Abstract: A processor accesses a depth map and a first image of a scene generated using one or more sensors of an artificial reality device. The processor generates, based on the first image, segmentation masks respectively associated with a plurality of object types. The segmentation masks segment the depth map into a plurality of segmented depth maps respectively associated with the object types. The processor generates meshes using, respectively, the segmented depth maps. For each eye of the user, the processor captures a second image and generates, based on the second image, segmentation information. The processor warps the plurality of meshes to generate warped meshes for the eye, and then generates an eye-specific mesh for the eye by compositing the warped meshes according to the segmentation information. The processor renders an output image for the eye using the second image and the eye-specific mesh.

Abstract: In one embodiment, a computing system is configured to, during a first tracking session, detect first landmarks in a first image of the environment surrounding a user, and determine a first location of the user by comparing detected first landmarks to a landmark database. During a second tracking session, the computing system captures motion data and estimates a second location of the user based on the motion data and first user location. Based on the motion data and first user location, the computing system detects landmarks in a second image at a second location. The system accesses expected landmarks from the landmark database visible at the second location and determines the estimated second location of the user is inaccurate by comparing the expected landmarks with the second landmarks. The computing system re-localizes the user by comparing the landmarks in the landmark database and third landmarks in a third image.

Abstract: In one embodiment, a method includes capturing, using one or more cameras implemented in a wearable device worn by a user, a first image depicting at least a part of a hand of the user holding a controller in an environment, identifying one or more features from the first image to estimate a pose of the hand of the user, estimating a first pose of the controller based on the pose of the hand of the user and an estimated grip that defines a relative pose between the hand of the user and the controller, receiving IMU data of the controller, and estimating a second pose of the controller by updating the first pose of the controller using the IMU data of the controller. The method utilizes multiple data sources to track the controller under various conditions of the environment to provide an accurate controller tracking consistently.

Abstract: In one embodiment, a method includes capturing, using one or more cameras implemented in a wearable device worn by a user, a first image depicting at least a part of a hand of the user holding a controller in an environment, identifying one or more features from the first image to estimate a pose of the hand of the user, estimating a first pose of the controller based on the pose of the hand of the user and an estimated grip that defines a relative pose between the hand of the user and the controller, receiving IMU data of the controller, and estimating a second pose of the controller by updating the first pose of the controller using the IMU data of the controller. The method utilizes multiple data sources to track the controller under various conditions of the environment to provide an accurate controller tracking consistently.

Abstract: One embodiment is directed to controlling a user device based on an interpreted user intention. Another embodiment is directed to generating a three-dimensional first-resolution digital map of a geographic area in real world based on second-resolution observations on the geographic area using a machine-learning model, where the first resolution is higher than the second resolution. Another embodiment is directed to estimating a location and/or a pose of a camera with images captured by the camera and data from Inertial Measurement Unit (IMU) sensors. Another embodiment is directed to causing the content of an app running on a first device to be rendered by and displayed on a second device. Yet another embodiment is directed to an augmented reality device comprising a pair of glasses and a hat.

Abstract: In one embodiment, a method includes capturing, using one or more cameras implemented in a wearable device worn by a user, a first image depicting at least a part of a hand of the user holding a controller in an environment, identifying one or more features from the first image to estimate a pose of the hand of the user, estimating a first pose of the controller based on the pose of the hand of the user and an estimated grip that defines a relative pose between the hand of the user and the controller, receiving IMU data of the controller, and estimating a second pose of the controller by updating the first pose of the controller using the IMU data of the controller. The method utilizes multiple data sources to track the controller under various conditions of the environment to provide an accurate controller tracking consistently.

Abstract: In one embodiment, a method for tracking includes receiving motion data captured by a motion sensor of a wearable device, generating a pose of the wearable device based on the motion data, capturing a first frame of the wearable device by a camera using a first exposure time, identifying, in the first frame, a pattern of lights disposed on the wearable device, capturing a second frame of the wearable device by the camera using a second exposure time, identifying, in the second frame, predetermined features of the wearable device, and adjusting the pose of the wearable device in the environment based on the identified pattern of light in the first frame or the identified predetermined features in the second frame. The method utilizes the predetermined features for tracking the wearable device in a visible-light frame under specific light conditions to improve the accuracy of the pose of controller.

Abstract: The disclosed computer-implemented method for offloading image-based tracking operations from a general processing unit to a hardware accelerator unit may include (1) sending imaging data from an imaging device to a hardware accelerator unit, and (2) directing the hardware accelerator unit to generate a multi-scale representation of the imaging data sent from the imaging device, (3) preparing a set of input data for a set of image-based tracking operations, and (4) directing the hardware accelerator unit to execute the set of image-based tracking operations using the generated multi-scale representation of the imaging data and the prepared set of input data. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: In one embodiment, a computing system is configured to track objects in an environment or localize a user device. For example, the system accesses an image of an environment captured from a viewpoint. Based on the image, the system detects landmarks that are associated with objects in the environment and identifies expected landmarks that are expected to be observable from the viewpoint using a landmark database. The system determines that at least one of the expected landmarks is currently unobservable in the environment by comparing the expected landmarks with the detected landmarks. By accessing semantic information associated with the at least one expected landmark, the system updates the landmark database based on a determination that the semantic information satisfies predetermined criteria and removes the at least one expected landmark from the landmark database. The system performs object tracking, object mapping, or re-localization within the environment using the updated landmark database.

Abstract: The disclosed computer-implemented method for offloading image-based tracking operations from a general processing unit to a hardware accelerator unit may include (1) sending imaging data from an imaging device to a hardware accelerator unit, and (2) directing the hardware accelerator unit to generate a multi-scale representation of the imaging data sent from the imaging device, (3) preparing a set of input data for a set of image-based tracking operations, and (4) directing the hardware accelerator unit to execute the set of image-based tracking operations using the generated multi-scale representation of the imaging data and the prepared set of input data. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A wheel suspension system (101) with at least one wheel support (103), first and second coupling rods (105, 107) and at least one track rod (109). The first and second coupling rods (105, 107) are connected to one another in an articulated manner. The second coupling rod (107) and the wheel support (103) are connected to one another in an articulated manner. The track rod (109) is designed to apply a steering torque to the first coupling rod (105). The steering torque is transmitted from the first coupling rod (105), via the second coupling rod (107), to the wheel support (103). The wheel suspension system has at least one suspension link (111) which is mounted, in an articulated manner, on a vehicle body or chassis and is articulated to the wheel support (103). The suspension link (111) and the first coupling rod (105) are articulated to one another.

Abstract: The invention relates to a method for determining the position of a first sensor node relative to a second sensor node, wherein the first and the second sensor nodes are communicatively connected to each other and are a constituent part of a sensor network, comprising the method steps: reception of signal sections of transmitted signals from at least two transmitters by the first and the second sensor node, beginning at a time t1 for a time period tRX; determining the angle of incidence of the transmitted signals to at least one of the sensor nodes; determining the distance between the sensor nodes from the propagation time differences of the transmitted signals from the at least two transmitters received at the first and second sensor nodes; determining the position of the first sensor node relative to the second sensor node from the distance between the sensor nodes and the angle of incidence of the transmitted signals, wherein the sensor nodes determine the time t1 and the time period t1 in relation to a r

Abstract: A wheel suspension system (101) with at least one wheel support (103), first and second coupling rods (105, 107) and at least one track rod (109). The first and second coupling rods (105, 107) are connected to one another in an articulated manner. The second coupling rod (107) and the wheel support (103) are connected to one another in an articulated manner. The track rod (109) is designed to apply a steering torque to the first coupling rod (105). The steering torque is transmitted from the first coupling rod (105), via the second coupling rod (107), to the wheel support (103). The wheel suspension system has at least one suspension link (111) which is mounted, in an articulated manner, on a vehicle body or chassis and is articulated to the wheel support (103). The suspension link (111) and the first coupling rod (105) are articulated to one another.

Abstract: The invention relates to a method for determining the position of a first sensor node relative to a second sensor node, wherein the first and the second sensor nodes are communicatively connected to each other and are a constituent part of a sensor network, comprising the method steps: reception of signal sections of transmitted signals from at least two transmitters by the first and the second sensor node, beginning at a time t1 for a time period tRX; determining the angle of incidence of the transmitted signals to at least one of the sensor nodes; determining the distance between the sensor nodes from the propagation time differences of the transmitted signals from the at least two transmitters received at the first and second sensor nodes; determining the position of the first sensor node relative to the second sensor node from the distance between the sensor nodes and the angle of incidence of the transmitted signals, wherein the sensor nodes determine the time t1 and the time period t1 in relation to a r

Abstract: A device for demultiplexing a packet-based transport stream of transport stream packets each provided with a systematic forward error detection code is described. The transport stream packets are each allocated to one of a plurality of data sinks, so that in a payload data section of the transport stream packets allocated to the same data sink a data stream of forward error protection code-protected data packets which are addressed to the respective data sink is embedded. The device determines, for a transport stream packet which is erroneous according to the systematic forward error detection code, a probability value for each of the plurality of data sinks which indicates how probable it is that the predetermined transport stream packet is allocated to the respective data sink, and allocates the predetermined transport stream packet to a selected one of the plurality of data sinks.

Abstract: Exact data-rate analysis of the information signal portions to be transmitted in a subsequent transmission cycle per time-division multiplexing process shall be initially omitted. Instead, on the basis of highly accurate estimated values for the subsequent data rates, estimated values for relative waiting times are transmitted, in a current transmission cycle, from the current time slice to the subsequent time slice of the same service. In the subsequent transmission cycle, actual data rates may be set which may deviate from the estimated data rates for the individual information signals, as a result of which predicted time-slice boundaries for the subsequent transmission cycle may shift. However, the potential shift in the time-slice boundaries is subject to several boundary conditions. No time slice of the subsequent transmission cycle can start prior to its signaled estimated starting time. With constant data rates, the estimated time-slice structure and the actual time-slice structure are identical.

Abstract: A device for demultiplexing a packet-based transport stream of transport stream packets each provided with a systematic forward error detection code, wherein the transport stream packets are each allocated to one of a plurality of data sinks, so that in a payload data section of the transport stream packets allocated to the same data sink a data stream of forward error protection code-protected data packets is embedded addressed to the respective data sink, the device being implemented to determine, for a predetermined transport stream packet which is erroneous according to the systematic forward error detection code, a probability value for each of the plurality of data sinks which indicates how probable it is that the predetermined transport stream packet is allocated to the respective data sink, and allocate the predetermined transport stream packet, on the basis of the probability values for the plurality of data sinks, to a selected one of the plurality of data sinks.

Abstract: A device for encoding a plurality of information signals using a joint computing power includes a plurality of encoders for encoding a respectively different one of the information signals using the joint computing power, wherein each encoder is controllable via at least one respective encoding parameter with regard to its encoding complexity/encoding distortion performance.

Abstract: Exact data-rate analysis of the information signal portions to be transmitted in a subsequent transmission cycle per time-division multiplexing process shall be initially omitted. Instead, on the basis of highly accurate estimated values for the subsequent data rates, estimated values for relative waiting times are transmitted, in a current transmission cycle, from the current time slice to the subsequent time slice of the same service. In the subsequent transmission cycle, actual data rates may be set which may deviate from the estimated data rates for the individual information signals, as a result of which predicted time-slice boundaries for the subsequent transmission cycle may shift. However, the potential shift in the time-slice boundaries is subject to several boundary conditions. No time slice of the subsequent transmission cycle can start prior to its signaled estimated starting time. With constant data rates, the estimated time-slice structure and the actual time-slice structure are identical.

Abstract: A device for encoding a plurality of information signals using a joint computing power includes a plurality of encoders for encoding a respectively different one of the information signals using the joint computing power, wherein each encoder is controllable via at least one respective encoding parameter with regard to its encoding complexity/encoding distortion performance.