Abstract: The present disclosure describes a computer-implemented method for image landmark detection. The method includes receiving an input image for the image landmark detection, generating a feature map for the input image via a convolutional neural network, initializing an initial graph based on the generated feature map, the initial graph representing initial landmarks of the input image, performing a global graph convolution of the initial graph to generate a global graph, where landmarks in the global graph move closer to target locations associated with the input image, and iteratively performing a local graph convolution of the global graph to generate a series of local graphs, where landmarks in the series of local graphs iteratively move further towards the target locations associated with the input image.

Abstract: A registration technique is provided that can combine one or more related registrations to enhance accuracy of a registration of image volumes. A registration relationship between a first source volume and a target volume and a registration relationship between the first source volume and a second source volume are concatenated to provide an estimate of a registration relationship between the second source volume and the target volume. The estimate is utilized to inform the direct registration of the second source volume to the target volume or utilized in place of the direct registration.

Abstract: A method for aligning image frames, includes: obtaining a plurality of original image frames, the plurality of original image frames including a reference image frame and a plurality of to-be-aligned image frames; obtaining a brightness image of the reference image frame and a brightness image of each of the to-be-aligned image frames; for each of the to-be-aligned image frames, obtaining at least one mapping model between the reference image frame and the to-be-aligned image frame based on the brightness image of the reference image frame and the brightness image of the to-be-aligned image frame; and aligning the to-be-aligned image frame with the reference image frame based on the at least one mapping model.

Abstract: A method for large scene elastic semantic representation and self-supervised light field reconstruction is provided. The method includes acquiring a first depth map set corresponding to a target scene, in which the first depth map set includes a first depth map corresponding to at least one 5 angle of view; inputting the first depth map set into a target elastic semantic reconstruction model to obtain a second depth map set, in which the second depth map set includes a second depth map corresponding to the at least one angle of view; and fusing the second depth map corresponding to the at least one angle of view to obtain a target scene point cloud corresponding to the target scene.

Abstract: Apparatus for optical sensing includes an illumination assembly, which directs first optical radiation toward a target scene over a first range of angles and second optical radiation over at least one second range of angles, which is smaller than and contained within the first range, while modulating the optical radiation with a carrier wave having at least one predetermined carrier frequency. A detection assembly includes an array of sensing elements, which output respective signals in response to the first and the second optical radiation. Processing circuitry drives the illumination assembly to direct the first and the second optical radiation toward the target scene in alternation, and processes the signals output by the sensing elements in response to the first optical radiation in order to compute depth coordinates of points in the target scene, while correcting the computed depth coordinates in response to the second optical radiation.

Abstract: The multi-line laser three-dimensional imaging method and system is based on a random lattice. A multi-line laser is used and combined with a rotating mechanism to realize a large-view-field rapid scanning effect, such that the working efficiency is improved by orders of magnitude, and the deployment difficulty of the system is reduced. Due to the fact that within an imaging range, pattern features of the random lattice of each local area have uniqueness, a plurality of laser lines are extracted, position sequence numbers are distinguished, and noise points are reduced through mutual verification of the pattern features of the random lattice between adjacent images, such that the quality of three-dimensional point cloud data is greatly improved. The method and the system can be applied to industrial applications, such as disorderly grabbing, feeding and discharging, unstacking and stacking, logistics sorting and the like.

Abstract: A method for generating simulated point cloud data, a device, and a storage medium includes: acquiring at least one frame of point cloud data collected by a road collecting device in an actual environment without a dynamic obstacle as static scene point cloud data; setting, least one dynamic obstacle in a coordinate system matching the static scene point cloud data; simulating in the coordinate system, a plurality of simulated scanning lights emitted by a virtual scanner located at an origin of the coordinate system; updating the static scene point cloud data according to intersections of the plurality of simulated scanning lights and the at least one dynamic obstacle to obtain the simulated point cloud data comprising point cloud data of the dynamic obstacle; and at least one of adding a set noise to the simulated point cloud data, and, deleting point cloud data corresponding to the dynamic obstacle according to a set ratio.

Abstract: A dishwasher includes: a tub, a sump disposed in the tub, a rack disposed in the sump and receiving an object, a plurality of lighting devices disposed at the tub and configured to illuminate an upper end portion of the rack, a measuring camera disposed at the tub and capturing an image of the upper end portion of the rack and generating an object image, and a controller configured to perform a first lighting control on the lighting devices, acquiring a first object image generated based on a first image of the rack captured by the measuring camera, performing a second lighting control on the lighting devices, acquiring a second object image generated based on a second image of the upper end portion of the rack captured by the object measuring camera, and generating a three-dimensional shape image of the object based on the first and second object images.

Abstract: A system for measuring total operating deflection shapes of a structure includes one or more imagers, each including two cameras spaced apart from one another and each oriented and positioned to have corresponding fields of view of a different corresponding section of the structure, with the corresponding sections that may include overlap area of the structure within each of the different sections of the structure. Each of the cameras generates a corresponding data stream, which is communicated to a controller, which is configured to measure the response of the structure to an excitation, such as a vibration or an impulse. The system is configured to convert time-domain data from each of the data streams to the frequency-domain data using a Fourier Transform algorithm and stitching the shapes to obtain the total operating deflection shapes of the structure by scaling and stitching together the frequency-domain data.

Abstract: Various implementations disclosed herein include devices, systems, and methods that determines a distance between a portion (e.g., top) of a person's head and the floor below as an estimate of the person's height. For example, an example process may include determining a first position on a head of a person in a three-dimensional (3D) coordinate system, the first position determined based on detecting a feature on the head based on a two-dimensional (2D) image of the person in a physical environment, determining a second position on a floor below the first position in the 3D coordinate system, and estimating a height based on determining a distance between the first position and the second position.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generate floorplans and measurements using a three-dimensional (3D) representation of a physical environment generated based on sensor data.

Abstract: Various implementations disclosed herein include devices, systems, and methods that provide measurements of objects based on a location of a surface of the objects. An exemplary process may include obtaining a three-dimensional (3D) representation of a physical environment that was generated based on depth data and light intensity image data, generating a 3D bounding box corresponding to an object in the physical environment based on the 3D representation, determining a class of the object based on the 3D semantic data, determining a location of a surface of the object based on the class of the object, the location determined by identifying a plane within the 3D bounding box having semantics in the 3D semantic data satisfying surface criteria for the object, and providing a measurement of the object, the measurement of the object determined based on the location of the surface of the object.

Abstract: In one embodiment, a method includes receiving an image generated by a camera associated with a vehicle. The image includes a point of interest (POI) associated with a physical object. The method also includes determining a number of pixels from the POI of the image to an edge of the image. The edge of the image represents a location of the camera. The method further includes determining an offset distance from the POI to a Global Positioning System (GPS) unit associated with the vehicle using the number of pixels.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing at least one program, and a method for performing operations comprising: receiving a video that depicts a person. The operations further include identifying a set of skeletal joints of the person. The operations further include identifying a pose of the person depicted in the video based on positioning of the set of skeletal joints (or detecting a hand pose, detecting a mirror frame, or detecting a mobile device). The operations further include determining, based on the pose of the person (or detecting a hand pose, detecting a mirror frame, or detecting a mobile device), that the video comprises a mirror reflection of the person. The operations further include, in response to determining that the video comprises the mirror reflection of the person, causing display of a 3D virtual object in the video.

Abstract: There is provided a parcel recognition device that recognizes a parcel based on a color image including the parcel, the device including: a processor; and a memory, in which by cooperating with the memory, the processor subtracts a color of a projection image from a color of an image projection surface of the parcel on which the projection image is projected, in the color image, and sets a color obtained by the subtraction as a color of a recognition target, and recognizes the parcel.

Abstract: The disclosure relates to methods and systems for detecting the orientation of an oocyte and its polar body. Examples include an automated method for detection of an orientation of an oocyte, the method including: i) acquiring an image of the oocyte; ii) defining first and second elliptical features in the image based on edges detected in the image; iii) calculating an orientation of the second elliptical feature relative to the first elliptical feature; and iv) outputting a relative orientation of a polar body of the oocyte based on the orientation of the second elliptical feature relative to the first elliptical feature.

Abstract: An exemplary aspect is a location estimation system, including: a feature value extraction processing unit that performs feature value extraction processing for extracting a feature value from an input image; and a location estimation processing unit that compares the extracted feature value with map information and performs location estimation processing for estimating a self-location based on a result of the comparison. While the location estimation processing unit is performing the location estimation processing corresponding to an input image input at a predetermined timing, the feature value extraction processing unit performs the feature value extraction processing on an input image input at a timing after the predetermined timing.

Abstract: The present invention discloses deep learning based robot target recognition and motion detection methods, storage media and devices, the method consists of the following steps: Step S1. adding masks to regions where potentially dynamic objects are located through instance segmentation networks incorporating attention mechanisms and positional coding; Step S2, estimation of the camera pose using static feature points outside the instance segmentation mask in the scene; Step S3, estimation of the object pose transformation matrix from the camera pose; Step S4, determining the state of motion of the object's characteristic points from the relationship between motion parallax and differential entropy, and thus the state of motion of the object as a whole; Step S5, rejects the dynamic objects therein and repairs the static background of the rejected area for positional estimation and map construction.

Abstract: A machine-vision vehicle service system, and methods of operation, incorporating at least one gimbaled sensor module configured with at least an optical range finder to acquire measurements associated with physical floor surfaces in proximity to a vehicle undergoing service for guiding corrected placement of ADAS target components relative to an established vehicle floor plane.

Abstract: A method for an image capturing device includes: acquiring a first image of a target object; extracting coordinate information of a first 2D key point corresponding to the target object; acquiring a second image of the target object; acquiring coordinate information of a second 2D key point in the second image according to the coordinate information of the first 2D key point, the first 2D key point and the second 2D key point being the same key point in the target object; acquiring coordinate information of a 3D key point corresponding to the target object, the 3D key point being a key point obtained after a triangulation operation; and determining camera posture information of the second image according to the coordinate information of the first 2D key point, the coordinate information of the second 2D key point, the coordinate information of the 3D key point, and a 3D-2D projection.

Abstract: Systems and methods for determining a geographic location of an environment from an image including an annotation on a mobile device without GPS, with no network access, and with no access to peripheral devices or media is described. Open source data indicative of the earth's surface may be obtained and combined into grids or regions. Elevation data may be used to create skyline models at grid points on the surface. An image of an environment may be obtained from a camera on a mobile device. The user of the mobile device may trace a skyline of the environment depicted in the image. The annotation may be used to create reduced regions for edge detection analysis. The edge detection analysis may detect the skyline. The detected skyline may be compared to the skyline models to determine a most likely location of the user.

Abstract: Body and hand correlation method, apparatus, device, storage medium and computer program are provided. Method includes: in an image of which an image content includes a body to be correlated and a hand to be correlated, a first correlation probability between a body detection box of the body and a hand detection box of the hand is determined; a second correlation probability between the body and a wrist key point in a key point is determined based on the key point in the body detection box, the key point including the wrist key point and elbow key point belonging to the same arm; a third correlation probability between the hand detection box and the wrist key point is determined based on the wrist key point and elbow key point; and a correlation degree between the body and the hand is determined based on the first, second, and third correlation probabilities.

Abstract: Method of aligning an imaging device with respect to an object, the imaging device comprising two or more optical channels, is disclosed. The method may include aiming the two or more optical channels at corresponding overlapping zones of the object such that the two or more optical channels are oriented at different angles relative to each other and off-axis relative to a central axis of the imaging device. The method may additionally include guiding or focusing the imaging device relative to the object using composite images created by combining separate images from the two or more optical channels.

Abstract: A 3D measuring instrument includes a registration camera and a surface measuring system having a projector and autofocus camera. In a first pose, the registration camera captures a first registration image of first registration points. The autofocus camera captures a first surface image of first light projected onto the object by the projector and determines first 3D coordinates of points on the object. In a second pose, the registration camera captures a second registration image of second registration points. The autofocus camera adjusts the autofocus mechanism based at least in part on adjusting a focal length to reduce a difference between positions of the first and second registration points. A second surface image of second light is captured. A compensation parameter is determined based at least in part on the first registration image, the second registration image, the first 3D coordinates, the second surface image, and the projected second light.

Abstract: In some embodiments, a method includes receiving a first image and a second image from a stereo camera pair. The method includes selecting a first row of pixels from the rectified image and a set of rows of pixels from the second image and comparing the first row of pixels with each row of pixels from the set of rows of pixels to determine disparity values. The method includes determining a pair of rows of pixels having the first row of pixels and a second row of pixels from the set of rows of pixels. The pair of rows of pixels has an offset no greater than an offset between the first row of pixels and each row of pixels from remaining rows of pixels. The method includes adjusting, based on the offset, the relative rotational position between the first stereo camera and the second stereo camera.

Abstract: A method of obtaining a tree-based point cloud compression (PCC) media stream using moving picture experts group (MPEG)-dynamic adaptive streaming over http (DASH), is performed by at least one processor and includes obtaining, from a server, a media representation description (MPD) comprising a PCC uniform resource indicator (URI) and a PCC three-dimensional (3D) descriptor, and determining whether the PCC URI comprised in the obtained MPD indicates that the tree-based PCC media stream is to be accessed. The method further includes, based on the PCC URI being determined to indicate that the tree-based PCC media stream is to be accessed, obtaining, from the server, the tree-based PCC media stream, using the PCC 3D descriptor comprised in the obtained MPD.

Abstract: A mobile surveillance apparatus includes: a communication interface configured to receive map data of a preset area; and a processor configured to process the map data by reflecting at least one of unevenness and obstruction on a driving surface of a mobile module, and set a path for the mobile module, based on the processed map data.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and efficiently modifying a generative adversarial neural network using few-shot adaptation to generate digital images corresponding to a target domain while maintaining diversity of a source domain and realism of the target domain. In particular, the disclosed systems utilize a generative adversarial neural network with parameters learned from a large source domain. The disclosed systems preserve relative similarities and differences between digital images in the source domain using a cross-domain distance consistency loss. In addition, the disclosed systems utilize an anchor-based strategy to encourage different levels or measures of realism over digital images generated from latent vectors in different regions of a latent space.

Abstract: The present disclosure describes techniques for social networking based on trading asset items. The techniques comprise sending a request by a first client computing device for connecting with a second client computing device, displaying a first video comprising a first user and a second video comprising a second user on an interface, determining a first body part of the first user based on a selection of a representative of a first asset item associated with the second user, determining a position of rendering an image of the first asset item on the interface, rendering the image of the first asset item and combining the image into the first video for display of an effect of the first asset item being tried on the first body part of the first user, and receiving the first asset item from the second user based on the effect and user input.

Abstract: A method for generating a dataset is provided. The method includes generating, within a simulated environment, a simulated image including one or more distortions, the simulated image includes a plurality of vehicles, generating vehicle image patches and ground truth from the simulated image, performing, using a style transfer module, a style-transfer operation on the vehicle image patches, combining the vehicle image patches, on which the style-transfer operation is performed, with a background image of a real-world location, and generating a dataset based on the ground truth and the combination of the vehicle image patches and the background image.

Abstract: A system for imaging reconstruction is provided. The system may obtain a first set of image data of a subject acquired by a scanner and a second set of image data of the subject acquired by the scanner. The first set of image data may correspond to a first angle range of the scanner. The second set of image data may correspond to a second angle range of the scanner. The first angle range may be different from the second angle range. The system may also generate a first image based on the first set of image data and generate a second image based on the second set of image data. The system may further generate a target image based on the first image and the second image.

Abstract: Systems, methods, and devices for generating a corrected image are provided. A first robotic arm may be configured to orient a source at a first pose and a second robotic arm may be configured to orient a detector at a plurality of second poses. An image dataset may be received from the detector at each of the plurality of second poses to yield a plurality of image datasets. The plurality of datasets may comprise an initial image having a scatter effect. The plurality of image datasets may be saved. A scatter correction may be determined and configured to correct the scatter effect. The correction may be applied to the initial image to correct the scatter effect.

Abstract: The present disclosure provides a photoacoustic image reconstruction method for suppressing artifacts, including: acquiring relevant parameters of the system; selecting a suitable pixel size and dividing the imaging area into multiple pixels; traversing each pixel, calculating multiple delay and summations according to the time sequence, and restoring the signal waveform; calculating the signal envelope of the signal recovered from each pixel, performing signal suppression, suppressing artifacts in the signal, and retaining real signal; the real signal value in the suppressed signal is taken as the gray value of the pixel in the image, and is saved in the picture to complete the reconstruction of the image.

Abstract: A processor acquires at least one radiographic image of a subject including a plurality of compositions and acquires a composition ratio of the subject. The processor sets an attenuation coefficient of radiation used in a case in which the radiographic image is acquired for each pixel of the radiographic image according to the composition ratio. The processor performs image processing on the radiographic image using the set attenuation coefficient.

Abstract: A deep-learning-based method for metal artifact reduction in CT images includes providing a dataset and a cGAN. The dataset includes CT image pairs, randomly partitioned into a training set, a validation set, and a testing set. Each Pre-CT and Post-CT image pairs is respectively acquired in a region before and after an implant is implanted. The Pre-CT and Post-CT images of each pair are artifact-free CT and artifact-affected CT images, respectively. The cGAN is conditioned on the Post-CT images, includes a generator and a discriminator that operably compete with each other, and is characterized with a training objective that is a sum of an adversarial loss and a reconstruction loss. The method also includes training the cGAN with the dataset; inputting the post-operatively acquired CT image to the trained cGAN; and generating an artifact-corrected image by the trained cGAN, where metal artifacts are removed in the artifact-corrected image.

Abstract: A method for composing context images with user media captures contemplates selecting, at a first location, a context image associated with the first location to incorporate into captured images at a second location. The method further contemplates that the selected context images and user media captures specific to the first location are combined to create a composite image at the second location.

Abstract: An electronic price tag display method and an electronic price tag display system, a server and a computer readable storage medium. The method is applied to the server, and includes: obtaining basic information of data to be displayed in an image; converting the basic information into bitmap data; and delivering the bitmap data to an electronic price tag in order that the electronic price tag displays the content of the data to be displayed. By implementing the method, the process of manually editing bitmap data by the user is abandoned, the manpower resource and the time cost are saved, the efficiency of display control of the electronic price tag is improved, and the condition that the editing result is affected by human operation error is avoided simultaneously.

Abstract: Described herein is a computer implemented method. The method includes detecting user input activating a text effect selection control. In response to the user input the method further includes: automatically generating a first shadow for a selected design element, the first shadow having a first colour, a first direction, a first offset, and a first opacity; automatically generating a second shadow for the selected design element, the second shadow having the first colour, the first direction, a second offset greater than the first offset, and a second opacity less than the first opacity; displaying the first shadow behind the selected design element; and displaying the second shadow behind the first shadow.

Abstract: The present disclosure relates to an AR animation generation system that detects a change in position of a mobile computing system in a real-world environment, determines that a position for a virtual object in an augmented reality (AR) scene is to be changed from a first position in the AR scene to a second position in the AR scene, identifies an animation profile to be used for animating the virtual object, wherein the animation profile is associated with the virtual object, and animates the virtual object in the AR scene using the animation profile. Animating the virtual object in the AR scene includes moving the virtual object in the AR scene from the first position to the second position along a path, wherein the path and a movement of the virtual object along the path are determined based on the animation profile.

Abstract: Methods, systems, and apparatus including: first attaching ink lines drawn directly onto characters of the CG animation; first enabling the artist to modify the ink lines using nudges to generate a drawing; first moving the drawing into a UV space and generating first pass training data; second attaching the ink lines onto the characters of the CG animation; second enabling the artist to modify the ink lines; second moving the drawing into the UV space and generating second pass training data; combining the first pass training data and the second pass training data to generate combined data; and creating and outputting a second generation machine learning using the combined data.

Abstract: Computer animation involving pose disambiguation is disclosed. Two or more source segmentation masks are generated from corresponding contemporaneous video images of a character from different points of view. A three-dimensional model of an animation character corresponding to the character in the two or more contemporaneous video images is generated. Two or more different target segmentation masks corresponding to different views of the animation character corresponding to the character in the two or more video images. Each target segmentation mask is compared to a corresponding source segmentation mask from the comparison it is determined whether a pose of the three-dimensional model corresponds to a pose of the character in the video images. The model is used to generate a frame of animation of the animated character when the pose of model corresponds to the pose of the character in the video images.

Abstract: A method for calibrating an animation includes obtaining a static source image of a source face; capturing, by an image capturing device, a driving video of a human; determining whether a driving face, of the human, is present in each of the video frames; measuring a driving face position and a driving face size in a calibration reference frame of the driving video; generating each of one or more modified video frames based on the calibration reference frame and each of one or more subsequent video frames; and outputting, for each of the driving video frames, the source image in response to determining that the driving face is not present, and outputting the source image and the modified video frame in response to determining that the driving face is present.

Abstract: Real-time animation of a virtual character can be provided by pre-calculating a control policy that identifies a suitable animation clip to animate the next movement of the virtual character. The control policy can be calculated using a Markov decision process (MDP) and can specify an action to take (e.g., a movement) when the virtual character is in a particular state (e.g., in a particular position or pose). The control policy can be determined based on a discounted set of rewards or punishments associated with various actions that can occur in each state. The control policies can be pre-calculated, offline from a runtime animation engine (e.g., in an augmented reality display). The runtime animation engine can use the control policies to select an animation clip to move the virtual character through an environment in real time.

Abstract: The present disclosure provides a method and apparatus of displaying an image, an electronic device and a storage medium. The method includes: obtaining a preset number of candidate sub-images by segmenting a to-be-displayed first candidate image; assigning each of the candidate sub-images to a corresponding first image sub-template in a preset first image template sequentially, where a number of the first image sub-templates is equal to a number of the candidate sub-images; adjusting each of the first image sub-templates in the first image template such that the first candidate image displays a preset animation effect, where the preset animation effect is obtained from configuration information of an electronic device.

Abstract: A method, user device, and a printing device for manufacturing one or more customized products are provided. The method involves capturing one or more three-dimensional (3-D) images of one or more objects, transmitting the captured one or more 3D images to a printing device, converting the transmitted one or more 3D images into a predefined format; wherein the predefined format is a format read by the printing device. The method further comprises printing the converted one or more 3D images using the printing device to create one or more 3D objects, wherein the one or more 3D objects are a replica of the one or more objects in the one or more captured 3D images, and manufacturing one or more customized products using the created one or more 3D objects.

Abstract: A method and system for dynamically transferring graphical image processing operations from a graphical processing unit (GPU) to a digital signal processor (DSP). The method includes estimating the number of operations needed for the processing a set of image data; determining the operational limits of a GPU and compare with estimated number of operations and if the operational limits are exceeded; transfer the processing operations to the DSP from the GPU. The transfer can include transferring a portion of executable code for performing the processing operations, and generating a replacement code for the GPU. The DSP can then process a portion of the image data before sending it to the GPU for further processing.

Abstract: An example method of hardware-assisted graphics pipeline emulation comprises: computing, based on an input set of graphic primitives, a set of tessellation factors; computing, based on the input set of graphic primitives, a set of points specifying a plurality of patches; computing, based on the set of points, a tessellation count buffer; generating, based on the set of points and the tessellation count buffer, a tessellation offset buffer; performing, using the tessellation offset buffer, a tessellation setup stage; performing, by a graphics processing unit (GPU), a tessellation stage based on the set of tessellation factors, wherein the tessellation stage generates a plurality of output points corresponding to one or more patches of the plurality of patches; and computing, by a domain shader stage, a plurality of vertex positions defined by the plurality of output points.

Abstract: One embodiment provides a graphics processor comprising a hardware graphics rendering pipeline configured to perform multisample anti-aliasing, the hardware graphics rendering pipeline including pixel processing logic to determine that each sample location of a pixel of a multisample surface is associated with a clear value and resolve a color value for the pixel to a non-multisample surface via a write of metadata to indicate that the pixel has the clear value. The resolve can be a stenciled resolve that automatically bypasses execution of a pixel shader for pixels having clear color data.

Abstract: The invention provides, in some aspects, a system for implementing a rule derived basis to display image sets. In various embodiments of the invention, the selection of the images to be displayed, the layout of the images, as well as the rendering parameters and styles can be determined using a rule derived basis. The rules are based on meta data of the examination as well as image content that is being analyzed by neuronal networks. In an embodiment of the present invention, the user is presented with images displayed based on their preferences without having to first manually adjust parameters.

Abstract: In some implementations, a method of generating a third person view of a computer-generated reality (CGR) environment is performed at a device including non-transitory memory and one or more processors coupled with the non-transitory memory. The method includes: obtaining a first viewing vector associated with a first user within a CGR environment; determining a first viewing frustum for the first user within the CGR environment based on the first viewing vector associated with the first user and one or more depth attributes; generating a representation of the first viewing frustum; and displaying, via the display device, a third person view of the CGR environment including an avatar of the first user and the representation of the first viewing frustum adjacent to the avatar of the first user.