Patent Description:
Depth maps can be generated in various ways. One example technique for generating a depth map includes structured light depth imaging. One form of structured light depth imaging includes projecting a series of different light patterns (e.g., striped patterns with different numbers and/or widths of stripes) into an environment and utilizing a camera to capture a series of images of the environment. Each image captures the environment while the environment is illuminated with a different light pattern.

While capturing the images, the camera is typically kept stationary so that each image sensing pixel of the camera captures the same portion of the environment throughout the projecting and capturing of the different light patterns.

The light patterns of the series of different light patterns are selected to allow pixel signatures to be determined for each image sensing pixels of the camera. For example, the series of different light patterns may include arrangements of vertical stripes formed from illuminated vertical sections and unilluminated vertical sections arranged in an alternating pattern. The different light patterns may include different densities of vertical stripes. For instance, a first light pattern may include a single illuminated vertical section (occupying half of the pattern) and a single unilluminated vertical section (occupying the other half of the pattern). A second light pattern may include four vertical stripes (two illuminated, two unilluminated, arranged in an alternating pattern), a third light pattern may include eight vertical stripes (four illuminated, four unilluminated, arranged in an alternating pattern), and so forth.

According to the above example, a pixel signature for a particular image sensing pixel may be defined by tracking whether the portion of the environment captured by the particular image sensing pixel was illuminated during projection of each of the different light patterns into the environment. For instance, a first value may be recorded indicating whether the particular image sensing pixel detected light pattern illumination while the first light pattern was projected into the environment (e.g., a binary "<NUM>" or "<NUM>", with a "<NUM>" indicating that illumination was detected), a second value may be recorded indicating whether the particular image sensing pixel detected light pattern illumination while the second light pattern was projected into the environment, a third value may be recorded indicating whether the particular image sensing pixel detected light pattern illumination while the third light pattern was projected into the environment, and so forth. Stated differently, the first value may indicate whether the portion of the environment captured by the particular image sensing pixel was within an illuminated stripe of the first pattern, the second value may indicate whether the portion of the environment captured by the particular image sensing pixel was within an illuminated stripe of the second pattern, the third value may indicate whether the portion of the environment captured by the particular image sensing pixel was within an illuminated stripe of the third pattern, and so forth. The various values for the particular image sensing pixel (e.g., indicating light pattern illumination or non-illumination during projection of the series of different light patterns) may be combined (e.g., arranged as a sequence of values) to generate the pixel signature for the particular image sensing pixel.

Pixels signatures as discussed above may be determined for the image sensing pixel of the camera based on images captured of the various structured light patterns projected into the environment. A system may also determine virtual pixel signatures based on the structured light patterns projected into the environment. For example, the virtual pixel signatures may each be associated with pixel coordinates and may be based on whether the pixel coordinates correspond to an illuminated portion or an unilluminated portion across multiple patterns.

Accordingly, to perform depth computations, a system may search along scanlines (e.g., horizontal scanlines, or a scanning direction orthogonal to the stripes of the structured light patterns) to identify the locations of camera pixels associated with pixel signatures that match a virtual pixel signature on the same scanline. The system may use pixel coordinates associated with matched pixel signatures and virtual pixel signatures to determine disparity and/or depth values. Such matching may be performed or attempted to calculate depth values for all camera pixels, thereby forming a depth map of the captured environment. To facilitate ideal structured light depth imaging as discussed above, the light patterns of the series of structured light patterns should be selected to allow pixel signatures for each image sensing pixel of the camera to be unique from other pixel signatures at least along the same scanline (e.g., along the same horizontal scanline).

In some instances, structured light imaging as described in the above example may provide high-precision depth information for a captured environment with reduced error compared to other conventional techniques for depth imaging (e.g., using a single dot pattern projection to facilitate active stereo imaging). However, environments that include moving objects present many challenges for structured light imaging utilizing a series of light patterns as discussed above. For example, structured light images are typically captured using complementary metal-oxide-semiconductor (CMOS) and/or charge-coupled device (CCD) image sensors. Such sensors may include image sensing pixel arrays where each pixel is configured to generate electron-hole pairs in response to detected photons. The electrons may become stored in per-pixel capacitors, and the charge stored in the capacitors may be read out to provide image data (e.g., by converting the stored charge to a voltage).

CMOS and/or CCD image sensors typically operate by performing an exposure operation to allow charge to collect in the per-pixel capacitors and subsequently performing a readout operation to generate image data based on the collected per-pixel charge. Thus, moving objects in a captured environment often occupy one position (or one set of positions) during exposure and/or readout of a first light pattern image and occupy a different position (or different set of positions) during exposure and/or readout of a second light pattern image. Thus, different light pattern images may include spatially misaligned representations of the same objects in the environment, which can cause errors in depth computations.

Thus, for at least the foregoing reasons, there is an ongoing need and desire for improved systems and methods for facilitating structured light depth computations.

<CIT> describes systems and methods for machine vision. Such machine vision includes ego-motion, as well as the segmentation and/or classification of image data of one or more targets of interest. The projection and detection of scanning light beams that generate a pattern are employed. Real-time continuous and accurate spatial-temporal 3D sensing is achieved. The relative motion between an observer and a projection surface is determined. A combination of visible and non-visible patterns, as well as a combination of visible and non-visible sensor arrays is employed to sense 3D coordinates of target features, as well as acquire color image data to generate 3D color images of targets. Stereoscopic pairs of cameras are employed to generate 3D image data. Such cameras are dynamically aligned and calibrated. Information may be encoded in the transmitted patterns. The information is decoded upon detection of the pattern and employed to determine features of the reflecting surface. <CIT> describes aspects which relate to systems and methods for structured light (SL) depth systems. A depth finding system includes one or more processors and a memory, coupled to the one or more processors, includes instructions that, when executed by the one or more processors, cause the system to capture a plurality of frames based on transmitted pulses of light, where each of the frames is captured by scanning a sensor array after a respective one of the pulses has been transmitted, and generate an image depicting reflections of the transmitted light by combining the plurality of frames, where each of the frames provides a different portion of the image. <NPL>, describes that coded structured light is considered one of the most reliable techniques for recovering the surface of objects. This technique is based on projecting a light pattern and viewing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be easily found. The decoded points can be triangulated and 3D information is obtained. Presented is an overview of the existing techniques, as well as a new and definitive classification of patterns for structured light sensors. Implemented is a set of representative techniques in this field and present some comparative results. The advantages and constraints of the different patterns are also discussed. <NPL>, provides a review of recent advances in 3D surface imaging technologies, particularly on noncontact 3D surface measurement techniques based on structured illumination. The high-speed and high-resolution pattern projection capability offered by the digital light projection technology, together with the recent advances in imaging sensor technologies, may enable new generation systems for 3D surface measurement applications that will provide much better functionality and performance than existing ones in terms of speed, accuracy, resolution, modularization, and ease of use. Performance indexes of 3D imaging system are discussed, and various 3D surface imaging schemes are categorized, illustrated, and compared. Calibration techniques are also discussed since they play critical roles in achieving the required precision. Numerous applications of 3D surface imaging technologies are discussed with several examples.

Disclosed examples include systems, methods, and devices for facilitating structured light depth computation using single photon avalanche diodes (SPADs).

According to the invention, there is provided a system that includes inter alia a SPAD array comprising a plurality of SPAD pixels, an illuminator configured to emit one or more structured light patterns, one or more processors, and one or more hardware storage devices storing instructions that are executable by the one or more processors to configure the system to perform various acts. The acts include, over a frame capture time period, selectively activating the illuminator to perform interleaved structured light illumination operations. The interleaved structured light illumination operations include alternately emitting at least a first structured light pattern from the illuminator and emitting at least a second structured light pattern from the illuminator. The acts also include, over the frame capture time period, performing a plurality of sequential shutter operations to configure each SPAD pixel of the SPAD array to enable photon detection. The plurality of sequential shutter operations generates, for each SPAD pixel of the SPAD array, a plurality of binary counts indicating whether a photon was detected during each of the plurality of sequential shutter operations.

This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter, since the scope of the invention is defined by the appended claims.

Disclosed embodiments are generally directed to systems, methods, and devices for facilitating structured light depth computation using single photon avalanche diodes (SPADs).

Those skilled in the art will recognize, in view of the present disclosure, that at least some of the disclosed embodiments may be implemented to address various shortcomings associated with at least some conventional structured light depth computation techniques. The following section outlines some example improvements and/or practical applications provided by the disclosed embodiments. It will be appreciated, however, that the following are examples only and that the embodiments described herein are in no way limited to the example improvements discussed herein.

In contrast with conventional CMOS or CCD sensors, a SPAD is operated at a bias voltage that enables the SPAD to detect a single photon. Upon detecting a single photon, an electron-hole pair is formed, and the electron is accelerated across a high electric field, causing avalanche multiplication (e.g., generating additional electron-hole pairs). Thus, each detected photon may trigger an avalanche event. A SPAD may operate in a gated manner (each gate corresponding to a separate shutter operation), where each gated shutter operation may be configured to result in a binary output. The binary output may comprise a "<NUM>" where an avalanche event was detected during an exposure (e.g., where a photon was detected), or a "<NUM>" where no avalanche event was detected.

Separate shutter operations may be integrated over a frame capture time period. The binary output of the shutter operations over a frame capture time period may be counted, and an intensity value may be calculated based on the counted binary output.

An array of SPADs may form an image sensor, with each SPAD forming a separate pixel in the SPAD array. To capture an image of an environment, each SPAD pixel may detect avalanche events and provide binary output for consecutive shutter operations in the manner described herein. The per-pixel binary output of multiple shutter operations over a frame capture time period may be counted, and per-pixel intensity values may be calculated based on the counted per-pixel binary output. The per-pixel intensity values may be used to form an intensity image of an environment.

As will be described in more detail hereinafter, techniques of the present disclosure include performing interleaved light pattern exposure operations using SPAD pixels of a SPAD array. During a first light pattern exposure, sequential shutter operations are performed using the SPAD pixels to generate binary counts, with each binary count indicating whether a photon was detected during a shutter operation (e.g., "<NUM>" indicating a photon was detected, "<NUM>" indicating that no photon was detected). The sequential shutter operations of the first light pattern exposure are performed as the captured scene is illuminated according to a first light pattern. During a second light pattern exposure, sequential shutter operations are performed using the SPAD pixels while an illuminator emits a second light pattern into the captured scene. These shutter operations also provide binary counts. The different light pattern exposures and corresponding light pattern illuminations may be performed in an interleaved manner (e.g., first light pattern illumination and exposure, second light pattern illumination and exposure, first light pattern illumination and exposure, and so forth). Additional light pattern exposures under illumination according to additional light patterns may also be performed and interleaved (e.g., third light pattern illumination and exposure, fourth light pattern illumination and exposure, nth light pattern illumination and exposure).

The interleaved light pattern exposures are alternately performed (e.g., one after the other) over a frame capture time period, providing multiple subsets of binary counts. For example, a first subset of binary counts may be associated with the first light pattern exposure, a second temporally subsequent subset of binary counts may be associated with a second light pattern exposure, a third temporally subsequent subset of binary counts may be associated with first light pattern exposure, a fourth temporally subsequent subset of binary counts may be associated with second light pattern exposure, a fifth temporally subsequent subset of binary counts may be associated with first light pattern exposure, and so forth. As noted above, additional subsets of binary counts may correspond to additional light pattern illuminations and exposures and may be interleaved with the above.

Accordingly, subsets of binary counts associated with the same light pattern exposures (e.g., different subsets of binary counts associated with a first light pattern exposure) can be generated not temporally contiguous to one another. Furthermore, a subset of binary counts associated with one light pattern exposure (e.g., a second light pattern exposure) may temporally intervene between two subsets of binary counts associated with another light pattern exposure (e.g., a first light pattern exposure), and vice versa.

A system may then use all of the subsets of binary counts associated with each particular light pattern exposure (e.g., the first light pattern exposure, the second light pattern exposure, etc.) to generate a respective light pattern image for the particular light pattern exposure, even where the subsets of binary counts associated with the particular light pattern exposure are temporally noncontiguous. The different respective light pattern images may be used to generate pixel signatures for computing depth information.

The use of SPAD image sensors to capture light pattern images as described herein may provide a number of advantages over conventional systems and techniques for capturing light pattern images (e.g., for structured light depth computations). As noted above, conventional techniques for capturing light pattern images include utilizing CMOS or CCD sensors to fully expose and read out a first light pattern image before proceeding to fully expose and read out a subsequent light pattern image, which may give rise to motion artifacts and/or spatial misalignment between the different light pattern images. In contrast, by interleaving different light pattern exposures according to the present disclosure, the motion in the captured scene (and/or motion of the image sensor(s)) will affect all light pattern images in a similar manner, thereby mitigating motion artifacts and/or spatial misalignment between the light pattern images. Accordingly, the accuracy and/or usability of structured light depth imaging may be improved.

Having just described some of the various high-level features and benefits of the disclosed embodiments, attention will now be directed to <FIG>. These Figures illustrate various conceptual representations, architectures, methods, and supporting illustrations related to the disclosed embodiments.

<FIG> illustrates various example components of a system <NUM> that may be used to implement one or more disclosed embodiments. For example, <FIG> illustrates that a system <NUM> may include processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>, input/output system(s) <NUM> (I/O system(s) <NUM>), and communication system(s) <NUM>. Although <FIG> illustrates a system <NUM> as including particular components, one will appreciate, in view of the present disclosure, that a system <NUM> may comprise any number of additional or alternative components.

The processor(s) <NUM> may comprise one or more sets of electronic circuitry that include any number of logic units, registers, and/or control units to facilitate the execution of computer-readable instructions (e.g., instructions that form a computer program). Such computer-readable instructions may be stored within storage <NUM>. The storage <NUM> may comprise physical system memory and may be volatile, non-volatile, or some combination thereof. Furthermore, storage <NUM> may comprise local storage, remote storage (e.g., accessible via communication system(s) <NUM> or otherwise), or some combination thereof. Additional details related to processors (e.g., processor(s) <NUM>) and computer storage media (e.g., storage <NUM>) will be provided hereinafter.

In some implementations, the processor(s) <NUM> may comprise or be configurable to execute any combination of software and/or hardware components that are operable to facilitate processing using machine learning models or other artificial intelligence-based structures/architectures. For example, processor(s) <NUM> may comprise and/or utilize hardware components or computer-executable instructions operable to carry out function blocks and/or processing layers configured in the form of, by way of non-limiting example, single-layer neural networks, feed forward neural networks, radial basis function networks, deep feed-forward networks, recurrent neural networks, long-short term memory (LSTM) networks, gated recurrent units, autoencoder neural networks, variational autoencoders, denoising autoencoders, sparse autoencoders, Markov chains, Hopfield neural networks, Boltzmann machine networks, restricted Boltzmann machine networks, deep belief networks, deep convolutional networks (or convolutional neural networks), deconvolutional neural networks, deep convolutional inverse graphics networks, generative adversarial networks, liquid state machines, extreme learning machines, echo state networks, deep residual networks, Kohonen networks, support vector machines, neural Turing machines, and/or others.

As will be described in more detail, the processor(s) <NUM> may be configured to execute instructions <NUM> stored within storage <NUM> to perform certain actions associated with imaging using SPAD arrays. The actions may rely at least in part on data <NUM> (e.g., avalanche event counting or tracking, etc.) stored on storage <NUM> in a volatile or non-volatile manner.

In some instances, the actions may rely at least in part on communication system(s) <NUM> for receiving data from remote system(s) <NUM>, which may include, for example, separate systems or computing devices, sensors, and/or others. The communications system(s) <NUM> may comprise any combination of software or hardware components that are operable to facilitate communication between on-system components/devices and/or with off-system components/devices. For example, the communications system(s) <NUM> may comprise ports, buses, or other physical connection apparatuses for communicating with other devices/components. Additionally, or alternatively, the communications system(s) <NUM> may comprise systems/components operable to communicate wirelessly with external systems and/or devices through any suitable communication channel(s), such as, by way of non-limiting example, Bluetooth, ultra-wideband, WLAN, infrared communication, and/or others.

<FIG> illustrates that a system <NUM> may comprise or be in communication with sensor(s) <NUM>. Sensor(s) <NUM> may comprise any device for capturing or measuring data representative of perceivable phenomenon. By way of non-limiting example, the sensor(s) <NUM> may comprise one or more image sensors, microphones, thermometers, barometers, magnetometers, accelerometers, gyroscopes, and/or others.

<FIG> also illustrates that the sensor(s) <NUM> may include SPAD array(s) <NUM>. As depicted in <FIG>, a SPAD array <NUM> may comprise an arrangement of SPAD pixels <NUM> that are each configured to facilitate avalanche events in response to sensing a photon, as described hereinabove. SPAD array(s) <NUM> may be implemented on a system <NUM> (e.g., an MR HMD) to facilitate various functions such as image capture and/or computer vision tasks.

Furthermore, <FIG> illustrates that a system <NUM> may comprise or be in communication with I/O system(s) <NUM>. I/O system(s) <NUM> may include any type of input or output device such as, by way of non-limiting example, a touch screen, a mouse, a keyboard, a controller, and/or others, without limitation. For example, the I/O system(s) <NUM> may include a display system that may comprise any number of display panels, optics, laser scanning display assemblies, and/or other components.

<FIG> conceptually represents that the components of the system <NUM> may comprise or utilize various types of devices, such as mobile electronic device 100A (e.g., a smartphone), personal computing device 100B (e.g., a laptop), a mixed-reality head-mounted display 100C (HMD 100C), an aerial vehicle 100D (e.g., a drone), and/or other devices. Although the present description focuses, in at least some respects, on utilizing an HMD to implement techniques of the present disclosure, additional or alternative types of systems may be used.

<FIG> illustrates an example implementations of a single photon avalanche diode (SPAD) sensor in a head-mounted display (HMD). In particular, <FIG> illustrates an example HMD <NUM>, which may correspond in at least some respects to the system <NUM> described hereinabove with reference to <FIG>. In the example shown in <FIG>, the HMD <NUM> includes SPAD sensor <NUM>. The SPAD sensor <NUM> may be configured to capture intensity image frames as described hereinabove (e.g., by counting photons or avalanche events detected over a frame capture time period on a per-pixel basis). Intensity images captured using the SPAD sensor <NUM> may be used for a variety of purposes, such as to facilitate image/video capture, pass-through imaging, depth computations (e.g., structured light depth imaging), object tracking, object segmentation, surface reconstruction, simultaneous localization and mapping (SLAM), and/or others. The HMD <NUM> may implement any number of other camera(s) <NUM> for the same, additional, or alternative purposes.

<FIG> also illustrates the HMD <NUM> as comprising an illuminator <NUM>, which may take the form of any suitable light emitting device. As will be described herein, a system (e.g., an HMD <NUM> or/or other device) may operate an illuminator (e.g., illuminator <NUM>) in conjunction with one or more SPAD sensors (e.g., SPAD sensor <NUM>) to capture images that are usable to facilitate structured light depth computation. For example, a system may selectively (or iteratively) activate the illuminator (e.g., in a pulsed manner) to allow the SPAD sensor(s) 202A-202E to capture images of an environment as the environment is illuminated with different structured light patterns. The system may utilize the illuminator <NUM> as a "virtual camera" in conjunction with the SPAD sensor <NUM> to facilitate structured light depth computations.

In accordance with the present disclosure, the illuminator <NUM> may take on various forms to facilitate various types of illumination for capturing various types of illuminated images. For example, the illuminator <NUM> may be configured to emit visible light, infrared light, ultraviolet light, combinations thereof, and/or light in other spectral ranges. In some instances, as indicated above, the illuminator <NUM> may be configured to emit one or more structured light patterns, such as striped structured light patterns. Although the present disclosure focuses, in at least some respects, emitting striped structured light patterns with an illuminator to facilitate structured light depth computations, one will appreciate, in view of the present disclosure, that additional or alternative types of illumination may be used. For example, grayscale illumination, sinusoidal patterns, random patterns, and/or others may be used.

One will appreciate, in view of the present disclosure, that although <FIG> only illustrates a single illuminator <NUM> on the HMD <NUM>, any number of illuminators may be used with any type(s) of system(s) to practice techniques of the present disclosure.

<FIG> illustrate an example of SPAD exposure operations performed over a frame capture time period. In particular, <FIG> illustrates a SPAD array <NUM>, which may correspond to the SPAD array(s) <NUM> described hereinabove with reference to <FIG>. In this regard, each SPAD pixel (e.g., SPAD pixel <NUM>) of the SPAD array <NUM> is configurable to trigger avalanche events in response to detecting photons. The SPAD pixel <NUM> may be operated in a controlled, gated manner to facilitate different exposure operations for image acquisition.

<FIG> depicts ellipsis <NUM> between SPAD pixels of the SPAD array <NUM> and representations of exposure operations that will be described in more detail hereafter. The ellipsis <NUM> indicates that the exposure operations described hereafter may be performed using any number of SPAD pixels of a SPAD array <NUM> (e.g., all SPAD pixels). A single representation of the exposure operations is shown in <FIG> (and subsequent Figures) for the sake of clarity and simplicity. <FIG> additionally provides a time axis t to illustrate the temporal relationship among the different exposure operations that will be described hereinafter.

<FIG> shows that, to facilitate capturing of image frames usable for structured light depth computations, SPAD pixels of a SPAD array <NUM> are configured to perform multiple exposure operations in an interleaved manner. In particular, <FIG> illustrates ambient exposure operations (labeled as "A" in <FIG>), pattern <NUM> exposure operations (labeled as "P1" in <FIG> and referred to hereinafter as "P1 exposure operations"), pattern <NUM> exposure operations (labeled as "P2" in <FIG> and referred to hereinafter as "P2 exposure operations"), and pattern <NUM> exposure operations (labeled as "P3" in <FIG> and referred to hereinafter as "P3 exposure operations") performed over a frame capture time period <NUM>. In the example shown in <FIG>, the ambient exposure operations, P1 exposure operations, P2 exposure operations, and P3 exposure operations are performed in an interleaved manner, with sets of exposure operations including an ambient exposure operation, a P1 exposure operation, a P2 exposure operation, and a P3 exposure operation being performed one after another.

The ellipsis <NUM> indicates that any number of ambient exposure operations, P1 exposure operations, P2 exposure operations, and/or P3 exposure operations may be performed over the frame capture time period <NUM>. Furthermore, although the present example focuses, in at least some respects, on utilizing ambient exposure operations, P1 exposure operations, P2 exposure operations, and P3 exposure operations, ambient exposure operations may be omitted from the frame capture time period <NUM>, and/or additional or fewer pattern exposure operations may be interleaved within the frame capture time period <NUM>.

<FIG> furthermore illustrates (via dashed lines extending downward from the first ambient exposure operation) that an ambient exposure operation includes applying a set of shutter operations <NUM>. As noted above, applying a shutter operation to a SPAD pixel configures the SPAD pixel for photon detection by configuring the SPAD pixel to trigger avalanche events in response to detected photons. Thus, the presence of an avalanche event during a shutter operation indicates that the SPAD pixel detected a photon during the shutter operation. Whether a SPAD pixel experienced an avalanche event (and therefore detected a photon) during a shutter operation may be represented by a binary "<NUM>" or "<NUM>", with "<NUM>" indicating that an avalanche event occurred during the shutter operation and with "<NUM>" indicating that no avalanche event occurred during the shutter operation. Accordingly, <FIG> depicts binary counts <NUM> associated with each shutter operation <NUM>. The ellipsis <NUM> indicates that an ambient exposure operation may comprise any suitable number of shutter operations <NUM>.

<FIG> also depicts that the individual shutter operations <NUM> are performed over a particular gate time <NUM>. The gate time <NUM> is the duration over which a SPAD pixel becomes configured to trigger an avalanche event in response to a detected photon.

Although <FIG> only explicitly depicts the set of shutter operations <NUM> associated with the first ambient exposure operation, other sets of shutter operations are applied to facilitate the other exposures (i.e., the P1, P2, and/or P3 exposure operations). For each P1 exposure operation, shutter operations <NUM> are performed while an illuminator (e.g., illuminator <NUM>) is selectively activated (or pulsed) to project pattern <NUM> into the environment. As depicted in <FIG>, pattern <NUM> includes an illuminated vertical stripe (on the left, illustrated in white) and an unilluminated vertical stripe (on the right, illustrated in black). For each P2 exposure operation, shutter operations <NUM> are performed while an illuminator (e.g., illuminator <NUM>) is selectively activated (or pulsed) to project pattern <NUM> into the environment. As depicted in <FIG>, pattern <NUM> includes two illuminated vertical stripes and two unilluminated vertical stripes, which are arranged in an alternating fashion. Furthermore, for each P3 exposure operation, shutter operations <NUM> are performed while an illuminator (e.g., illuminator <NUM>) is selectively activated (or pulsed) to project pattern <NUM> into the environment. As depicted in <FIG>, pattern <NUM> includes four illuminated vertical stripes and four unilluminated vertical stripes, which are arranged in an alternating fashion. In contrast, for each ambient exposure operation, shutter operations <NUM> are performed while the illuminator(s) selectively refrain(s) from illuminating the environment. In this regard, over the frame capture time period, the illuminator(s) (e.g., including illuminator <NUM>) alternately emits different light patterns and refrains from emitting light.

As noted above, the ellipsis <NUM> indicates that any number of ambient exposure operations and pattern exposure operations may be performed over the frame capture time period <NUM>. As will be described in more detail hereafter, the results of the ambient exposure operations may be combined to form an ambient image, and the results of the different pattern exposure operations may be combined to form different pattern images. To provide desirable images, in some instances, at least two pattern exposure operations for each light pattern used are performed over a frame capture time period <NUM>. Furthermore, in some instances, systems refrain from pausing performance of the shutter operations <NUM> within the frame capture time period <NUM> in order to avoid motion artifacts. For example, systems may refrain from pausing performance of the shutter operations to perform readout operations (although, under some configurations, readout operations may be performed passively during the frame capture time period <NUM> without pausing performance of the shutter operations).

The shutter operations <NUM> performed during each separate ambient exposure operation (i.e., without emission of light by the illuminator(s)) may provide a separate subset of binary counts. For example, <FIG> illustrates various subsets 312A, 312B, and 312C of binary counts. Each subset 312A, 312B, and 312C of binary counts is associated with a different respective ambient exposure operation (illustrated in <FIG> by the arrows extending from the various ambient exposure operations to the various subsets 312A, 312B, and 312Cof binary counts). As indicated above, and as depicted in <FIG>, the various subsets 312A, 312B, and 312C of binary counts are not generated temporally contiguous to one another (i.e., because the pattern exposure operations intervene between the ambient exposure operations). The various subsets 312A, 312B, and 312C of binary counts may be combined to form a set of binary counts <NUM>, and the set of binary counts <NUM> may be used to generate an ambient image, even though the various subsets 312A, 312B, and 312C of binary counts that form the set of binary counts <NUM> are not temporally contiguous (see <FIG>).

Similarly, the shutter operations <NUM> performed during each separate P1 exposure operation (i.e., during emission of pattern <NUM> by the illuminator(s)) may provide a separate subset of binary counts. For example, <FIG> illustrates various subsets 316A, 316B, and 316C of binary counts. Each subset 316A, 316B, and 316C of binary counts is associated with a different respective P1 exposure operation (illustrated in <FIG> by the arrows extending from the various P1 exposure operations to the various subsets 316A, 316B, and 316C of binary counts). As indicated above, and as depicted in <FIG>, the various subsets 316A, 316B, and 316C of binary counts are not generated temporally contiguous to one another (i.e., because ambient exposure operations, P2 exposure operations, and P3 exposure operations intervene between the P1 exposure operations). The various subsets 316A, 316B, and 316C of binary counts may be combined to form a set of binary counts <NUM>, and the set of binary counts <NUM> may be used for generating a pattern <NUM> image, even though the various subsets 316A, 316B, and 316C of binary counts that form the set of binary counts <NUM> are not temporally contiguous (see <FIG>).

Also, the shutter operations <NUM> performed during each separate P2 exposure operation (i.e., during emission of pattern <NUM> by the illuminator(s)) may provide a separate subset of binary counts. For example, <FIG> illustrates various subsets 320A, 320B, and 320C of binary counts. Each subset 320A, 320B, and 320C of binary counts is associated with a different respective P2 exposure operation (illustrated in <FIG> by the arrows extending from the various P2 exposure operations to the various subsets 320A, 320B, and 320C of binary counts). As indicated above, and as depicted in <FIG>, the various subsets 320A, 320B, and 320C of binary counts are not generated temporally contiguous to one another (i.e., because ambient exposure operations, P1 exposure operations, and P3 exposure operations intervene between the P2 exposure operations). The various subsets 320A, 320B, and 320C of binary counts may be combined to form a set of binary counts <NUM>, and the set of binary counts <NUM> may be used for generating a pattern <NUM> image, even though the various subsets 320A, 320B, and 320C of binary counts that form the set of binary counts <NUM> are not temporally contiguous (see <FIG>).

In addition, the shutter operations <NUM> performed during each separate P3 exposure operation (i.e., during emission of pattern <NUM> by the illuminator(s)) may provide a separate subset of binary counts. For example, <FIG> illustrates various subsets 324A, 324B, and 324C of binary counts. Each subset 324A, 324B, and 324C of binary counts is associated with a different respective P3 exposure operation (illustrated in <FIG> by the arrows extending from the various P3 exposure operations to the various subsets 324A, 324B, and 324C of binary counts). As indicated above, and as depicted in <FIG>, the various subsets 324A, 324B, and 324C of binary counts are not generated temporally contiguous to one another (i.e., because ambient exposure operations, P1 exposure operations, and P2 exposure operations intervene between the P3 exposure operations). The various subsets 324A, 324B, and 324C of binary counts may be combined to form a set of binary counts <NUM>, and the set of binary counts <NUM> may be used for generating a pattern <NUM> image, even though the various subsets 324A, 324B, and 324C of binary counts that form the set of binary counts <NUM> are not temporally contiguous (see <FIG>).

Although <FIG> only illustrates a single set of binary counts <NUM> obtained from shutter operations <NUM> performed by a single SPAD pixel <NUM> during ambient exposure operations over the frame capture time period <NUM>, separate sets of binary counts from ambient exposure operations may be generated for each SPAD pixel of the SPAD array <NUM>. Similarly, although <FIG> only illustrates a single set of binary counts <NUM> obtained from shutter operations <NUM> performed by a single SPAD pixel <NUM> during P1 exposure operations over the frame capture time period <NUM>, separate sets of binary counts from P1 exposure operations may be generated for each SPAD pixel of the SPAD array <NUM>. Also, although <FIG> only illustrates a single set of binary counts <NUM> obtained from shutter operations <NUM> performed by a single SPAD pixel <NUM> during P2 exposure operations over the frame capture time period <NUM>, separate sets of binary counts from P2 exposure operations may be generated for each SPAD pixel of the SPAD array <NUM>. In addition, although <FIG> only illustrates a single set of binary counts <NUM> obtained from shutter operations <NUM> performed by a single SPAD pixel <NUM> during P3 exposure operations over the frame capture time period <NUM>, separate sets of binary counts from P3 exposure operations may be generated for each SPAD pixel of the SPAD array <NUM>.

<FIG> illustrates sets of ambient exposure binary counts <NUM>, which includes each set of binary counts generated by each SPAD pixel of the SPAD array <NUM> during ambient exposure operations (see <FIG>). Each set of binary counts of the sets of ambient exposure binary counts <NUM> (e.g., including set of binary counts <NUM> from <FIG>) includes a respective plurality of subsets of binary counts (e.g., subsets 312A-312C for set of binary counts <NUM>) generated by a SPAD pixel (e.g., SPAD pixel <NUM>) during the ambient exposure operations over the frame capture time period <NUM>.

<FIG> also illustrates ambient readout <NUM> performed using the sets of ambient exposure binary counts <NUM>. For a SPAD array, a "readout" comprises determining or outputting a number of photons detected over a set of shutter operations on a per-pixel basis. Pixels capturing brighter portions of a captured environment will have counted a greater number of photons than pixels capturing darker portions of the captured environment. The per-pixel number of photons detected over the set of shutter operations may therefore be used to form an intensity image.

Accordingly, ambient readout <NUM> may comprise determining or outputting the number of photons represented by each set of binary counts of the sets of ambient exposure binary counts <NUM>, where each set corresponds to a different SPAD pixel. Per-pixel intensity values may be determined based on the number of photons from each set, and the per-pixel intensity values may be used to generate the ambient image <NUM>.

Similarly, <FIG> illustrates sets of P1 exposure binary counts <NUM>, which includes each set of binary counts generated by each SPAD pixel of the SPAD array <NUM> during P1 exposure operations (see <FIG>). Each set of binary counts of the sets of P1 exposure binary counts <NUM> (e.g., including set of binary counts <NUM> from <FIG>) includes a respective plurality of subsets of binary counts (e.g., subsets 316A-316C for set of binary counts <NUM>) generated by a SPAD pixel (e.g., SPAD pixel <NUM>) during the P1 exposure operations over the frame capture time period <NUM>.

<FIG> also illustrates P1 readout <NUM> performed using the sets of P1 exposure binary counts <NUM>. P1 readout <NUM> may comprise determining or outputting the number of photons represented by each set of binary counts of the sets of P1 exposure binary counts <NUM>, where each set corresponds to a different SPAD pixel. Per-pixel intensity values may be determined based on the number of photons from each set, and the per-pixel intensity values may be used to generate the pattern <NUM> image <NUM>.

Furthermore, <FIG> illustrates sets of P2 exposure binary counts <NUM>, which includes each set of binary counts generated by each SPAD pixel of the SPAD array <NUM> during P2 exposure operations (see <FIG>). Each set of binary counts of the sets of P2 exposure binary counts <NUM> (e.g., including set of binary counts <NUM> from <FIG>) includes a respective plurality of subsets of binary counts (e.g., subsets 320A-320C for set of binary counts <NUM>) generated by a SPAD pixel (e.g., SPAD pixel <NUM>) during the P2 exposure operations over the frame capture time period <NUM>.

<FIG> also illustrates P2 readout <NUM> performed using the sets of P2 exposure binary counts <NUM>. P2 readout <NUM> may comprise determining or outputting the number of photons represented by each set of binary counts of the sets of P2 exposure binary counts <NUM>, where each set corresponds to a different SPAD pixel. Per-pixel intensity values may be determined based on the number of photons from each set, and the per-pixel intensity values may be used to generate the pattern <NUM> image <NUM>.

Also, <FIG> illustrates sets of P3 exposure binary counts <NUM>, which includes each set of binary counts generated by each SPAD pixel of the SPAD array <NUM> during P3 exposure operations (see <FIG>). Each set of binary counts of the sets of P3 exposure binary counts <NUM> (e.g., including set of binary counts <NUM> from <FIG>) includes a respective plurality of subsets of binary counts (e.g., subsets 324A-324C for set of binary counts <NUM>) generated by a SPAD pixel (e.g., SPAD pixel <NUM>) during the P3 exposure operations over the frame capture time period <NUM>.

<FIG> also illustrates P3 readout <NUM> performed using the sets of P3 exposure binary counts <NUM>. P3 readout <NUM> may comprise determining or outputting the number of photons represented by each set of binary counts of the sets of P3 exposure binary counts <NUM>, where each set corresponds to a different SPAD pixel. Per-pixel intensity values may be determined based on the number of photons from each set, and the per-pixel intensity values may be used to generate the pattern <NUM> image <NUM>.

<FIG> illustrates ambient image <NUM> including a representation of a moving ball captured by the SPAD array <NUM>. <FIG> also illustrates the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM> as each including a respective representation of the same moving ball captured by the SPAD array <NUM> under their respective illumination conditions. Because the ambient exposure operations used to generate the ambient image <NUM> are interleaved over the same frame capture time period <NUM> with the pattern illumination operations used to generate the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>, the moving ball is depicted in the ambient image <NUM>, the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM> in a spatially aligned manner. Stated differently, the motion of the ball will affect the capturing of the ambient image <NUM>, the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM> in substantially the same way.

Because the representations of the moving ball are substantially spatially aligned in the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>, these images may be well-suited for determining pixel signatures for facilitating depth calculations. <FIG> and <FIG> illustrate examples of determining a pixel signature associated with a SPAD pixel. In particular, <FIG> illustrates the ambient image <NUM>, the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>. <FIG> depicts an image pixel of the ambient image <NUM> corresponding to SPAD pixel <NUM> discussed hereinabove with reference to <FIG> (labeled in <FIG> as "<NUM>"). The following discussion describes how a pixel signature may be obtained for the SPAD pixel <NUM> (or the image pixel corresponding thereto).

<FIG> illustrates the set of binary counts <NUM> generated based on shutter operations <NUM> of the SPAD pixel <NUM> during ambient exposure operations (see as described hereinabove with reference to <FIG>). <FIG> furthermore illustrates an ambient light measure <NUM> determined based on the set of binary counts <NUM>. The ambient light measure <NUM> comprises a representation of number of detected photons represented in the set of binary counts <NUM>. In the present example, the set of binary counts <NUM> indicates that <NUM> photons were detected at the SPAD pixel <NUM> during the ambient exposure operations, providing an ambient light measure <NUM> of <NUM> photons (as illustrated in <FIG>).

As is shown in <FIG>, the ambient light measure <NUM> may be used to determine a threshold number of photons <NUM>. The threshold number of photons <NUM> indicates, in some instances, a cutoff number of photons that is usable to determine whether, while capturing the different pattern images, the SPAD pixel <NUM> captured a portion of a scene that was illuminated by a structured light pattern. In some instances, the threshold number of photons <NUM> is greater than the ambient light measure <NUM>.

As will be described hereinbelow, the threshold number of photons <NUM> may be used to determine signature values for the SPAD pixel <NUM> associated with the capturing of each of the pattern images (i.e., the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>), and the pixel signature for the SPAD pixel <NUM> may be based on the signature values.

<FIG> illustrates the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>, as well as a representation of the SPAD pixel <NUM> on each pattern image to visually depict the portion of the various pattern images captured by the SPAD pixel <NUM>. <FIG> includes the set of binary counts <NUM> captured by the SPAD pixel <NUM> during the P1 exposure operations for generating the pattern <NUM> image <NUM>. <FIG> furthermore illustrates a number of photons <NUM> determined based on the set of binary counts <NUM> (i.e., <NUM> photons) and shows a signature value <NUM> determined based on whether the number of photons <NUM> satisfies the threshold number of photons <NUM> discussed above.

As depicted in <FIG>, an arrow extends from the number of photons <NUM> to a decision block within the signature value <NUM>. In the example shown in <FIG>, if the number of photons <NUM> satisfies the threshold number of photons <NUM>, the signature value <NUM> is defined as a value of "<NUM>," and if the number of photons <NUM> fails to satisfy the threshold number of photons <NUM>, the signature value <NUM> is defined as a value of "<NUM>. " <FIG> illustrates an example in which, during the P1 exposure operations performed over the frame capture time period <NUM> to generate the pattern <NUM> image <NUM>, the SPAD pixel <NUM> captured a portion of the environment that was illuminated by pattern <NUM> as projected by an illuminator (see pattern <NUM> image <NUM> in <FIG>). Accordingly, <FIG> illustrates the number of photons <NUM> represented by the set of binary counts <NUM> as <NUM> photons, which far exceeds the ambient light measure <NUM> and therefore, in this example, satisfies the threshold number of photons <NUM>. Accordingly, <FIG> shows the "Yes" and "<NUM>" elements within the signature value <NUM> in bold and underlined format, indicating that the number of photons <NUM> satisfies the threshold number of photons <NUM>, resulting in a signature value <NUM> of "<NUM>" for the pattern <NUM> portion of the SPAD pixel <NUM>.

<FIG> similarly shows the set of binary counts <NUM> captured by the SPAD pixel <NUM> during the P2 exposure operations for generating the pattern <NUM> image <NUM>. <FIG> furthermore illustrates a number of photons <NUM> determined based on the set of binary counts <NUM> (i.e., <NUM> photons) and shows a signature value <NUM> determined based on whether the number of photons <NUM> satisfies the threshold number of photons <NUM> discussed above. As shown in <FIG>, the number of photons <NUM> represented by the set of binary counts <NUM> is <NUM> photons, which fails to exceed the ambient light measure <NUM> and therefore, in this example, fails to exceed the threshold number of photons <NUM>. Accordingly, <FIG> shows the "No" and "<NUM>" elements within the signature value <NUM> in bold and underlined format, indicating that the number of photons <NUM> fails to satisfy the threshold number of photons <NUM>, resulting in a signature value <NUM> of "<NUM>" for the pattern <NUM> portion of the SPAD pixel <NUM>.

Furthermore, <FIG> illustrates the set of binary counts <NUM> captured by the SPAD pixel <NUM> during the P3 exposure operations for generating the pattern <NUM> image <NUM>. <FIG> furthermore illustrates a number of photons <NUM> determined based on the set of binary counts <NUM> (i.e., <NUM> photons) and shows a signature value <NUM> determined based on whether the number of photons <NUM> satisfies the threshold number of photons <NUM> discussed above. As shown in <FIG>, the number of photons <NUM> represented by the set of binary counts <NUM> is <NUM> photons, which far exceeds the ambient light measure <NUM> and therefore, in this example, satisfies the threshold number of photons <NUM>. Accordingly, <FIG> shows the "Yes" and "<NUM>" elements within the signature value <NUM> in bold and underlined format, indicating that the number of photons <NUM> satisfies the threshold number of photons <NUM>, resulting in a signature value <NUM> of "<NUM>" for the pattern <NUM> portion of the SPAD pixel <NUM>.

Although the foregoing examples utilize measured numbers of photons to determine signature values, other metrics based on sets of binary counts may be used (e.g., average numbers of photons).

The signature values <NUM>, <NUM>, and <NUM> may be combined to form a pixel signature associated with the SPAD pixel <NUM>. Because the signatures values <NUM>, <NUM>, and <NUM> are determined based on the sets of binary counts <NUM>, <NUM>, and <NUM>, respectively, the pixel signature is also based on the binary counts <NUM>, <NUM>, and <NUM>. <FIG> illustrates a pixel signature <NUM> formed from the signature values <NUM>, <NUM>, and <NUM> by using a sequence of the signature values <NUM>, <NUM>, and <NUM> as an identifier. One will appreciate, in view of the present disclosure, that a pixel signature may take on other forms and that the signature values (which may also take on other forms) may be combined and/or transformed in various ways to generate the pixel signature.

It will be appreciated, in view of the present disclosure, that pixel signatures may be determined for any number of SPAD pixels (or image pixels associated with the SPAD pixels). <FIG> focus, in at least some respects, on techniques for generating pixel signatures that utilize per-pixel threshold numbers of photons determined based on the ambient image <NUM> (e.g., based on per-pixel ambient light measures <NUM>). However, other techniques may be used to generate pixel signatures.

An additional technique for generating pixel signatures is discussed hereinbelow with reference to <FIG> and <FIG>. <FIG> illustrates the ambient image <NUM>, the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>. Rather than determining per-pixel threshold numbers of photons, <FIG> illustrates performing ambient light subtraction <NUM> on the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM>. The ambient light subtraction <NUM> may comprise subtracting the intensity values, ambient light measures, or binary counts associated with the ambient image <NUM> from each of the pattern <NUM> image <NUM>, the pattern <NUM> image <NUM>, and the pattern <NUM> image <NUM> on a per-pixel basis. In the example shown in <FIG>, the ambient light subtraction operation <NUM> provides pattern <NUM> illumination image <NUM>, pattern <NUM> illumination image <NUM>, and pattern <NUM> illumination image <NUM>.

In some instances, by subtracting the ambient light from the pattern images to generate pattern illumination images, one or more common photon thresholds may be used to determine signature values for all SPAD pixels used to capture the images (e.g., a threshold of <NUM> photon). For example, <FIG> illustrates image pixels in pattern <NUM> illumination image <NUM>, pattern <NUM> illumination image <NUM>, and pattern <NUM> illumination image <NUM> that correspond to the SPAD pixel <NUM>. <FIG> also illustrates an illumination value <NUM> (i.e., <NUM> photons) for the SPAD pixel <NUM>, which is, in some instances, provided by subtracting an ambient light measure (e.g., ambient light measure <NUM>) from a number of photons (e.g., number of photons <NUM>) associated with the pattern <NUM> image <NUM>. In the example shown in <FIG>, the illumination value <NUM> for the SPAD pixel <NUM> is <NUM> photons, and the signature value <NUM> for the pattern <NUM> portion of the SPAD pixel <NUM> is determined to be a value of "<NUM>" based on the illumination value <NUM> satisfying a photon count threshold that is shared with other SPAD pixels (e.g., a threshold of <NUM> photon).

<FIG> also illustrates an illumination value <NUM> for the SPAD pixel <NUM>. In the example shown in <FIG>, the illumination value <NUM> for the SPAD pixel <NUM> is <NUM> photons, and the signature value <NUM> for the pattern <NUM> portion of the SPAD pixel <NUM> is determined to be a value of "<NUM>" based on the illumination value <NUM> failing to satisfy a photon count threshold that is shared with other SPAD pixels (e.g., a threshold of <NUM> photon). Furthermore, <FIG> illustrates an illumination value <NUM> for the SPAD pixel <NUM>. In the example shown in <FIG>, the illumination value <NUM> for the SPAD pixel <NUM> is <NUM> photons, and the signature value <NUM> for the pattern <NUM> portion of the SPAD pixel <NUM> is determined to be a value of "<NUM>" based on the illumination value <NUM> satisfying a photon count threshold that is shared with other SPAD pixels (e.g., a threshold of <NUM> photon). Similar to pixel signature <NUM> discussed above, pixel signature <NUM> may be determined based on the signature values <NUM>, <NUM>, and <NUM>.

The present examples focus on using three light patterns to generate pixel signatures. It will be appreciated, in view of the present disclosure, that any number of light patterns may be used to facilitate unique pixel signatures for pixels lying along the same scanline.

In some instances, SPAD pixels may be configured to perform any processing described herein on-sensor to provide sensor output that corresponds to pixel signatures, which may facilitate computationally efficient depth processing.

Furthermore, in some instances, parameters associated with capturing sets of binary counts for facilitating depth processing may be dynamically modified to account for the amount of ambient light present in a captured scene, the distance between image sensors and captured objects, and/or other factors. For example, where a captured scene includes high ambient light, additional light may need to be emitted by an illuminator to provide for sufficient differentiation between portions of the scene that are illuminated with pattern light and portions of the scene that are not. Accordingly, in some instances, based on detected ambient light (e.g., determined by capturing an ambient light image), a system may modify a pulse time period for pulsing an illuminator, a number of pulses associated with emitting one or more light patterns, an amount of light (e.g., intensity of light) emitted by an illuminator, a frame capture time period, shutter timing associated with shutter operations (e.g., gate time <NUM>), and/or other parameters.

As noted hereinabove, an illuminator (e.g., illuminator <NUM>) may be used as a "virtual camera" in conjunction with a SPAD sensor (e.g., SPAD sensor <NUM>) to facilitate structured light depth calculations. <FIG> illustrates pattern <NUM>, pattern <NUM>, and pattern <NUM>, which were project into the captured environment to generate pixel signatures <NUM> and/or <NUM> according to examples of the present disclosure. <FIG> also illustrates a virtual pixel <NUM> associated with particular pixel coordinates relative to pattern <NUM>, pattern <NUM>, and pattern <NUM>. A system may determine whether the particular pixel coordinates correspond to an illuminated portion or an unilluminated portion for each structured light pattern (e.g., pattern <NUM>, pattern <NUM>, and pattern <NUM>).

Accordingly, <FIG> depicts the virtual pixel <NUM> overlaid on the various patterns (i.e., pattern <NUM>, pattern <NUM>, and pattern <NUM>) and depicts an arrow extending from the virtual pixel <NUM> to a respective decision block associated with a respective illumination value (i.e., illumination value <NUM> for pattern <NUM>, illumination value <NUM> for pattern <NUM>, and illumination value <NUM> for pattern <NUM>). The decision blocks associated with the illumination values <NUM>, <NUM>, and <NUM> conceptually depict a determination of whether the coordinates of the virtual pixel <NUM> correspond to an illuminated or unilluminated portion of the various patterns. As is evident from <FIG>, the pixel coordinates of the virtual pixel <NUM> correspond to an illuminated portion of pattern <NUM>, which is represented in the example of <FIG> by an illumination value of "<NUM>" for the illumination value <NUM> (with "<NUM>" and "Yes" illustrated in bold and underlined format). <FIG> also depicts the pixel coordinates of the virtual pixel <NUM> corresponding to an unilluminated portion of pattern <NUM>, which is represented in the example of <FIG> by an illumination value of "<NUM>" for the illumination value <NUM>. Furthermore, <FIG> illustrates the pixel coordinates of the virtual pixel <NUM> corresponding to an illuminated portion of pattern <NUM>, which is represented in the example of <FIG> by an illumination value of "<NUM>" for the illumination value <NUM>.

<FIG> illustrates a virtual pixel signature <NUM> generated based on the illumination values <NUM>-<NUM> discussed above. In the example of <FIG>, the virtual pixel signature <NUM> is represented by a sequence of values including "<NUM>", "<NUM>", and "<NUM>", which matches the sequence of values that define the pixel signatures <NUM> and <NUM> discussed above for the SPAD pixel <NUM>.

A system may determine a depth value for a SPAD pixel by identifying a corresponding virtual pixel (on a same scanline) that has a virtual pixel signature that matches the pixel signature for the SPAD pixel and using the pixel coordinates of the SPAD pixel and the corresponding virtual pixel to determine a disparity value (which may be used to calculate depth). <FIG> conceptually depicts such functionality, illustrating pixel coordinates <NUM> associated with the SPAD pixel <NUM> and the pixel signature <NUM> being used with pixel coordinates <NUM> associated with the corresponding virtual pixel <NUM> and the matching virtual pixel signature <NUM> to determine a disparity value <NUM>. Such functionality may be performed for all SPAD pixels of a SPAD array to determine per-pixel disparity and/or depth values for generating a depth map.

The following discussion now refers to a number of methods and method acts that may be performed by the disclosed systems. Although the method acts are discussed in a certain order and illustrated in a flow chart as occurring in a particular order, no particular ordering is required unless specifically stated, or required because an act is dependent on another act being completed prior to the act being performed. One will appreciate that certain embodiments of the present disclosure may omit one or more of the acts described herein.

<FIG> illustrates an example flow diagram <NUM> depicting acts associated with structured light depth computation using SPADs. The discussion of the various acts represented in flow diagram <NUM> include references to various hardware components described in more detail with reference to <FIG> and/or <NUM>.

Act <NUM> of flow diagram <NUM> includes, over a frame capture time period, selectively activating an illuminator to perform interleaved structured light illumination operations, the interleaved structured light illumination operations comprising alternately emitting at least a first structured light pattern from the illuminator and emitting at least a second structured light pattern from the illuminator. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>), an illuminator (e.g., illuminator <NUM>), and/or other components. In some instances, the first structured light pattern and the second structured light pattern comprise striped structured light patterns. Furthermore, in some instances the second structured light pattern comprises more stripes than the first structured light pattern. Furthermore, performing the interleaved structured light illumination operations comprises causing the first structured light pattern and the second structured light pattern to be emitted from the illuminator at least twice over the frame capture time period. Still furthermore, in some instances, performing the plurality of sequential shutter operations comprises refraining from pausing performance of the shutter operations to perform a readout operation during the frame capture time period.

Act <NUM> of flow diagram <NUM> includes, over the frame capture time period, performing a plurality of sequential shutter operations to configure each SPAD pixel of a SPAD array to enable photon detection, the plurality of sequential shutter operations generating, for each SPAD pixel of the SPAD array, a plurality of binary counts indicating whether a photon was detected during each of the plurality of sequential shutter operations. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>) and/or other components.

Act <NUM> of flow diagram <NUM> includes, for each SPAD pixel of the SPAD array, determining a respective pixel signature based on at least (i) a first set of binary counts generated via the SPAD pixel during illumination by the first structured light pattern over the frame capture time period and (ii) a second set of binary counts generated via the SPAD pixel during illumination by the second structured light pattern over the frame capture time period. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>) and/or other components. In some instances, the first set of binary counts comprises a first plurality of subsets of binary counts generated via the SPAD pixel during illumination by the first structured light pattern over the frame capture time period, and each of the first plurality of subsets of binary counts are not generated temporally contiguous to one another. In some instances, the second set of binary counts comprises a second plurality of subsets of binary counts generated via the SPAD pixel during illumination by the second structured light pattern over the frame capture time period, and each of the second plurality of subsets of binary counts are not generated temporally contiguous to one another. Furthermore, in some instances, at least one subset of binary counts of the second plurality of subsets of binary counts temporally intervenes between at least two subsets of binary counts of the first plurality of subsets of binary counts.

In some instances, for each SPAD pixel of the SPAD array, the respective pixel signature is based on at least a respective first signature value and a respective second signature value. In some implementations, the respective first signature value is determined by determining a first illumination value by subtracting a respective ambient light measure from a number of photons represented by the first set of binary counts and determining whether the first illumination value satisfies a threshold number of photons. Furthermore, in some instances, the respective second value is determined by determining a second illumination value by subtracting the respective ambient light measure from a number of photons represented by the second set of binary counts and determining whether the second illumination value satisfies the threshold number of photons.

Still furthermore, in some instances, for each SPAD pixel of the SPAD array, the respective pixel signature is based on at least a respective first signature value and a respective second signature value, the respective first signature value is based on whether a number of photons represented by the first set of binary counts satisfies a respective threshold number of photons, and the respective second signature value being based on whether a number of photons represented by the second set of binary counts. In some implementations, for each SPAD pixel of the SPAD array, the threshold number of photons is determined based on a respective ambient light measure. The respective ambient light measure is determined based on an ambient light image frame captured using the SPAD array while refraining from emitting a structured light pattern from the illuminator. In some instances, the ambient light image frame is generated based on photons detected by SPAD pixels of the SPAD array during the frame capture time period while refraining from emitting a structured light pattern from the illuminator.

Act <NUM> of flow diagram <NUM> includes determining a plurality of virtual pixel signatures using at least the first structured light pattern and the second structured light pattern. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>) and/or other components. In some instances, each virtual pixel signature of the plurality of virtual pixel signatures is associated with respective pixel coordinates relative to the first structured light pattern and the second structured light pattern. Each particular virtual pixel signature of the plurality of virtual pixel signatures may be based on (i) whether the respective pixel coordinates for the particular virtual pixel signature are associated with an illuminated portion or an unilluminated portion of the first structured light pattern and (ii) whether the respective pixel coordinates for the particular virtual pixel signature are associated with an illuminated portion or an unilluminated portion of the second structured light pattern.

Act <NUM> of flow diagram <NUM> includes generating a depth map by identifying correspondences between (i) the respective pixel signatures of the SPAD pixels of the SPAD array and (ii) the plurality of virtual pixel signatures. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>) and/or other components.

Act <NUM> of flow diagram <NUM> includes, based on an ambient light image frame captured using the SPAD array while refraining from emitting a structured light pattern from the illuminator, dynamically modifying (i) a pulse time period associated with emitting the first structured light pattern or the second structured light pattern, (ii) a number of pulses associated with emitting the first structured light pattern or the second structured light pattern over the frame capture time period, (iii) an amount of emitted light associated with emitting the first structured light pattern or the second structured light pattern, (iv) the frame capture time period, or (v) a shutter timing associated with performing the plurality of sequential shutter operations. Act <NUM> is performed, in some instances, utilizing one or more components of a system <NUM> (e.g., processor(s) <NUM>, storage <NUM>, sensor(s) <NUM>, SPAD array(s) <NUM>), I/O system(s) <NUM>, communication system(s) <NUM>) and/or other components.

Disclosed embodiments may comprise or utilize a special purpose or general-purpose computer including computer hardware, as discussed in greater detail below. Disclosed embodiments also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general-purpose or special-purpose computer system. Computer-readable media that store computer-executable instructions in the form of data are one or more "physical computer storage media" or "hardware storage device(s). " Computer-readable media that merely carry computer-executable instructions without storing the computer-executable instructions are "transmission media. " Thus, by way of example and not limitation, the current embodiments can comprise at least two distinctly different kinds of computer-readable media: computer storage media and transmission media.

Computer storage media (aka "hardware storage device") are computer-readable hardware storage devices, such as RAM, ROM, EEPROM, CD-ROM, solid state drives ("SSD") that are based on RAM, Flash memory, phase-change memory ("PCM"), or other types of memory, or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code means in hardware in the form of computer-executable instructions, data, or data structures and that can be accessed by a general-purpose or special-purpose computer.

When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmission media can include a network and/or data links which can be used to carry program code in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

Computer-executable instructions comprise, for example, instructions and data which cause a general-purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions.

Disclosed embodiments may comprise or utilize cloud computing. A cloud model can be composed of various characteristics (e.g., on-demand self-service, broad network access, resource pooling, rapid elasticity, measured service, etc.), service models (e.g., Software as a Service ("SaaS"), Platform as a Service ("PaaS"), Infrastructure as a Service ("IaaS"), and deployment models (e.g., private cloud, community cloud, public cloud, hybrid cloud, etc.).

Those skilled in the art will appreciate that the invention may be practiced in network computing environments with many types of computer system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, wearable devices, and the like. The invention may also be practiced in distributed system environments where multiple computer systems (e.g., local and remote systems), which are linked through a network (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links), perform tasks. In a distributed system environment, program modules may be located in local and/or remote memory storage devices.

For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), central processing units (CPUs), graphics processing units (GPUs), and/or others.

As used herein, the terms "executable module," "executable component," "component," "module," or "engine" can refer to hardware processing units or to software objects, routines, or methods that may be executed on one or more computer systems. The different components, modules, engines, and services described herein may be implemented as objects or processors that execute on one or more computer systems (e.g., as separate threads).

One will also appreciate how any feature or operation disclosed herein may be combined with any one or combination of the other features and operations disclosed herein. Additionally, the content or feature in any one of the figures may be combined or used in connection with any content or feature used in any of the other figures. In this regard, the content disclosed in any one figure is not mutually exclusive and instead may be combinable with the content from any of the other figures.

Claim 1:
A system (<NUM>) for structured light depth computation using single photon avalanche diodes, the system (<NUM>) comprising:
a single photon avalanche diode array (<NUM>, <NUM>) comprising a plurality of single photon avalanche diode pixels (<NUM>, <NUM>);
an illuminator (<NUM>) configured to emit one or more structured light patterns;
one or more processors (<NUM>); and
one or more hardware storage devices (<NUM>) storing instructions (<NUM>) that are executable by the one or more processors (<NUM>) to configure the system (<NUM>) to facilitate structured light depth computation using the single photon avalanche diodes by configuring the system (<NUM>) to:
over a frame capture time period (<NUM>), selectively activate the illuminator (<NUM>) to perform interleaved structured light illumination operations, the interleaved structured light illumination operations comprising alternately emitting at least a first structured light pattern from the illuminator (<NUM>) and emitting at least a second structured light pattern from the illuminator (<NUM>), wherein the first structured light pattern is different from the second structured light pattern, and wherein performing the interleaved structured light illumination operations comprises causing the first structured light pattern and the second structured light pattern to be emitted from the illuminator (<NUM>) at least twice over the frame capture time period (<NUM>) and within the same frame capture time period (<NUM>); and
over the frame capture time period (<NUM>), perform a plurality of sequential shutter operations (<NUM>) to configure the single photon avalanche diode array (<NUM>, <NUM>) to enable photon detection, the plurality of sequential shutter operations (<NUM>) generating, for each single photon avalanche diode pixel (<NUM>, <NUM>) of the single photon avalanche diode array (<NUM>, <NUM>), a plurality of binary counts (<NUM>) indicating whether a photon was detected during each of the plurality of sequential shutter operations (<NUM>).