  (first image) and the second light intensity distribution  610 - 2  (second image) if a specular surface is present in the scene (and, optionally, how big the total area of the specular surface is). For instance, if the difference falls below a certain threshold, the processing circuitry may determine that a specular surface is present in the scene. Additionally, the processing circuitry may infer from a comparison of the first image and the second image if the specular surface belongs to a transparent object. 
     Referring back to  FIG.  5   a    and  FIG.  5   b   , alternatively to the above-mentioned techniques, a processing circuitry may be configured to determine the presence of the specular surface in the scene by determining a difference between at least one of a sum, a standard deviation, a mean value of light intensities of the first image  500   a  and the second image  500   b . For instance, the processing circuitry may calculate a sum of light intensities (pixel values) of the first image  500   a  and a sum of light intensities (pixel values) of the second image  500   b . As the polarization filter applied for capturing the second image  500   b  removes specular reflections, a corresponding light intensity value (direct reflection value) may only partly be recorded in the second image  500   b . Thus, the processing circuitry may determine a difference in the sum of light intensities of the first image  500   a  and the sum of light intensities of the second image  500   b . If the difference exceeds a certain threshold, the processing circuitry may generate data indicating a specular surface is detected. 
     In some examples, the processing circuitry may be configured to convolute the first image  500   a  and the second image  500   b . For instance, the light intensities of the first image  500   a  and the light intensities of the second image  500   b  may be convoluted with a filter-kernel. Convoluting may be performed by adding light intensities of each pixel to light intensities of neighboring pixels, weighted based on the filter-kernel. The filter-kernel is a matrix of real numbers used for weighting pixel data. The processing circuitry may be further configured to apply edge detection to the convoluted first image  500   a  and the convoluted second image  500   b . Edge detection is a mathematical method for detecting edges or curves in a digital image by identifying pixels at which light intensities change sharply (or has discontinuities) relative to neighboring pixels. The processing circuitry may be further configured to determine the presence of the specular surface based on comparing at least one detected edge of the first image  500   a  and at least one detected edge of the second image  500   b . For instance, the processing circuity may detect sharp edges at the structure  510   a  in the first image  500   a  and weaker or no edges at the structure  510   b  in the second image  500   b . The processing circuitry may determine whether a specular surface is present based on a difference in intensity, in shape, or in location of the detected edges between the first image  500   a  and the second image  500   b . 
     In other examples, the first image  500   a  and the second image  500   b  may be captured by at least one time-of-flight camera of the imaging system. In this case, the processing circuitry may be further configured to, if presence of the specular surface is determined, determine a distance between the specular surface and a non-specular surface beneath the specular surface based on the comparison of the first image  500   a  and the second image  500   b . The time-of-flight camera may provide measurement data indicating a time difference between an emission of the polarized light and a capturing time when a reflection of the polarized light impinges on a sensitive area of the time-of-flight camera. A distance between the imaging system and objects in the scene which caused the reflection may be inferred from the measurement data. For instance, if a transparent material with a specular surface such as water is present in the scene, the first image  500   a  may represent measurement data generated based on specular reflections at a specular surface of the water. The second image  500   b  may represent measurement data generated based on non-specular reflections of light passing through the water. The non-specular reflection may be caused by a reflection at a non-specular surface beneath the water, such as a ground where the water is located on. The processing circuit may determine a distance between the imaging system and the specular surface of the water and a distance between the imaging system and the non-specular surface based on the measurement data. Hence, the processing circuit may infer a water level or depth of water by subtracting the distances derived from the first image  500   a  and from the second image  500   b . 
     In some examples, the processing circuitry may be configured to determine reflection characteristics of the specular surface based on the comparison of the first image  500   a  and the second image  500   b . For instance, the processing circuitry may determine the reflection characteristics by deriving a transparency or a spectral reflectance of a material forming the specular surface based on the comparison. For deriving the transparency or the spectral reflectance, the processing circuitry may compare light intensities and wavelengths of the first image  500   a  (without polarization filter) and light intensities and wavelengths, recorded by the second image  500   b  (with polarization filter). If the processing circuitry determines presence of the specular surface, the processing circuitry may further be configured to classify the material forming the specular surface based on the reflection characteristics. Since reflection characteristics may be material-specific, the processing circuitry may compare the reflection characteristics with one or more predefined reflection characteristics being related to one or more candidate materials. The processing circuitry may classify the material as, e.g., water, snow, oil, metal, or glass. The processing circuitry may alternatively classify the material by applying an object recognition algorithm (computer vision) to the first image  500   a  and the second image  500   b . 
     In some examples, the processing circuitry may be further configured to, if presence of the specular surface is determined, determine whether the specular surface is located on a roadway. For instance, the processing circuitry may determine, based on the first image  500   a   and second image  500   b , if a reflection characteristic indicated by pixels representing a surrounding of the detected specular surface matches (known) reflection characteristics of the roadway. The processing circuitry may further be configured to, if it is determined that the specular surface is located on the roadway, estimate a friction coefficient of a vehicle on the roadway based on a material forming the specular surface. For instance, the processing circuitry may have classified the material as water. Since the friction coefficient is material-specific, the processing circuitry may derive the friction coefficient from the classification of the material, e.g., by extracting the friction coefficient of water from a look-up-table. In case the specular surface is formed by a transparent material such as water, the processing circuitry may additionally determine a depth of the transparent material (a water level) as described above. Then, the processing circuitry may determine the friction coefficient based on the classified material and on the depth of the classified material. 
     It is to be noted that the first image  500   a  and the second image  500   b  shown in  FIG.  5   a    and  FIG.  5   b    are meant as an example. In other examples, the first image  500   a  and the second image  500   b  may show a different scene without specular surfaces or with more specular surfaces than shown in  FIG.  5   a    and  FIG.  5   b   . In other examples, the first image  500   a  and the second image  500   b  may show objects in the scene, they may comprise any information about light emanating from the scene, e.g., measurement data of a time-of-flight camera, a light intensity, or a wavelength (color) of the light. A processing circuitry may use any information captured by the first image  500   a  and the second image  500   b  to infer if a specular surface is present in the scene. 
       FIG.  7    illustrates an example of a vehicle  700  comprising an apparatus  710  for detecting a specular surface in a scene. For instance, the scene may be a roadway on which the vehicle  700  may drive. The apparatus  710  may be, e.g., the apparatus  100 ,  200 ,  300 , or  400 . The vehicle may be any apparatus for transporting people or cargo. For instance, the vehicle may comprise wheels driven by an engine (and optionally a powertrain system). In particular, the vehicle may be an automobile, a train, a truck, a motorcycle, or a tractor. 
     The apparatus  710  comprises an illumination device  720  configured to emit polarized light towards the scene. In some examples, the illumination device  720  may be integrated into a headlight of the vehicle  700 . In this case, the illumination device  720  may comprise a first light source configured to emit the polarized light and a second light source configured to emit unpolarized light. The second light source may be a conventional headlight for illuminating a surrounding of the vehicle  700 . 
     The apparatus  710  further comprises an imaging system  740 . For instance, the imaging system  740  may comprise one or more camera (imager) which are implemented in a front of the vehicle  700 . The first light-source may emit light which is polarized and modulated. The camera may be sensitive to the polarized and modulated light. The camera may generate a first image without a polarization filter and based on reflections of the polarized and modulated light and a second image with a polarization filter. 
     A processing circuitry  760  of the apparatus  710  may be configured to determine presence of the specular surface based on a comparison of the first image and the second image. The processing circuitry may be further configured to, if presence of the specular surface is determined, to determine whether the specular surface is located on a roadway. And, if it is determined that the specular surface is located on the roadway, estimate a friction coefficient of the vehicle  700 , especially of wheels of the vehicle, on the roadway based on a classified material forming the specular surface. 
     The estimated friction coefficient may be input to an advanced driver assistance system (ADAS) of the vehicle  700 . The ADAS may estimate a brake path based on a velocity of the vehicle  700  and the estimated friction coefficient. If the estimated brake path exceeds a certain threshold, the ADAS may output a warning signal or automatically reduce the velocity. 
       FIG.  8    illustrates a flowchart of an example of a method  800  for operating an apparatus for detecting a specular surface in a scene. The apparatus comprises an illumination device, an imaging system, a polarization filter, and processing circuitry, such as the apparatus  100 ,  200 ,  300 , or  400 . 
     The method  800  comprises emitting  810  polarized light towards the scene, capturing  820  a first image of the scene based on light emanating from the scene. The light emanating from the scene comprises one or more reflection of the emitted polarized light. The method  800  further comprises generating  830  filtered light by filtering the light emanating from the scene through the polarization filter, capturing  840  a second image of the scene based on the filtered light and determining  850  presence of the specular surface in the scene based on a comparison of the first image and the second image. 
     More details and aspects of the method  800  are explained in connection with the proposed technique or one or more examples described above, e.g., with reference to  FIG.  1   . The method  800  may comprise one or more additional optional features corresponding to one or more aspects of the proposed technique, or one or more examples described above. 
     The method  800  may allow a detection of specular surfaces in the scene which may be in particular useful for water detection in automotive applications or for fitness devices with sweat detection. 
     A basic idea of the implementation to combine conventional imaging and polarization imaging may be applicable in other application fields besides for detecting a specular surface in a scene. For instance, techniques described above, e.g., with reference to  FIG.  1   , may be used for determining reflection characteristics of objects in the scene. This may be useful for material classification since reflection characteristics are material specific. Examples for material classification are described hereinafter with reference to  FIG.  9    and  FIG.  10   . 
       FIG.  9    illustrates an example of an apparatus  900  for classifying a material in a scene  910 . The apparatus  900  comprises an illumination device  920  configured to emit polarized light  930  towards the scene  910 . A portion of the emitted polarized light  930  may impinge on a surface of the material and be reflected off of the surface. 
     The apparatus  900  further comprises an imaging system  940  configured to capture a first image of the scene  910  based on light emanating from the scene  910 . The light emanating from the scene  910  comprises one or more reflection of the emitted polarized light  930 , e.g., reflection  934  and reflection  932 . The reflection may be caused by parts of the emitted polarized light being reflected off of the material. 
     The imaging system  940  is further configured to capture a second image of the scene based on filtered light  936 . The apparatus  900  further comprises a polarization filter  950  configured to generate the filtered light by filtering the light emanating from the scene  910 . 
     The illumination device  920 , the imaging system  940  and the polarization filter  950  may be setup and configured analogously to the illumination devices, imaging systems and polarization filters described above with respect to the apparatuses  100 ,  200 ,  300 , and  400 . Hence, it is referred to the above description for the further structural details of the illumination device  920 , the imaging system  940  and the polarization filter  950 . 
     The apparatus  900  further comprises processing circuitry  960  configured to determine reflection characteristics of the material based on a comparison of the first image and the second image and classify the material based on the reflection characteristics. The processing circuitry  960  may be configured to determine the reflection characteristics of the material by determining a difference between at least one of a sum, a standard deviation, a mean value of light intensities of the first image and the second image. An example approach of how the processing circuitry  960  may determine the reflection characteristics is explained with reference to  FIG.  5   a    and  FIG.  5   b   . 
     The processing circuitry  960  may be configured to classify the material by comparing the determined reflection characteristics of the material with one or more predefined reflection characteristic being related to one or more candidate material. For instance, the processing circuitry  960  may access a database of candidate materials which registers the candidate materials with respective reflection characteristics. The processing circuitry  960  may compare entries of the database with the determined reflection characteristics. If one of the entries lies within a predefined tolerance range around the determined reflection characteristics, the processing circuitry  960  may select a corresponding candidate material as match for the material. 
     The apparatus  900  may be used for material classification, e.g., in industrial or medical applications. The apparatus  900  may be advantageous since it classifies materials optically without mechanically or chemically affecting the materials. 
     In some examples, the processing circuitry  960  may be configured to determine whether the determined reflection characteristics correspond to predefined reflection characteristics of human skin. For instance, the processing circuitry  960  may access a data storage storing a value range of reflection characteristics which are typical for human skin. If it is determined that the determined reflection characteristics correspond to the predefined reflection characteristics of human skin, the processing circuitry  960  may be configured to classify the material as human skin. In other words, if the determined reflection characteristics lie within the value range, the processing circuitry  960  may declare the material as human skin. 
     On the one hand, if the material is classified as human skin, the apparatus  900  may be configured to perform a face recognition process. On the other hand, if the material is not classified as human skin, the apparatus  900  may be configured to output data indicating that the material in the scene is not part of a human. 
     In the latter case, the apparatus  900  may measure how deep light enters into the human skin in the illuminated scene before being reflected towards the imaging system  940 . Since human skin exhibits predefined reflection characteristics, they may be compared with reflection characteristics derived from a comparison of the (normal intensity) first image and the (filtered) second image. The first image and the second image may be placed in an amplitude/light intensity histogram to compare the resulting reflection characteristics with the predefined reflection characteristics of human skin. 
     The apparatus  900 , as described in the latter, may be used for anti-spoofing in face recognition processes. This may be useful for smartphones or other devices with a user login based on face recognition (face-ID). The apparatus  900  may prevent an unlocking of the concerned device if an unauthorized user tries to deceive the face recognition by wearing a mask of an authorized user. 
       FIG.  10    illustrates a flowchart of an example of a method  1000  for operating an apparatus for classifying a material in a scene, such as the apparatus  900 . The apparatus comprises an illumination device, an imaging system, a polarization filter, and processing circuitry. 
     The method  1000  comprises emitting  1010  polarized light towards the scene and capturing  1020  a first image of the scene based on light emanating from the scene. The light emanating from the scene comprises one or more reflection of the emitted polarized light. The method  1000  further comprises generating  1030  filtered light by filtering the light emanating from the scene through the polarization filter and capturing  1040  a second image of the scene based on the filtered light. The method  1000  further comprises determining  1050  reflection characteristics of the material based on a comparison of the first image and the second image and classifying  1060  the material based on the reflection characteristics. 
     More details and aspects of the method  1000  are explained in connection with the proposed technique or one or more examples described above, e.g., with reference to  FIG.  9   . The method  1000  may comprise one or more additional optional features corresponding to one or more aspects of the proposed technique, or one or more examples described above. 
     The method  1000  may allow a classification of a material in the scene which may be in particular useful for anti-spoofing. 
     Aspects 
     The following aspects pertain to further implementations: 
     Implementation (1) is an apparatus for detecting a specular surface in a scene comprising an illumination device configured to emit polarized light towards the scene, an imaging system configured to capture a first image of the scene based on light emanating from the scene wherein the light emanating from the scene comprises one or more reflection of the emitted polarized light and wherein the imaging system is further configured to capture a second image of the scene based on filtered light. The apparatus comprises a polarization filter configured to generate the filtered light by filtering the light emanating from the scene and processing circuitry configured to determine presence of the specular surface in the scene based on a comparison of the first image and the second image. 
     Implementation (2) is the apparatus of implementation (1) wherein the emitted polarized light exhibits one of a right-handed circular polarization and a left-handed circular polarization, and wherein the polarization filter is configured to filter the other one of the right-handed circular polarization and the left-handed circular polarization out of the light emanating from the scene. 
     Implementation (3) is the apparatus of implementation (1) wherein the emitted polarized light exhibits a predefined linear polarization, and wherein the polarization filter is configured to filter the light emanating from the scene by attenuating light exhibiting the predefined linear polarization. 
     Implementation (4) is the apparatus of any one of implementations (1) to (3) wherein the imaging system comprises a first camera configured to capture the first image of the scene and a second camera configured to capture the second image of the scene wherein the polarization filter is placed in front of the second camera. 
     Implementation (5) is the apparatus of implementation (4) wherein the first camera is configured to capture the first image of the scene by capturing light emanating from the scene in a first field of view and wherein the second camera is configured to capture the second image of the scene by capturing light emanating from the scene in a second field of view and wherein the first field of view and the second field of view at least partly overlap. 
     Implementation (6) is the apparatus of implementation (4) or (5) wherein the imaging system further comprises a beam splitter configured to direct a first portion of the light emanating from the scene to the first camera and direct a second portion of the light emanating from the scene to the second camera. 
     Implementation (7) is the apparatus of any one of implementations (4) to (6) wherein at least one of the first camera and the second camera is a time-of-flight camera. 
     Implementation (8) is the apparatus of any one of implementations (1) to (3) wherein the imaging system comprises a camera configured to capture the first image and the second image of the scene and a mechanical assembly configured to move the polarization filter with respect to the camera wherein the polarization filter is placed in front of the camera while capturing the second image of the scene and wherein the polarization filter is placed offset to the front of the camera while capturing the first image of the scene. 
     Implementation (9) is the apparatus of implementation (8), wherein the mechanical assembly comprises a first aperture and a second aperture mechanically coupled to a rotatable shaft, and wherein the polarization filter is integrated into the second aperture. 
     Implementation (10) is the apparatus of implementation (8) or (9) wherein the camera is a time-of-flight camera. 
     Implementation (11) is the apparatus of implementation (7) or (10) wherein the processing circuitry is further configured to, if presence of the specular surface is determined, determine a distance between the specular surface and a non-specular surface beneath the specular surface based on the comparison of the first image and the second image. 
     Implementation (12) is the apparatus of any one of implementations (1) to (11) wherein the illumination device comprises a first light source configured to emit the polarized light towards the scene and a second light source configured to emit unpolarized light towards the scene. 
     Implementation (13) is the apparatus of any one of implementations (1) to (12) wherein the processing circuitry is configured to determine the presence of the specular surface in the scene by determining a difference between a light intensity distribution in the first image and a light intensity distribution in the second image. 
     Implementation (14) is the apparatus of any one of implementations (1) to (13) wherein the processing circuitry is configured to determine the presence of the specular surface in the scene by determining a difference between at least one of a sum, a standard deviation, a mean value of light intensities of the first image and the second image. 
     Implementation (15) is the apparatus of any one of implementations (1) to (14) wherein the processing circuitry is configured to convolute the first image and the second image, apply edge detection to the convoluted first image and the convoluted second image and determine the presence of the specular surface based on comparing at least one detected edge of the first image and at least one detected edge of the second image. 
     Implementation (16) is the apparatus of any one of implementations (1) to (15) wherein the processing circuitry is further configured to determine reflection characteristics of the specular surface based on a comparison of the first image and the second image and, if presence of the specular surface is determined, classify a material forming the specular surface based on the reflection characteristics. 
     Implementation (17) is the apparatus of implementation (16) wherein the processing circuitry is further configured to classify the material as at least one of water, snow, oil, metal, glass. 
     Implementation (18) is the apparatus of implementation (16) or (17) wherein the processing circuitry is further configured to, if presence of the specular surface is determined, determine whether the specular surface is located on a roadway and, if it is determined that the specular surface is located on the roadway, estimate a friction coefficient of a vehicle on the roadway based on the classified material. 
     Implementation (19) is the apparatus of any one of implementations (1) to (15) wherein the processing circuitry is further configured to, if presence of the specular surface is determined, determine whether the specular surface is located on skin of a human and, if it is determined that the specular surface is located on the skin of the human, classify the specular surface as sweat. 
     Implementation (20) is a vehicle comprising the apparatus for detecting a specular surface in a scene according to any one of implementations (1) to (17) wherein the processing circuitry is further configured to, if presence of the specular surface is determined, determine whether the specular surface is located on a roadway and, if it is determined that the specular surface is located on the roadway, estimate a friction coefficient of the vehicle on the roadway based on a classified material forming the specular surface. 
     Implementation (21) is the vehicle of implementation (20) wherein the illumination device is integrated into a headlight of the vehicle. 
     Implementation (22) is a method for operating an apparatus for detecting a specular surface in a scene wherein the apparatus for detecting the specular surface comprises an illumination device, an imaging system, a polarization filter, and processing circuitry. The method comprises emitting polarized light towards the scene, capturing a first image of the scene based on light emanating from the scene wherein the light emanating from the scene comprises one or more reflection of the emitted polarized light. The method further comprises generating filtered light by filtering the light emanating from the scene through the polarization filter, capturing a second image of the scene based on the filtered light and determining presence of the specular surface in the scene based on a comparison of the first image and the second image. 
     Implementation (23) is an apparatus for classifying a material in a scene comprising an illumination device configured to emit polarized light towards the scene, an imaging system configured to capture a first image of the scene based on light emanating from the scene wherein the light emanating from the scene comprises one or more reflection of the emitted polarized light and wherein the imaging system is further configured to capture a second image of the scene based on filtered light. The apparatus further comprises a polarization filter configured to generate the filtered light by filtering the light emanating from the scene; and processing circuitry configured to determine reflection characteristics of the material based on a comparison of the first image and the second image and classify the material based on the reflection characteristics. 
     Implementation (24) is the apparatus of implementation (23) wherein the emitted polarized light exhibits one of a right-handed circular polarization and a left-handed circular polarization and wherein the polarization filter is configured to filter the other one of the right-handed circular polarization and the left-handed circular polarization out of the light emanating from the scene. 
     Implementation (25) is the apparatus of implementation (23) wherein the emitted polarized light exhibits a predefined linear polarization and wherein the polarization filter is configured to filter the light emanating from the scene by attenuating light exhibiting the predefined linear polarization. 
     Implementation (26) is the apparatus of any one of implementations (23) to (25) wherein the imaging system comprises a first camera configured to capture the first image of the scene and a second camera configured to capture the second image of the scene wherein the polarization filter is placed in front of the second camera. 
     Implementation (27) is the apparatus of any one of implementations (23) to (26) wherein the first camera is configured to capture the first image of the scene by capturing light emanating from the scene in a first field of view and wherein the second camera is configured to capture the second image of the scene by capturing light emanating from the scene in a second field of view and wherein the first field of view and the second field of view at least partly overlap. 
     Implementation (28) is the apparatus of implementation (26) or (27) wherein the imaging system further comprises a beam splitter configured to direct a first portion of the light emanating from the scene to the first camera and direct a second portion of the light emanating from the scene to the second camera. 
     Implementation (29) is the apparatus of any one of implementations (23) to (25) wherein the imaging system comprises a camera configured to capture the first image and the second image of the scene and a mechanical assembly configured to move the polarization filter with respect to the camera wherein the polarization filter is placed in front of the camera while capturing the second image of the scene and wherein the polarization filter is placed offset to the front of the camera while capturing the first image of the scene. 
     Implementation (30) is the apparatus of implementation (29) wherein the mechanical assembly comprises a first aperture and a second aperture mechanically coupled to a rotatable shaft and wherein the polarization filter is integrated into the second aperture. 
     Implementation (31) is the apparatus of any one of implementations (23) to (30) wherein the illumination device comprises a first light source configured to emit the polarized light towards the scene and a second light source configured to emit unpolarized light towards the scene. 
     Implementation (32) is the apparatus of any one of implementations (23) to (31) wherein the processing circuitry is configured to determine the reflection characteristics of the material by determining a difference between a light intensity distribution in the first image and a light intensity distribution in the second image. 
     Implementation (33) is the apparatus of any one of implementations (23) to (32) wherein the processing circuitry is configured to determine the reflection characteristics of the material by determining a difference between at least one of a sum, a standard deviation, a mean value of light intensities of the first image and the second image. 
     Implementation (34) is the apparatus of any one of implementations (23) to (33) wherein the processing circuitry is configured to classify the material by comparing the determined reflection characteristics of the material with one or more predefined reflection characteristic, the one or more predefined reflection characteristic being related to one or more candidate material. 
     Implementation (35) is the apparatus of any one of implementations (23) to (34) wherein the processing circuitry is configured to determine whether the determined reflection characteristics correspond to predefined reflection characteristics of human skin and, if it is determined that the determined reflection characteristics correspond to the predefined reflection characteristics of human skin, classify the material as human skin. 
     Implementation (36) is the apparatus of implementation (35) wherein the apparatus is further configured to, if the material is classified as human skin, perform a face recognition process. 
     Implementation (37) is the apparatus of implementation (35) or (36) wherein, if the material is not classified as human skin, the apparatus is configured to output data indicating that the material in the scene is not part of a human. 
     Implementation (38) is a method for operating an apparatus for classifying a material in a scene, wherein the apparatus comprises an illumination device, an imaging system, a polarization filter, and processing circuitry. The method comprises emitting polarized light towards the scene and capturing a first image of the scene based on light emanating from the scene wherein the light emanating from the scene comprises one or more reflection of the emitted polarized light. The method further comprises generating filtered light by filtering the light emanating from the scene through the polarization filter, capturing a second image of the scene based on the filtered light, determining reflection characteristics of the material based on a comparison of the first image and the second image and classifying the material based on the reflection characteristics. 
     The aspects and features described in relation to a particular one of the previous aspects may also be combined with one or more of the further aspects to replace an identical or similar feature of that further aspect or to additionally introduce the features into the further aspect. 
     Aspects may further be or relate to a (computer) program including a program code to execute one or more of the above methods when the program is executed on a computer, processor, or other programmable hardware component. Thus, steps, operations, or processes of different ones of the methods described above may also be executed by programmed computers, processors, or other programmable hardware components. Aspects may also cover program storage devices, such as digital data storage media, which are machine-, processor- or computer-readable and encode and/or contain machine-executable, processor-executable or computer-executable programs and instructions. Program storage devices may include or be digital storage devices, magnetic storage media such as magnetic disks and magnetic tapes, hard disk drives, or optically readable digital data storage media, for example. Other aspects may also include computers, processors, control units, (field) programmable logic arrays ((F)PLAs), (field) programmable gate arrays ((F)PGAs), graphics processor units (GPU), application-specific integrated circuits (ASICs), integrated circuits (ICs) or system-on-a-chip (SoCs) systems programmed to execute the steps of the methods described above. 
     It is further understood that the disclosure of several steps, processes, operations, or functions disclosed in the description or claims shall not be construed to imply that these operations are necessarily dependent on the order described, unless explicitly stated in the individual case or necessary for technical reasons. Therefore, the previous description does not limit the execution of several steps or functions to a certain order. Furthermore, in further aspects, a single step, function, process, or operation may include and/or be broken up into several sub-steps, -functions, -processes or -operations. 
     If some aspects have been described in relation to a device or system, these aspects should also be understood as a description of the corresponding method. For example, a block, device or functional aspect of the device or system may correspond to a feature, such as a method step, of the corresponding method. Accordingly, aspects described in relation to a method shall also be understood as a description of a corresponding block, a corresponding element, a property or a functional feature of a corresponding device or a corresponding system. 
     The following claims are hereby incorporated in the detailed description, wherein each claim may stand on its own as a separate aspect. It should also be noted that although in the claims a dependent claim refers to a particular combination with one or more other claims, other aspects may also include a combination of the dependent claim with the subject matter of any other dependent or independent claim. Such combinations are hereby explicitly proposed, unless it is stated in the individual case that a particular combination is not intended. Furthermore, features of a claim should also be included for any other independent claim, even if that claim is not directly defined as dependent on that other independent claim.