DEVICE AND METHOD FOR CALCULATING A LIGHT AND / OR SOUND WAVE GUIDE IN AN AUGMENTED REALITY SYSTEM WITH AT LEAST ONE OBJECT

Description

[0001] The invention relates to a device and a method for calculating the guidance of light and / or sound waves in an augmented reality system with at least one object, as well as an associated computer program product (see independent claims 1, 9, and 10). Augmented reality, abbreviated AR, is a relatively new field of technology in which, for example, additional visual and, where applicable, partially audiological information is superimposed on the current optical, audiological, or possibly also haptic perception of the real environment. This information can address all human sensory modalities. A fundamental distinction is made between the so-called "see-through" technology, in which a user looks into the real environment through a translucent display unit, and the so-called "feed-through" technology, in which the real environment is captured by a recording unit or...The image is captured by a recording device, such as a camera, and mixed or overlaid with a computer-generated virtual image before being played back on an output or display unit.

[0002] As a result, a user simultaneously perceives both the real environment and the virtual image components generated by, for example, computer graphics, as a combined representation (a composite image). This blending of real and virtual image components into "augmented reality" allows the user to perform their actions while directly incorporating the superimposed and thus simultaneously perceptible additional information.

[0003] For an "augmented reality" to be as realistic as possible, a key problem lies in determining the path of light and / or sound waves. This path of light can be understood as adapting the virtual lighting conditions to the real lighting conditions, particularly by inserting virtual shadow and / or highlight areas for the virtual object being inserted.

[0004] To ensure that computer-generated objects blend as naturally as possible into the real-world environment, the object's lighting is crucial. Point and area light sources play a particularly important role here. While diffuse background lighting / brightness can be easily determined via sensors on the device, accurately calculating the available point and area light sources remains a challenge. These sources make a decisive contribution to a realistic rendering of the objects by creating reflections and realistic shadows. This is especially important when the light source is moving (e.g., due to passing vehicles).

[0005] Not only the lighting is crucial for a realistic depiction of the object. The sound wave propagation, i.e., .Sound propagation, amplification, attenuation, and superposition all play a role. The direction of sound waves can be altered by different materials used on objects and by the placement of those objects.

[0006] In particular, the implementation of virtual lighting or the integration of virtual shadow and / or bright areas in "augmented reality systems" has so far been treated largely in a very static way, whereby the position of a light source was integrated into the virtual 3D model in a fixed or unchangeable manner.

[0007] From Walton et al.: "Synthesis of Environment Maps for Mixed Reality", 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), it is known that objects with a reflective surface can reflect the immediate surroundings (which are recorded simultaneously with a camera).

[0008] The disadvantage here is that changes in the position of the user, the recording unit, or the light source, which directly lead to a change in the lighting conditions, cannot be taken into account.

[0009] US 2018 / 0374276 A1 refers to a 3-dimensional representation of a physical environment into which virtual objects are to be inserted.

[0010] WO 2018 / 118730 A1 discloses a method for illuminating virtual objects comprising the recognition of a three-dimensional representation of a physical environment as well as the recognition of a three-dimensional world coordinate position for a virtual object in the physical environment.

[0011] US 2020 / 0302681 A1 deals with user-controlled interaction with a virtually generated space in which virtual objects are displayed or placed. The selection of objects to be chosen for the space design can be suggested heuristically, rule-based, or using a neural network trained on catalogs or previously designed spaces.

[0012] WO 2018 / 200337 A1 refers to a method that reveals a global exposure solution for an MR (mixed reality) scene.

[0013] The object of the invention is now to avoid the aforementioned disadvantages and to provide a method or device that is as universally applicable as possible for displaying virtual 3D objects embedded in a real environment.

[0014] The object of the invention is to provide a method and a control device that are improved compared to the prior art mentioned at the outset.

[0015] This task is solved by independent claims. Advantageous further training is the subject of dependent claims.

[0016] The invention claims a device for computer-aided calculation of light and sound wave guidance in an augmented reality system with at least one object, comprising a computing unit that displays an augmented reality with the at least one object as well as sensory impressions of the at least one object and presents it on an output unit of the augmented reality system for a user, wherein the computing unit is coupled with a detection device for detecting a first environmental area in which the at least one object is displayed, characterized in that The sensory impressions, which are visually and audibly pronounced, are supplemented by the calculation of the light and / or sound wave guidance in a delimited environment by the device, wherein the light and sound wave guidance is calculated using a predefinable and / or simulable 3D metamodel of the delimited environment, which comprises a second environmental area with objects arranged therein, the first environmental area with the at least one depicted object and one or more identifiable light- and sound-transmitting areas between the second and the first environmental area, wherein the first environmental area comprises an interior area of ​​such a delimited environment and the second environmental area comprises an exterior area of ​​the delimited environment, wherein light sources in the second environmental area are used to calculate the light and sound wave guidance.The 3D metamodel includes weather-related brightness in the second environment at a predefined and / or simulated time of day and year, noise from sources in the second environment at a predefined and / or simulated time of day and year, the angle of incidence of light and / or sound through the light- and sound-transmitting area(s) onto the at least one object, as well as light intensity from other light sources and noise level from other sources in the first environment, taking into account weather data that influences weather-related brightness and attenuates noise from sources in the second environment. Furthermore, the 3D metamodel is represented as a complete or partial knowledge graph, which includes at least one branch of the branches forming the knowledge graph (by connecting contained nodes) and is stored together with geometric relationships derived from the 3D metamodel.wherein the knowledge graph is pre-formed and optionally stored based on a prepared, digitally based representation of the surrounding areas and / or the light- and / or sound-transmitting areas, wherein the knowledge graph can be extended with a lighting model using a data-based learning method, wherein the user provides feedback (F) to the learning method regarding their subjective sensory impression of the calculated lighting for at least one object.

[0017] Visual sensory impressions refer to perception via the eyes, while audiological sensory impressions are perceived through hearing.

[0018] A defined environment can be a structure, building, ship, aircraft, or vehicle. The first environmental area typically encompasses the interior of such a defined environment. The second environmental area typically encompasses the exterior of the defined environment. Areas permeable to light and sound can include windows, air shafts, pipe systems, and drains. Light sources can be the sun, streetlights, lamps, etc. Noise sources can include animals, equipment, and even heavy rain.

[0019] A detection system can include one or more cameras, e.g., light field or lidar cameras. Other sensors, e.g., microphones, etc., can also be used as detection systems.

[0020] According to the invention, a light guidance or sound wave guidance simulation is linked or coupled with the display of an object on the AR system using a 3D model that is not visible in AR. This makes the object's representation realistic and thus increases the user's immersion. In AR systems where real objects are captured with a camera and displayed on an output unit, e.g., a screen (e.g., a vehicle display, iPad), this can lead to an indistinguishable difference between real and rendered objects. However, even for devices where reality is directly visible (see-through displays, HoloLens), there is a significant improvement in the representation of the depicted objects.

[0021] The sun's position, which varies depending on the time of day and year, can influence the angle of incidence of light through the translucent area(s).

[0022] The 3D metamodel can take a meta-perspective on the aforementioned areas outside of a first environmental area detectable by the detection device.

[0023] The brightness and / or noise from noise sources in the first ambient area can be detected by the detection device.

[0024] When calculating the light and sound wave guidance in relation to the at least one object, absorption or reflection of light and sound by objects located in front of it in the light and sound propagation cone through the light- and sound-transmitting area can be taken into account.

[0025] The 3D metamodel can model a building in an environment, where the first environment area represents the interior, the second environment area the exterior, and the light and / or sound-permeable areas can be defined as windows in the wall of the building.

[0026] Preferably, the 3D metamodel is represented by a BIM model (Building Information Modeling). It can also be represented by a point cloud.

[0027] Another aspect of the invention provides a method for the computer-aided calculation of a light and sound wave guidance in an augmented reality system with at least one object, wherein a device for computer-aided calculation comprises a computing unit that displays an augmented reality with the at least one object as well as sensory impressions of the at least one object on an output unit of the augmented reality system for a user, wherein the computing unit is coupled with a detection device for detecting a first environmental area in which the at least one object is displayed, characterized in that The sensory impressions, which are visually and audibly pronounced, are supplemented by the calculation of the light and sound wave guidance in a delimited environment, wherein the light and sound wave guidance is calculated using a predefinable and / or simulable 3D metamodel of the delimited environment, which includes a second environmental area with objects arranged therein, the first environmental area with the at least one depicted object and one or more identifiable light- and sound-transmitting areas between the second and the first environmental area, wherein the first environmental area comprises an interior area of ​​such a delimited environment and the second environmental area comprises an exterior area of ​​the delimited environment, wherein light sources in the second environmental area are used to calculate the light and sound wave guidance.The 3D metamodel includes weather-related brightness in the second environment at a predefined and / or simulated time of day and year, noise from sources in the second environment at a predefined and / or simulated time of day and year, the angle of incidence of light and / or sound through the light- and sound-transmitting area(s) onto the at least one object, as well as light intensity from other light sources and noise level from other sources in the first environment, taking into account weather data that influences weather-related brightness and attenuates noise from sources in the second environment. Furthermore, the 3D metamodel is represented as a complete or partial knowledge graph, which includes at least one branch of the branches forming the knowledge graph (by connecting contained nodes) and is stored together with geometric relationships derived from the 3D metamodel.wherein the knowledge graph is pre-formed and optionally stored based on a prepared, digitally based representation of the surrounding areas and / or the light- and / or sound-transmitting areas, wherein the knowledge graph can be extended with a lighting model using a data-based learning method, wherein the user provides feedback (F) to the learning method regarding their subjective sensory impression of the calculated lighting for at least one object.

[0028] The units or devices that are set up to perform such process steps can be implemented in hardware, firmware and / or software.

[0029] Another aspect of the invention is a computer program (product) with program code means for carrying out the method according to one of the preceding method claims, if it runs on a computer or a computing unit of the type mentioned above or is stored on a computer-readable storage medium.

[0030] The computer program or product can be stored on a computer-readable storage medium. The computer program or product can be written in a common programming language (e.g., C++, Java). The processing equipment can comprise a standard computer or server with appropriate input, output, and storage capabilities. This processing equipment can be integrated into the control unit or its components.

[0031] The method and the computer program (product) can be further developed or refined analogously to the aforementioned device and its further developments.

[0032] Further advantages, details and developments of the invention will become apparent from the following description of exemplary embodiments in conjunction with the drawings. Figure 1 Figure 1 schematically shows an embodiment of the invention in which objects are placed in the field of view or detection of the AR system so that the illumination of the object can be calculated, and Figure 2 The diagram schematically shows another embodiment of the invention, in which lighting calculation can be further improved.

[0033] Figure 1Figure 1 shows an AR system (AR) that includes a detection device (E). This device can be a mobile device or AR glasses. The detection device can be a camera (e.g., light field, lidar) and / or a microphone or other sensor. Figure 2 also shows a device (V) for the computer-aided calculation of the illumination of an object (O) within the AR system. This device includes or is coupled to a processing unit (R) with a CPU, which displays an augmented reality with audiological and / or visual sensory impressions of the object (at least one) on an output unit. egThe object is displayed on a smartphone, tablet, or AR glasses screen and shown to a user. The object—in this example, a pictured teapot—is located within a defined environment. This environment could be a structure, a finished building, a ship, an aircraft, or a car. The detection device can detect the object within a first area of ​​the defined environment. This first area could be the interior of the defined environment, for example, a building. There is also a second area of ​​the defined environment, which could be the exterior of the building. The following example focuses on a building with both an interior and exterior, without further restrictions. A boundary between the first and second areas, or vice versa, could be a wall or a type of fence. Various configurations are possible. There are also areas that are permeable to light or sound, for example.Windows, shafts, pipe systems between the second and the first surrounding area, which may be located in the boundary or wall.

[0034] Buildings can be represented as 3D (meta)models, and the model data can be saved in files for this purpose.

[0035] The most well-known digital building models are the so-called BIM models (BIM stands for Building Information Modeling). The international organization buildingSMART aims to establish open standards (openBIM) for information exchange and communication based on Building Information Modeling. The Industry Foundation Classes (IFC), or a derivative thereof, has developed and continues to develop a standard format for Building Information Modeling (BIM). One such format is the BIM-IFC format, which is created according to the corresponding Object Windows Library (OWL) specification.

[0036] Such BIM models typically contain a detailed 3D metamodel of the building with different views, along with semantic information that describes the individual building elements, such as walls, ceilings, floors, windows, doors, stairs, or columns, and their relationships to one another. This semantic information or data can be prepared, for example, as a knowledge graph, particularly in the format mentioned above.

[0037] The 3D metamodel with semantic information can be represented as a complete or partial knowledge graph. The knowledge graph comprises at least one branch of those branches forming the knowledge graph – created by connecting contained nodes – and is stored together with geometric relationships derived from the 3D metamodel. The knowledge graph is pre-generated and, if necessary, stored based on a prepared, digitally based representation of the surrounding areas and / or the light- or sound-transmitting areas.

[0038] Point clouds from scans of existing buildings, which can be broken down into tiles, are often managed in this way. This extends to the creation of so-called digital twins of buildings.

[0039] Another trend is the increasing centralization of building data, e.g. in a cloud platform, so that multiple users can access the data simultaneously.

[0040] The representation of a building in a digital building model typically reflects a planned state of the building. The building should then be constructed in such a way that its building elements correspond as closely as possible to their representation in the building model.

[0041] Using such a BIM model, the contribution of weather-related brightness and / or noise from noise sources in the outdoor area to a user-specified and / or simulated time of day and year, which penetrates into the interior through one or more light / sound-transmitting areas, can first be calculated for the lighting of the object.

[0042] The 3D metamodel (BIM and / or point cloud) takes a meta-perspective on the aforementioned areas outside of the initial environment detectable by the scanning device. This means that the actual building model with its exterior is not displayed in the AR system, as the AR system shows the actual environment—in this example, the interior—into which the virtual object is then placed.

[0043] The contribution of sunlight entering from the exterior to the interior influences the illumination of the object. For example, using well-known software like Autodesk Revit (https: / / www.autodesk.de / products / revit / over-view?term=1-YEAR), which can be integrated into the device V, a hypothetical position (or path) of the sun around the building can be calculated, given the building's geographical location and a specific date (or time period). Based on this, light and sound wave guidance can be performed using illumination and sound propagation calculations or simulations. This step is in Figure 2 marked with S1.

[0044] The sun's position, which varies depending on the time of day and year, can not only influence the angle of incidence of light through the translucent areas, but also affect noises, such as sounds from animals outdoors that can be heard at a certain time of day and year and penetrate into the interior through the sound-permeable areas.

[0045] This can also take into account different window materials, or indirect lighting caused by scattering off walls or reflective surfaces. According to step S2 in Figure 2 Weather data can also be taken into account, which can affect brightness through clouds, rain, etc., but can also dampen noise.

[0046] To enable this method to be used with point clouds, preprocessing steps are advisable. These ensure that windows can be clearly identified and correctly factored into the calculation. Windows can also transmit additional sound. To identify the windows, i.e., a light source, the following procedure can be used: The same image section is captured multiple times from different viewpoints. If there are reflections in this image section caused by light sources, these will move along with the direction of the shot. The presence of a light source reflection can be determined using a histogram analysis. However, if only a single image is considered, a difference in brightness cannot usually be clearly attributed to a reflection, but could also result from differences in color or surface texture.Only because the reflection, captured simultaneously from different positions, essentially travels across the surface, can a difference in brightness be interpreted accordingly. In contrast to a reflection, a material-based difference in brightness remains stationary. Once a reflection has been clearly identified, the position (or at least the direction) of the light source can be deduced from the camera position and the object surface. For this purpose, a depth map of the environment (point cloud, 3D metamodel) is created and used, acquired with a suitable sensor, such as a lidar sensor or plenoptic camera. The incident ray from the reflection into the camera is mirrored across the surface normal. The mirrored ray now points from the surface towards the light source, whose distance, however, cannot be determined further.As a rule, it can be assumed that the light source is located far away from the object under consideration, so a physically meaningful distance can initially be chosen. If a reflection is found in multiple objects, the intersection point of the corresponding projections can be determined. This allows the exact position of the light source to be deduced, provided there are not multiple light sources.

[0047] Furthermore, artifacts created by reflections in the window panes can be removed. If these were perceived as real objects, they would block some of the incoming light rays or sound.

[0048] Sound reflections or attenuations can be determined, if necessary, by an audio frequency spectrum analysis, e.g., using Fast Fourier Transform.

[0049] Another embodiment of the invention provides for the identification of objects that affect the lighting or illumination within a building. The absorption or reflection of light or sound by objects located upstream of object O within the light or sound propagation cone through the light- or sound-transmitting area should be taken into account. This absorption / reflection can be caused by clouds, trees outdoors, or even by objects indoors.

[0050] In particular, lamps and reflective surfaces need to be included so that they can be equipped with appropriate materials for the calculation. Detailed simulators can also incorporate the seasonal foliage of trees into the calculation. This information is typically added manually to point clouds (at least the tree species). Alternatively, object recognition methods in point clouds can be used for this task. A basic lighting and sound frequency model is then calculated using this information.

[0051] Especially when direct sunlight dominates the lighting, cloud cover can play an important role. This information can either be obtained from weather servers (usually inaccurate, particularly with light cloud cover) or directly from sensors in / on the building (e.g., outdoor cameras).

[0052] Since these and other influencing factors, such as the foliage of trees in front of windows, cannot be predicted with such precision, the resulting lighting and sound frequency model can be calibrated using light meters and sensitive microphones on the VR system (e.g., from the mobile phone camera). For this purpose, the expected lighting / volume at the AR system (according to the lighting and sound frequency model) is compared with the actually measured level, and the lighting and sound frequency model is adjusted accordingly, as described in step S3. Figure 2 is indicated for the lighting.

[0053] Natural lighting and sound sources allow for the calculation of a highly realistic lighting and sound frequency model, enabling significantly improved object rendering in AR devices compared to the previously mentioned state of the art. However, lighting in buildings (at least in the evenings and during winter months) is often dominated by artificial light. Depending on the quality of the collected data and the available sensors, this can also be incorporated into the lighting model. Detailed BIM models typically record the position and type (including luminous intensity) of all light sources, especially lamps. With limitations, lamps, etc., can also be identified and entered in the point cloud (possibly manually). Determining the current state of the interior lighting, however, remains a challenge.In case of doubt, it can be assumed that all lights are on at a certain measured illuminance or at certain times of day (depending on the season). More precise statements (for spot lighting) can be made when the lighting is controlled via the building management system or another accessible application (e.g., the Comfy app). Then, the activity of individual lights can be integrated into the lighting model. Alternatively, the activity of the lights could also be detected with cameras / IR sensors on the AR system, but for this to work, they would need to be within the system's field of view (e.g., no backlighting).

[0054] If the user or an application places objects within the AR device's field of view, their rendering can be calculated using the currently calculated lighting model. Optionally, the user can then make manual adjustments, such as switching light or sound sources known from the BIM model on or off, or changing the lighting intensity or volume.

[0055] Measures that lead to a subjective improvement in the object's lighting can be used to optimize the lighting using a data-driven learning method. For this purpose, the knowledge graph can be extended with a lighting model using the data-driven learning method, with the user providing feedback F regarding their subjective sensory impression of the calculated lighting for object O to the learning method. The noise level around the model can also be improved using a learning method analogous to that used for lighting.

[0056] The results of the learning process can then be transferred to other nearby objects in a user-specific manner (if necessary, the calibration can also be exchanged with other users if it concerns user-unspecific adjustments to the lighting - e.g., reduction of brightness due to deciduous trees in front of the window - which were not previously included in the model).

[0057] Additionally, the method can be applied to "sound rendering". Obstacles originating from a 3D meta-model (BIM model or point cloud) can be included in the representation of sound / noise sources, and sound waves can be reflected or attenuated by these obstacles (e.g., a sound source is located behind an obstacle and is initially displayed quietly, then at normal volume when moving around the obstacle).

[0058] Although the invention has been illustrated and described in detail by the preferred embodiment, the invention is not limited by the disclosed examples and other variations can be derived by the person skilled in the art without leaving the scope of protection of the invention.

[0059] The implementation of the processes or procedures / steps described above can be carried out using instructions stored on computer-readable storage media or in volatile computer memory (hereinafter collectively referred to as computer-readable memory). Examples of computer-readable memory include volatile memory such as caches, buffers, or RAM, as well as non-volatile memory such as removable media, hard drives, etc.

[0060] The functions or steps described above can be represented in the form of at least one instruction set in / on computer-readable memory. These functions or steps are not bound to a specific instruction set, a specific form of instruction sets, a specific storage medium, a specific processor, or specific execution schemes, and can be executed by software, firmware, microcode, hardware, processors, integrated circuits, etc., either independently or in any combination. Various processing strategies can be employed, such as serial processing by a single processor, multiprocessing, multitasking, or parallel processing, etc.

[0061] The instructions can be stored in local memory, but it is also possible to store the instructions on a remote system and access them via a network.

[0062] In the context of the invention, "computer-aided" can, for example, be understood to mean an implementation of the method in which, in particular, a processor, which may be part of the control / computing device or unit, performs at least one process step of the method.

[0063] The terms "processor," "central signal processing," "control unit," or "data processing device," as used herein, encompass processing devices in the broadest sense, including, for example, servers, general-purpose processors, graphics processors, digital signal processors, application-specific integrated circuits (ASICs), programmable logic circuits such as FPGAs, discrete analog or digital circuits, and any combination thereof, including all other processing devices known to those skilled in the art or which may be developed in the future. Processors may consist of one or more devices, units, or components. If a processor consists of several devices, these may be designed or configured for parallel or sequential processing or execution of instructions. In the context of the invention, a "memory unit" may, for example, refer to a memory in the form of main memory (RAM).Random-Access Memory (RAM) or a hard drive.

Claims

1. Apparatus (V) for computer-aided calculation of a light and sound wave guidance in an augmented reality system (AR) with at least one object (O), comprising a computing unit (R), which represents an augmented reality with the at least one object and also sensory impressions of the at least one object on an output unit (D) of the augmented reality system for a user, wherein the computing unit is coupled to a capture device (E) for capturing a first environment region in which the at least one object is represented, - wherein the sensory impressions, which are visually and audiologically distinctive, are supplemented by the calculation of the light and sound wave guidance in a delimited environment by the apparatus, - wherein the light and sound wave guidance is calculated with the aid of a predefinable and / or simulable 3D meta-model of the delimited environment, said meta-model comprising a second environment region with objects arranged therein, the first environment region with the at least one depicted object, and one or more identifiable light- and sound-transmissive regions between the second and first environment regions, wherein the first environment region comprises an inner region of such a delimited environment and the second environment region comprises an outer region of the delimited environment, - wherein for the calculation of the light and sound wave guidance, there are included light sources in the second environment region, a weather-related brightness in the second environment region at a predefinable and / or simulated time of day and season and noises from noise sources in the second environment region at a predefinable and / or simulated time of day and season, the angle of incidence of light and / or sound through the light- and sound-transmissive region(s) onto the at least one object, and also light intensity from further light sources and noise intensity from further noise sources in the first environment region, wherein account is taken of weather data which influence the weather-related brightness and attenuate noises from noise sources in the second environment region, wherein the 3D meta-model is represented as a complete or partial knowledge graph which comprises at least one branch of those branches forming the knowledge graph - and formed by connection of contained nodes - and is stored together with geometric relationships derived from the 3D meta-model, wherein the knowledge graph is formed and, if appropriate, stored in advance on the basis of a prepared representation of the environment regions and / or of the light- and / or sound-transmissive regions that is based on digital data, wherein the knowledge graph can be extended with an illumination model by means of a data-based learning method, wherein the user returns a feedback (F) with regard to their subjective sensory impression of the calculated light guidance for the at least one object to the learning method.

2. Apparatus according to the preceding claim, characterized in that the time of day- and season-dependent position of the sun influences the angle of incidence of light through the light-transmissive region(s).

3. Apparatus according to either of the preceding claims, characterized in that the 3D meta-model adopts a meta-perspective on the stated regions outside a first environment region that is capturable by the capture device.

4. Apparatus according to any of the preceding claims, characterized in that the brightness and / or noises from noise sources in the first environment region are captured by the capture device.

5. Apparatus according to any of the preceding claims, characterized in that in the calculation of the light and sound wave guidance with respect to the at least one object, an absorption or a reflection of light and / or sound by upstream objects in the light and / or sound propagation cone through the light- and sound-transmissive region is taken into account.

6. Apparatus according to any of the preceding claims, characterized in that the 3D meta-model models a building in an environment, wherein the first environment region represents the inner region of the building, the second environment region represents the outer region of the building and the light- and sound-transmissive regions in the delimitation represent windows in the wall of the building.

7. Apparatus according to any of the preceding claims, characterized in that the 3D meta-model is represented by a building information modelling model, abbreviated to BIM.

8. Apparatus according to any of the preceding claims, characterized in that the 3D meta-model is represented by a point cloud.

9. Method for computer-aided calculation of a light and sound wave guidance in an augmented reality system (AR) with at least one object (O), wherein an apparatus for the computer-aided calculation comprises a computing unit (R), which represents an augmented reality with the at least one object and also sensory impressions of the at least one object on an output unit (D) of the augmented reality system for a user, wherein the computing unit is coupled to a capture device (E) for capturing a first environment region in which the at least one object is represented, - wherein the sensory impressions, which are visually and audiologically distinctive, are supplemented by the calculation of the light and sound wave guidance in a delimited environment by the apparatus, - wherein the light and sound wave guidance is calculated with the aid of a predefinable and / or simulable 3D meta-model of the delimited environment, said meta-model comprising a second environment region with objects arranged therein, the first environment region with the at least one depicted object, and one or more identifiable light- and sound-transmissive regions between the second and first environment regions, wherein the first environment region comprises an inner region of such a delimited environment and the second environment region comprises an outer region of the delimited environment, - wherein for the calculation of the light and sound wave guidance, there are included light sources in the second environment region, a weather-related brightness in the second environment region at a predefinable and / or simulated time of day and season and noises from noise sources in the second environment region at a predefinable and / or simulated time of day and season, the angle of incidence of light and / or sound through the light- and / or sound-transmissive region(s) onto the at least one object, and also light intensity from further light sources and noise intensity from further noise sources in the first environment region, wherein account is taken of weather data which influence the weather-related brightness and attenuate noises from noise sources in the second environment region, wherein the 3D meta-model is represented as a complete or partial knowledge graph which comprises at least one branch of those branches forming the knowledge graph - and formed by connection of contained nodes - and is stored together with geometric relationships derived from the 3D meta-model, wherein the knowledge graph is formed and, if appropriate, stored in advance on the basis of a prepared representation of the environment regions and / or of the light- and / or sound-transmissive regions that is based on digital data, wherein the knowledge graph can be extended with an illumination model by means of a data-based learning method, wherein the user returns a feedback (F) with regard to their subjective sensory impression of the calculated light guidance for the at least one object to the learning method.

10. Computer program product, comprising instructions which, when the computer program is executed by a computer, cause the latter to execute the method according to any of the preceding method claims.

11. Computer-readable storage or data transmission medium, comprising instructions which, when executed by a computer, cause the latter to execute the method according to any of the preceding claims.