An augmented reality display system comprises a passable world model data comprises a set of map points corresponding to one or more objects of the real world. The augmented reality system also comprises a processor to communicate with one or more individual augmented reality display systems to pass a portion of the passable world model data to the one or more individual augmented reality display systems, wherein the piece of the passable world model data is passed based at least in part on respective locations corresponding to the one or more individual augmented reality display systems.

Treatment trajectory guidance systems and methods are provided. In one embodiment, the method for treatment trajectory guidance in a patient's brain includes obtaining a three- dimensional (3D) brain model that includes a model of an anatomy, the model of the anatomy including a plurality of feature points; modifying the 3D brain model based on magnetic resonance (MR) data of the patient's brain from a magnetic resonance imaging (MRI) device to obtain a plurality of modified feature points on a modified model of the patient's anatomy in the patient's brain; displaying on a display a first planned trajectory for treating the patient's anatomy based on the plurality of modified feature points; and displaying, on the display, a first estimated treatment result for the first planned trajectory.

Methods relating generally to textured printing are disclosed. In a method, at least one object or object outline in an image is identified using an artificial intelligence engine. A sub image is generated for the at least one object or object outline. The image and the sub image are processed to convert into image information and associated position information for the sub image in relation to the image for textured printing. The image information and the position information are stored in a memory for the textured printing.

A system configured to facilitate virtual outfit fitting is described. The system includes a smart closet device having components including a display door and a plurality of image sensors. A first image sensor of the plurality of image sensors is configured to move across a horizontal axis and a vertical axis of enclosure of the smart closet device to capture a plurality of images of a first outfit hung on an outfit hanging column. The smart closet device also includes a computing unit to generate a three-dimensional (3D) model of the first outfit based on the plurality of images. The computing unit is further configured to update an outfit database by storing the generated 3D model of the first outfit in an outfit database. The computing unit generate an image of a user wearing the output in response to receiving a selection of the first output from the user.

The present disclosure provides a visual perception method and apparatus, a perception network training method and apparatus, a device and a storage medium. The visual perception method recognizes the acquired image to be perceived with a perception network to determine a perceived target and a pose of the perceived target, and finally determines a control command according to a preset control algorithm and the pose, so as to enable an object to be controlled to determine a processing strategy for the perceived target according to the control command. According to the perception network training method, acquire image data and model data, then generate an edited image with a preset editing algorithm according to a 2D image and a 3D model, and finally train the perception network to be trained according to the edited image and the label.

In various examples there is an apparatus for computing an image depicting a face of a wearer of a head mounted display (HMD), as if the wearer was not wearing the HMD. An input image depicts a partial view of the wearer's face captured from at least one face facing capture device in the HMD. A machine learning apparatus is available which has been trained to compute expression parameters from the input image. A 3D face model that has expressions parameters is accessible as well as a photorealiser being a machine learning model trained to map images rendered from the 3D face model to photorealistic images. The apparatus computes expression parameter values from the image using the machine learning apparatus. The apparatus drives the 3D face model with the expression parameter values to produce a 3D model of the face of the wearer and then renders the 3D model from a specified viewpoint to compute a rendered image. The rendered image is upgraded to a photorealistic image using the photorealiser.

A method generating a more accurate 3D model for at least two gemstones using external surface of the gemstones; storing, in memory, the more accurate 3D model of the first gemstone and the second gemstone; comparing the more accurate 3D model of the first gemstone and the more accurate 3D model of the second gemstone from the stored memory; calculating, based on the comparison, a matching score for the more accurate 3D model of the first gemstone and the more accurate 3D model of the second gemstone, the matching score being informative of a match between the first gemstone and the second gemstone; and identifying the first gemstone and the second gemstone as being the same gemstone when the matching score meets a predefined matching criterion.

An object tracking system includes a first sensor, a second sensor, and a tracking system. The first sensor is configured to capture a first frame of a global plane for at least a first portion of a space. The second sensor is configured to capture a second frame of at least a second portion of the space. The tracking system is configured to determine the object is within an overlap region with the second sensor based on a first pixel location. The tracking system is further configured to determine a first coordinate in the global plane for the object, to determine a second pixel location in the second frame for the object based on the first coordinate, and to store the second pixel location with an object identifier a tracking list associated with the second sensor.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using surfels for vehicle localization. One of the methods includes obtaining surfel data comprising a plurality of surfels, wherein each surfel corresponds to a respective different location in an environment, and each surfel has associated data that comprises a stability measure, wherein the stability measure characterizes a permanence of a surface represented by the surfel; obtaining sensor data for a plurality of locations in the environment, the sensor data having been captured by one or more sensors of a first vehicle; determining a plurality of high-stability surfels from the plurality of surfels in the surfel data; and determining a location in the environment of the first vehicle using the plurality of selected high-stability surfels and the sensor data.

An intelligent assistant records speech spoken by a first user and determines a self-selection score for the first user. The intelligent assistant sends the self-selection score to another intelligent assistant, and receives a remote-selection score for the first user from the other intelligent assistant. The intelligent assistant compares the self-selection score to the remote-selection score. If the self-selection score is greater than the remote-selection score, the intelligent assistant responds to the first user and blocks subsequent responses to all other users until a disengagement metric of the first user exceeds a blocking threshold. If the self-selection score is less than the remote-selection score, the intelligent assistant does not respond to the first user.