The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects of the invention are apparent from and will be further elucidated, by way of example, with reference to the drawings, in which:

FIG. 1 is a block diagram of an embodiment of the system;

FIG. 2 is a flow diagram of a first embodiment of the method;

FIG. 3 highlights a repeating section in an example of a visual representation of a luminaire shown at a first moment;

FIG. 4 highlights the light source in the visual representation of FIG. 3;

FIG. 5 is a second example of a visual representation of the luminaire of FIG. 3, now shown at a second moment after a change in camera location and orientation;

FIG. 6 is a flow diagram of a second embodiment of the method;

FIG. 7 is a flow diagram of a third embodiment of the method;

FIG. 8 is a flow diagram of a fourth embodiment of the method;

FIG. 9 is a flow diagram of a fifth embodiment of the method;

FIG. 10 is a flow diagram of a sixth embodiment of the method; and

FIG. 11 is a block diagram of an exemplary data processing system for performing the method of the invention.

Corresponding elements in the drawings are denoted by the same reference numeral.

DETAILED DESCRIPTION OF THE EMBODIMENTS

FIG. 1 shows an embodiment of the system for displaying a visual representation of a luminaire, e.g., of a luminaire to be manufactured using an additive manufacturing process. The visual representation includes a representation of a light effect generated by one or more activated light sources in or on the luminaire. In this first embodiment, the system is a computer 1. The computer 1 is connected to the Internet 11. A display device 15 is connected to the computer 1. The computer 1 may be a desktop computer or laptop computer, for example. Alternatively, the system may be a tablet or mobile phone, for example.

The computer 1 comprises a receiver 3, a transmitter 4, a processor 5, a display interface 6, and storage means 7. The processor 5 is configured to obtain a three-dimensional model of the luminaire and one or more texture maps associated with the three-dimensional model. The one or more light sources and the luminaire are rotatably symmetric with respect to a central axis of the luminaire and the surface of the luminaire comprises a plurality of repeating sections.

The processor 5 is further configured to determine a camera location and orientation based on user input, determine observation angles on each of a plurality of surface positions of the three-dimensional model based on the camera location and orientation, and determine, for each of the plurality of surface positions, an applicable light value for a respective surface position based on the observation angle determined for the surface position and a light value predetermined either for the surface position or for a corresponding surface position of a different section of the luminaire. At least some of the applicable light values are determined based on light values predetermined for corresponding surface positions of a different section of the luminaire.

Determining the observation angles on each of the plurality of surface positions may comprise selecting a surface position, determining the surface orientation for this surface position, and determining the observation angle for this surface position relative to the surface orientation. In this case, the observation angles are relative to the surface orientation and the surface position. Alternatively, the observation angles may be relative to the 3D model's local coordinate system. The observation angles may be determined for each surface position of a repeating section, for example.

The processor 5 is further configured to render the visual representation of the luminaire based on the three-dimensional model, the one or more texture maps, the applicable light values, and the camera location and orientation, and display the visual representation on the display device 15 via the display interface 6. The user input may be received via a keyboard 16, a microphone (not shown) or via display device 15 if it has a touchscreen, for example.

The three-dimensional model may be obtained from an Internet server 13, for example. The Internet server 13 is also connected to the Internet 11. In the embodiment of FIG. 1, the rendering is executed by the processor 5, e.g., a CPU. In an alternative embodiment, the rendering is at least part executed by a GPU. In the embodiment of FIG. 1, the computer 1 is a local computer located near the display device 15. In an alternative embodiment, the computer 1 is a cloud computer which displays the visual representation via a local device, e.g., via a local computer, which is connected to the display device or comprises a display itself.

In the embodiment of the computer 1 shown in FIG. 1, the computer 1 comprises one processor 5. In an alternative embodiment, the computer 1 comprises multiple processors. The processor 5 of the computer 1 may be a general-purpose processor, e.g., from Intel or AMD, or an application-specific processor. The processor 5 of the computer 1 may run a Windows or Unix-based operating system for example. The storage means 7 may comprise one or more memory units. The storage means 7 may comprise one or more hard disks and/or solid-state memory, for example. The storage means 7 may be used to store an operating system, applications and application data, for example.

The receiver 3 and the transmitter 4 may use one or more wired and/or wireless communication technologies such as Ethernet and/or Wi-Fi (IEEE 802.11) to connect to the Internet 11, for example. In an alternative embodiment, multiple receivers and/or multiple transmitters are used instead of a single receiver and a single transmitter. In the embodiment shown in FIG. 1, a separate receiver and a separate transmitter are used. In an alternative embodiment, the receiver 3 and the transmitter 4 are combined into a transceiver. The computer 1 may comprise other components typical for a computer such as a power connector. The invention may be implemented using a computer program running on one or more processors.

A first embodiment of displaying a visual representation of a luminaire is shown in FIG. 2. The visual representation includes a representation of a light effect generated by one or more activated light sources in or on the luminaire. The method may be performed by the computer 1 of FIG. 1, for example.

A step 101 comprises obtaining a three-dimensional model of a luminaire and one or more texture maps associated with the three-dimensional model. The three-dimensional model may be a three-dimensional mesh model or a boundary representation, for example. The one or more light sources and the luminaire are rotatably symmetric with respect to a central axis of the luminaire and the surface of the luminaire comprises a plurality of repeating sections. FIGS. 3 and 4 show an example of a visual representation of a luminaire 31 from a first camera location and a first camera orientation at time t1. In FIG. 3, the repeating section 33 has been highlighted. In FIG. 4, the light source 35 has been highlighted.

A step 103 comprises determining a camera location and orientation based on user input. Next, in the first iteration of a step 104, a first surface position is selected from a plurality of surface positions of the three-dimensional model, which has been obtained in step 101. A step 105 comprises determining an observation angle on the surface position selected in step 104 based on the camera location and orientation determined in step 103. Determining the observation angle may comprise determining the surface orientation for the surface position selected in step 104 and determining the observation angle for this surface position relative to the surface orientation. The observation angle on a certain surface position typically depends on both the determined camera location and orientation and on the orientation of the luminaire. The user may or may not be able to change the orientation of the represented luminaire, e.g., rotate the represented luminaire.

A step 107 comprises determining an applicable light value for the surface position selected in step 104 based on the observation angle determined for this surface position in step 105 and a light value predetermined either for this surface position or for a corresponding surface position of a different section of the luminaire.

In a step 108, it is determined whether at least one of the surface positions has not been selected yet in step 104. If so, step 104 is repeated, and a next surface position is selected. As a result, observation angles are determined on each of the plurality of surface positions and step 107 is performed for each of the plurality of surface positions for which an observation angle was determined in step 105. At least some of the applicable light values determined in step 107 are determined based on light values predetermined for corresponding surface positions of a different section of the luminaire.

A step 109 comprises rendering the visual representation of the luminaire based on the three-dimensional model obtained in step 101, the one or more texture maps obtained in step 101, the applicable light values determined in step 107, and the camera location and orientation determined in step 103 (and optionally, the rotation of the luminaire). The one or more texture maps may include a logo to be applied to the luminaire and/or print relief details and/or modulation patterns. These print relief details and/or modulation patterns may be determined from a print track model, for example. A step 111 comprises displaying the visual representation rendered in step 109.

A second embodiment of displaying a visual representation of a luminaire is shown in FIG. 6. This second embodiment is an extension of the first embodiment of FIG. 2. In the embodiment of FIG. 6, steps 131, 133, 135, 137, and 139 are performed between steps 101 and 103 of FIG. 2 and step 103 is repeated after step 111.

In steps 131-139, the predetermined light values used in step 107 are pre-rendered by rendering a light value for each of a plurality of observation angles for each surface position in the three-dimensional model of at least one section of the luminaire. In the first iteration of step 131, a first surface position of one of the repeating sections of the three-dimensional model obtained in step 101 is selected. Next, in the first iteration of step 133, a first observation angle of the observation angles is selected.

The observation angle may be expressed as a single three-dimensional vector or as a combination of a horizontal angle and a vertical angle, for example. The observation angles may be relative to the surface position and relative to a surface orientation at this surface position, for example. When the material of the luminaire is opaque, the observation angle may be selected from fewer observation angles than when the material of the luminaire is semi-transparent. At this stage, the observation angles are independent of any orientation of the luminaire or of any camera location and orientation. Step 135 comprises rendering a light value for the observation angle last determined in step 133 for the surface position last selected in step 131.

Step 135 may comprise obtaining a local luminance distribution over observation angles for positions on the surface using a customizable high-end rendering pipeline. Since step 135 is the computationally intensive step, it has been included in the pre-rendering stage, i.e., it is executed ‘off-line’. This makes it possible to use all required resources and be physically accurate with raytracing and material models in order to obtain a high-quality dataset to start with.

The local luminance distribution obtained for a certain observation angle at a certain surface position preferably depends on the surface orientation at this surface position. This make it possible, for example, to determine the lambertion distribution and thereby realistically render the light effect. The local luminance distribution may be determined per light source and then combined. The following three factors may be taken into account to determine the local luminance distribution:

- Light position and its emission properties (e.g., a homogenous distribution for a point source);
- Surface position and orientation and is reflection/diffraction properties;
- Camera and its intrinsic and extrinsic values (the latter including the observation angle).

In step 137, it is determined whether there is at least one observation angle which has not been selected yet for the surface position last selected in step 131. If so, step 133 is repeated, and a next observation angle is selected. Otherwise, a step 139 is performed. In step 139, it is determined whether there is at least one surface position of the repeating section which has not been selected yet in step 133. If so, step 131 is repeated, and a next surface position of the repeating section is selected, after which the first observation angle is selected for this next surface position in step 133. Otherwise, step 103 is performed.

In the embodiment of FIG. 6, light values are rendered for one of the repeating sections of the luminaire. Since the one or more light sources and the luminaire are rotatably symmetric with respect to a central axis of the luminaire and the surface of the luminaire comprises a plurality of repeating sections, these light values can then be used for all repeating sections of the luminaire in step 107.

Step 135 may comprise storing the predetermined light values in angle-dependent light maps. In that case, step 107 comprises determining the applicable light values based on the angle-dependent light maps stored in step 135. As previously discussed, the surface of the luminaire can appear quite differently depending on the camera location and orientation. This light effect may be approximated with an (observation) angle dependent light map, which may be used in combination with the applicable observation angle to obtain the correct luminance or color. As a result, the applicable light values representing luminance or color on the surface of the object at a certain location will change when the camera location and/or orientation changes (or the orientation of the luminaire changes), because the applicable observation angles change as well.

If light values would be stored for each surface position of the three-dimensional model and the light maps would need to store values for many observation angles for every location on the surface, this would be quite data intensive. A map storing the luminance or color for 2048×2048 locations and 16 horizontal and 16 vertical angles would require storage of over 1 million values. Resolution could be reduced, and interpolation could be used, to create intermediate values, but the given example is already at the lower end of the resolution required for a realistic rendering.

However, since many luminaires are rotatably symmetric with respect to a central axis, have one or more light sources which are rotatably symmetric with respect to the central axis of the luminaire, and have a surface which comprises a plurality of repeating sections, it is not necessary to store unique light map values for every position on the surface, but only for a single repeating section, e.g., a vertical slice of the cylindrical structure. These values can then be re-used for the other sections, e.g., by having the correct UV parameterization of the surface in which coordinates repeat for the repeating sections of the surface.

Alternatively, step 135 may comprise training a machine learning model based on the predetermined light values. In that case, step 107 may comprise determining the applicable light values via the machine learning model trained in step 135. For example, instead of using light maps to reduce the data required to render an applicable light value, e.g., a color or luminance value, for a certain surface position from a certain observation angle, a function that will map these input parameters to the desired light value may be used. This is also referred to as a “compressed light map” in this description.

This machine learning model may be in the form a neural network or a non-linear regression model. A neural network may be created that has as inputs the position (UV coordinate on the model surface) and observation angle(s) (e.g., horizontal and vertical angles of observation of the surface point) and as output the light value (which could be greyscale or some color space such as RGB or XYZ). Using the reference local luminance distributions, the neural network may be trained to model the desired function that will achieve the mapping. The number of weights, or nodes, required in the network to obtain a plausible result may be adjusted accordingly and the size of data required for storing these weights will be considerably smaller than the size of data required for storing the full map (i.e., for all surface positions of the 3D model).

If a machine learning model is trained in step 135, it may be trained for a single repeating section and a surface position anywhere on the luminaire may then be mapped to a surface position on the single repeating section in step 107, or it may be trained for all repeating sections of the luminaire. In the latter case, as a result of the training, the machine learning model will learn what the repeating sections are, such that no redundant data is stored.

Optionally, the method may comprise an additional step of determining a material for printing the luminaire and step 135 may comprise pre-rendering the predetermined light values in dependence on this material. Optionally, the method may comprise an additional step of determining one or more positions of the one or more light sources, e.g., if there are multiple light sources or if there is a single light source which is not located in the center of the central axis, and step 135 may comprise pre-rendering the predetermined light values in dependence on these one or more positions.

Steps 103 to 111 are performed after step 139 as described in relation to FIG. 2. However, step 103 is repeated after step 111 has been performed. In the next iteration of step 103, a further camera location and orientation is determined based on further user input. For example, FIG. 5 shows a visual representation of the luminaire 31 of FIGS. 3 and 4 from a second camera location and a second camera orientation at time t2.

In the next iterations of steps 105 and 107, further observation angles are determined on each of the plurality of surface positions of the three-dimensional model based on the further camera location and orientation and a further applicable light value is determined for each of the plurality of surface positions based on the further observation angle determined for the surface position and a light value predetermined either for the surface position or for a corresponding surface position of a different section of the luminaire. At least some of the further applicable light values are determined based on light values predetermined for corresponding surface positions of a different section of the luminaire.

In the next iteration of step 109, a further visual representation of the luminaire is rendered based on the three-dimensional model, the one or more texture maps, the further applicable light values, and the further camera location and orientation. In the next iteration of step