U.S. Pat. No. 12,293,752

DETAILED DESCRIPTION

This disclosure relates generally to computer ecosystems including aspects of consumer electronics (CE) device networks such as but not limited to computer game networks. A system herein may include server and client components which may be connected over a network such that data may be exchanged between the client and server components. The client components may include one or more computing devices including game consoles such as Sony PlayStation® or a game console made by Microsoft or Nintendo or other manufacturer, extended reality (XR) headsets such as virtual reality (VR) headsets, augmented reality (AR) headsets, portable televisions (e.g., smart TVs, Internet-enabled TVs), portable computers such as laptops and tablet computers, and other mobile devices including smart phones and additional examples discussed below. These client devices may operate with a variety of operating environments. For example, some of the client computers may employ, as examples, Linux operating systems, operating systems from Microsoft, or a Unix operating system, or operating systems produced by Apple, Inc., or Google, or a Berkeley Software Distribution or Berkeley Standard Distribution (BSD) OS including descendants of BSD. These operating environments may be used to execute one or more browsing programs, such as a browser made by Microsoft or Google or Mozilla or other browser program that can access websites hosted by the Internet servers discussed below. Also, an operating environment according to present principles may be used to execute one or more computer game programs.

Servers and/or gateways may be used that may include one or more processors executing instructions that configure the servers to receive and transmit data over a network such as the Internet. Or a client and server can be connected over a local intranet or a virtual private network. A server or controller may be instantiated by a game console such as a Sony PlayStation®, a personal computer, etc.

Information may be exchanged over a network between the clients and servers. To this end and for security, servers and/or clients can include firewalls, load balancers, temporary storages, and proxies, and other network infrastructure for reliability and security. One or more servers may form an apparatus that implement methods of providing a secure community such as an online social website or gamer network to network members.

A processor may be a single- or multi-chip processor that can execute logic by means of various lines such as address lines, data lines, and control lines and registers and shift registers. A processor including a digital signal processor (DSP) may be an embodiment of circuitry.

Components included in one embodiment can be used in other embodiments in any appropriate combination. For example, any of the various components described herein and/or depicted in the Figures may be combined, interchanged, or excluded from other embodiments.

“A system having at least one of A, B, and C” (likewise “a system having at least one of A, B, or C” and “a system having at least one of A, B, C”) includes systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together.

Referring now toFIG.1, an example system10is shown, which may include one or more of the example devices mentioned above and described further below in accordance with present principles. The first of the example devices included in the system10is a consumer electronics (CE) device such as an audio video device (AVD)12such as but not limited to a theater display system which may be projector-based, or an Internet-enabled TV with a TV tuner (equivalently, set top box controlling a TV). The AVD12alternatively may also be a computerized Internet enabled (“smart”) telephone, a tablet computer, a notebook computer, a head-mounted device (HMD) and/or headset such as smart glasses or a VR headset, another wearable computerized device, a computerized Internet-enabled music player, computerized Internet-enabled headphones, a computerized Internet-enabled implantable device such as an implantable skin device, etc. Regardless, it is to be understood that the AVD12is configured to undertake present principles (e.g., communicate with other CE devices to undertake present principles, execute the logic described herein, and perform any other functions and/or operations described herein).

Accordingly, to undertake such principles the AVD12can be established by some, or all of the components shown. For example, the AVD12can include one or more touch-enabled displays14that may be implemented by a high definition or ultra-high definition “4K” or higher flat screen. The touch-enabled display(s)14may include, for example, a capacitive or resistive touch sensing layer with a grid of electrodes for touch sensing consistent with present principles.

The AVD12may also include one or more speakers16for outputting audio in accordance with present principles, and at least one additional input device18such as an audio receiver/microphone for entering audible commands to the AVD12to control the AVD12. The example AVD12may also include one or more network interfaces20for communication over at least one network22such as the Internet, an WAN, an LAN, etc. under control of one or more processors24. Thus, the interface20may be, without limitation, a Wi-Fi transceiver, which is an example of a wireless computer network interface, such as but not limited to a mesh network transceiver. It is to be understood that the processor24controls the AVD12to undertake present principles, including the other elements of the AVD12described herein such as controlling the display14to present images thereon and receiving input therefrom. Furthermore, note the network interface20may be a wired or wireless modem or router, or other appropriate interface such as a wireless telephony transceiver, or Wi-Fi transceiver as mentioned above, etc.

In addition to the foregoing, the AVD12may also include one or more input and/or output ports26such as a high-definition multimedia interface (HDMI) port or a universal serial bus (USB) port to physically connect to another CE device and/or a headphone port to connect headphones to the AVD12for presentation of audio from the AVD12to a user through the headphones. For example, the input port26may be connected via wire or wirelessly to a cable or satellite source26aof audio video content. Thus, the source26amay be a separate or integrated set top box, or a satellite receiver. Or the source26amay be a game console or disk player containing content. The source26awhen implemented as a game console may include some or all of the components described below in relation to the CE device48.

The AVD12may further include one or more computer memories/computer-readable storage media28such as disk-based or solid-state storage that are not transitory signals, in some cases embodied in the chassis of the AVD as standalone devices or as a personal video recording device (PVR) or video disk player either internal or external to the chas sis of the AVD for playing back AV programs or as removable memory media or the below-described server. Also, in some embodiments, the AVD12can include a position or location receiver such as but not limited to a cellphone receiver, GPS receiver and/or altimeter30that is configured to receive geographic position information from a satellite or cellphone base station and provide the information to the processor24and/or determine an altitude at which the AVD12is disposed in conjunction with the processor24.

Continuing the description of the AVD12, in some embodiments the AVD12may include one or more cameras32that may be a thermal imaging camera, a digital camera such as a webcam, an IR sensor, an event-based sensor, and/or a camera integrated into the AVD12and controllable by the processor24to gather pictures/images and/or video in accordance with present principles. Also included on the AVD12may be a Bluetooth® transceiver34and other Near Field Communication (NFC) element36for communication with other devices using Bluetooth and/or NFC technology, respectively. An example NFC element can be a radio frequency identification (RFID) element.

Further still, the AVD12may include one or more auxiliary sensors38that provide input to the processor24. For example, one or more of the auxiliary sensors38may include one or more pressure sensors forming a layer of the touch-enabled display14itself and may be, without limitation, piezoelectric pressure sensors, capacitive pressure sensors, piezoresistive strain gauges, optical pressure sensors, electromagnetic pressure sensors, etc. Other sensor examples include a pressure sensor, a motion sensor such as an accelerometer, gyroscope, cyclometer, or a magnetic sensor, an infrared (IR) sensor, an optical sensor, a speed and/or cadence sensor, an event-based sensor, a gesture sensor (e.g., for sensing gesture command). The sensor38thus may be implemented by one or more motion sensors, such as individual accelerometers, gyroscopes, and magnetometers and/or an inertial measurement unit (IMU) that typically includes a combination of accelerometers, gyroscopes, and magnetometers to determine the location and orientation of the AVD12in three dimension or by an event-based sensors such as event detection sensors (EDS). An EDS consistent with the present disclosure provides an output that indicates a change in light intensity sensed by at least one pixel of a light sensing array. For example, if the light sensed by a pixel is decreasing, the output of the EDS may be −1; if it is increasing, the output of the EDS may be a +1. No change in light intensity below a certain threshold may be indicated by an output binary signal of 0.

The AVD12may also include an over-the-air TV broadcast port40for receiving OTA TV broadcasts providing input to the processor24. In addition to the foregoing, it is noted that the AVD12may also include an infrared (IR) transmitter and/or IR receiver and/or IR transceiver42such as an IR data association (IRDA) device. A battery (not shown) may be provided for powering the AVD12, as may be a kinetic energy harvester that may turn kinetic energy into power to charge the battery and/or power the AVD12. A graphics processing unit (GPU)44and field programmable gated array46also may be included. One or more haptics/vibration generators47may be provided for generating tactile signals that can be sensed by a person holding or in contact with the device. The haptics generators47may thus vibrate all or part of the AVD12using an electric motor connected to an off-center and/or off-balanced weight via the motor's rotatable shaft so that the shaft may rotate under control of the motor (which in turn may be controlled by a processor such as the processor24) to create vibration of various frequencies and/or amplitudes as well as force simulations in various directions.

A light source such as a projector such as an infrared (IR) projector also may be included.

In addition to the AVD12, the system10may include one or more other CE device types. In one example, a first CE device48may be a computer game console that can be used to send computer game audio and video to the AVD12via commands sent directly to the AVD12and/or through the below-described server while a second CE device50may include similar components as the first CE device48. In the example shown, the second CE device50may be configured as a computer game controller manipulated by a player or a head-mounted display (HMD) worn by a player. The HMD may include a heads-up transparent or non-transparent display for respectively presenting AR/MR content or VR content (more generally, extended reality (XR) content). The HMD may be configured as a glasses-type display or as a bulkier VR-type display vended by computer game equipment manufacturers.

In the example shown, only two CE devices are shown, it being understood that fewer or greater devices may be used. A device herein may implement some or all of the components shown for the AVD12. Any of the components shown in the following figures may incorporate some or all of the components shown in the case of the AVD12.

Now in reference to the afore-mentioned at least one server52, it includes at least one server processor54, at least one tangible computer readable storage medium56such as disk-based or solid-state storage, and at least one network interface58that, under control of the server processor54, allows for communication with the other illustrated devices over the network22, and indeed may facilitate communication between servers and client devices in accordance with present principles. Note that the network interface58may be, e.g., a wired or wireless modem or router, Wi-Fi transceiver, or other appropriate interface such as, e.g., a wireless telephony transceiver.

Accordingly, in some embodiments the server52may be an Internet server or an entire server “farm” and may include and perform “cloud” functions such that the devices of the system10may access a “cloud” environment via the server52in example embodiments for, e.g., network gaming applications. Or the server52may be implemented by one or more game consoles or other computers in the same room as the other devices shown or nearby.

The components shown in the following figures may include some or all components shown in herein. Any user interfaces (UI) described herein may be consolidated and/or expanded, and UI elements may be mixed and matched between Uls.

Present principles may employ various machine learning models, including deep learning models. Machine learning models consistent with present principles may use various algorithms trained in ways that include supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, feature learning, self-learning, and other forms of learning. Examples of such algorithms, which can be implemented by computer circuitry, include one or more neural networks, such as a convolutional neural network (CNN), a recurrent neural network (RNN), and a type of RNN known as a long short-term memory (LSTM) network. Support vector machines (SVM) and Bayesian networks also may be considered to be examples of machine learning models. In addition to the types of networks set forth above, models herein may be implemented by classifiers.

As understood herein, performing machine learning may therefore involve accessing and then training a model on training data to enable the model to process further data to make inferences. An artificial neural network/artificial intelligence model trained through machine learning may thus include an input layer, an output layer, and multiple hidden layers in between that that are configured and weighted to make inferences about an appropriate output.

Refer now toFIG.2. A computer simulation such as a computer game may be sent from a computer game console200or a computer game server202to a display device204such as a TV for presentation of the computer simulation under control of one or more computer simulation controllers206, such as but not limited to a PlayStation® controller or other controller.

One or more haptic generators208may be provided on the controller206, which can be operated by a player210to control presentation of the computer simulation. Audio sourced from the game console200or server202is played on one or more speakers212of a speaker system. The player210may wear a virtual reality (VR) or augmented reality (AR) head-mounted display (HMD) such as a headset214such as a PlayStation® headset. Any one or more of the console200, display204, controller206, and headset214may include one or more motion sensors216, one or more cameras218, and one or more microphones220.

In addition to the speaker(s)212of the display204, the headset214may include one or more speakers222. The player210may be immersed in a VR or AR computer simulation being presented on the headset214with audio from the simulation being played on the headset speaker222when the player210may be interrupted by a real world disturbance such as a dog braking, a motor starting, or a person224shouting.

The elements of the system shown inFIG.2can incorporate some or all of the appropriate devices and components described above in reference toFIG.1.

FIG.3illustrates example logic in a first implementation. Commencing at block300, background noise is recorded in the vicinity of the player shown inFIG.2. The background noise may be detected by any one or more of the microphones shown inFIG.2and may be averaged over a time period such as ten minutes or thirty minutes or other period to establish the amplitude of a baseline background noise floor.

Decision diamond302indicates that during game play, should the amplitude of a deviation (also referred to herein as a disturbance) in background noise exceed a threshold above the floor established at block300, if desired the logic may proceed to optional step304to determine whether the noise detected at decision diamond302lasts for at least a certain duration, e.g., more than one-half second, to avoid invoking active noise canceling ANC) or ambient noise addition based on spurious spikes.

From optional step304if the deviation lasts at least the duration or from decision diamond302when the deviation exceeds the threshold and step304is omitted, the logic moves to block306. At block306ambient noise in the vicinity of the player may be gradually introduced at a rate and amplitude that may depend on the amplitude of the deviation detected at decision diamond302, to avoid startling the player with a sudden increase in emulated ambient noise.

The ambient noise may be emulated to be gradually increased by, e.g., playing, on the headset speakers, white noise at a gradually increasing amplitude. The amplitude may gradually increase along a continuous amplitude curve that may be linear, the slope of which may depend on the amplitude of the deviation. Once the deviation ceases, emulated amplitude noise also ceases.

FIG.4illustrates further. A background noise floor is illustrated as a horizontal line400over time. A first deviation402has an amplitude significantly exceeding the floor400, but a short time duration Δt1and so no emulated ambient noise is generated when optional step304inFIG.3is used.

On the other hand, a second deviation404has an amplitude significantly exceeding the floor400along with a time duration Δt2that is greater than the period discussed inFIG.3above and so emulated ambient noise406is generated with a gradually increasing volume, in the example shown, a linearly increasing volume although it is to be understood that the emulated noise may increase by temporally equally-spaced decibel levels. WhileFIG.4illustrates for ease of perception that the emulated ambient noise406continues to increase after the second deviation404ends, it is to be understood that the emulated ambient noise may end when the deviation ends.

FIGS.5-7illustrate alternative techniques. Commencing at block500inFIG.5, a motion signal is received from any one or more of the motion sensors shown inFIG.2, potentially indicating a possible disturbance. If the motion signals indicate a possible disturbance at decision diamond502, active noise canceling (ANC) may be implemented at a gradually increasing rate at block504.

The determination at decision diamond502may be made using rules, e.g., if speed of motion exceeds a threshold, it indicates a disturbance, or by a machine learning (ML) model trained on a training set of motion signals with ground truth labels indicating whether the signals are or are not to be regarded as disturbances.

Turning to block600inFIG.6, a microphone signal is received from any one or more of the microphones shown inFIG.2, potentially indicating a possible disturbance. If the microphone signals indicate a possible disturbance at decision diamond602, ANC may be implemented at a gradually increasing rate at block604.

The determination at decision diamond602may be made using rules, e.g., if volume of microphone signal exceeds a threshold, it indicates a disturbance. Or, a ML model may make the determination. Such a ML model may be trained on a training set of microphone signals with ground truth labels indicating whether the signals are or are not to be regarded as disturbances.

Now consider block700inFIG.7, in which one or more mages from any one or more of the cameras shown inFIG.2is received, potentially indicating a possible disturbance. If the image(s) indicate a possible disturbance at decision diamond702, ANC may be implemented at a gradually increasing rate at block704.

The determination at decision diamond702may be made using rules, e.g., if a shouting person or barking dog is imaged it indicates a disturbance. Or, a ML model may make the determination. Such a ML model may be trained on a training set of images with ground truth labels indicating whether the images are or are not to be regarded as disturbances.

The techniques described above forFIGS.3and5-7may be combined if desired.

FIG.8illustrates the techniques ofFIGS.5-7. When a disturbance800is determined to have occurred, ANC802is implemented at first at a low level, increasingly linearly to higher levels as shown.

While the particular embodiments are herein shown and described in detail, it is to be understood that the subject matter which is encompassed by the present invention is limited only by the claims.