A computer-implemented method for inducing an Out of Body Experience (OBE) in a user through an augmented/virtual reality (ARNR) system, the OBE including an exit state and a disembodiment state, the method comprising the steps of (a) changing the user viewpoint from body-centered viewpoint to distanced viewpoints, thereby inducing an OBE exit state, and (b) showing to the user his/her own body from the distanced viewpoints, thereby inducing an OBE disembodiment state.

A computer-implemented method for inducing an Out of Body Experience (OBE) in a user through an augmented/virtual reality (ARNR) system, the OBE including an exit state and a disembodiment state, the method comprising the steps of (a) changing the user viewpoint from body-centered viewpoint to distanced viewpoints, thereby inducing an OBE exit state, and (b) showing to the user his/her own body from the distanced viewpoints, thereby inducing an OBE disembodiment state.

Techniques for capturing three-dimensional image data of a scene and processing light field image data obtained by an optical wavefront sensor in 3D imaging applications are provided. The disclosed techniques provide a depth map of an observable scene from light field information about an optical wavefront emanating from the scene, and make use of color filters forming a color mosaic defining a primary color and one or more secondary colors, and color radial transfer functions calibrated to provide object distance information from the spatio-spectrally sampled pixel data.

Techniques for capturing three-dimensional image data of a scene and processing light field image data obtained by an optical wavefront sensor in 3D imaging applications are provided. The disclosed techniques provide a depth map of an observable scene from light field information about an optical wavefront emanating from the scene, and make use of color filters forming a color mosaic defining a primary color and one or more secondary colors, and color radial transfer functions calibrated to provide object distance information from the spatio-spectrally sampled pixel data.

A method to efficiently update and manage outputs of real time or offline 3D reconstruction and scanning in a mobile device having limited resource and connection to the Internet is provided. The method makes available to a wide variety of mobile XR applications fresh, accurate and comprehensive 3D reconstruction data, in either single user applications or multi-user applications sharing and updating the same 3D reconstruction data. The method includes a block-based 3D data representation that allows local update and maintains neighbor consistency at the same time, and a multi-layer caching mechanism that retrieves, prefetches, and stores 3D data efficiently for XR applications. Between sessions of an XR device, blocks may be persisted on the device or in remote storage in one or more cache layers. The device may, upon starting a new session, selectively use the blocks from one or more layers of the cache.

A depth processor and a three-dimensional image device. The depth processor comprises at least two input ports, an input switch, a data processing engine and at least one output port. The input port is used for receiving a first image, wherein the first image at least comprises a structured light image collected by a structured light depth camera. The input switch is connected to the output port, and is used for letting some or all of first images that come from the input ports pass. The data processing engine is connected to the input switch, and is used for processing the first image output via the input switch, so as to output a second image, wherein the second image at least comprises a depth image. The output port is connected to the data processing engine, and is used for outputting the second image to a main device.

An optical device may include an emitter array including a plurality of emitter groups. Each emitter group may be independently addressable from other emitter groups, of the plurality of emitter groups, for independently lasing. Emitters of the plurality of emitter groups may be interspersed within the emitter array such that a minimum emitter-to-emitter distance within the emitter array is less than a minimum emitter-to-emitter distance within any of the emitter groups.

Systems and methods for implementing one or more autonomous features for autonomous and semi-autonomous control of one or more vehicles are provided. More specifically, image data may be obtained from an image acquisition device and processed utilizing one or more machine learning models to identify, track, and extract one or more features of the image utilized in decision making processes for providing steering angle and/or acceleration/deceleration input to one or more vehicle controllers. In some instances, techniques may be employed such that the autonomous and semi-autonomous control of a vehicle may change between vehicle follow and lane follow modes. In some instances, at least a portion of the machine learning model may be updated based on one or more conditions.

A depth information calculation method and device based on a light-field-binocular system. The method includes obtaining a far-distance disparity map based on binocular information of calibrated input images, setting respective first confidences pixels in the disparity map, and obtaining a first target confidence; detecting the first confidence of a pixel being smaller than a preset value and responsively determining a new disparity value based on light field information of the input images, determining an update depth value based on the new disparity value, and obtaining a second target confidence of the pixel; and combining the far-distance disparity map and a disparity map formed by the new disparity value on a same unit into an index map, combining the first confidence and the first target confidence into a confidence map, optimizing the index and confidence maps to obtain a final disparity map, which is converted to a final depth map.

A method applied to a camera that includes a visible light sensor, a phase sensor, and a processor. The visible light sensor collects a visible light image of a shooting scene. The phase sensor collects a phase image of the shooting scene. The processor obtains depth information based on the phase image, and superimposes the depth information on the visible light image to obtain a depth image. Optionally, the camera may also include an infrared illuminator that may be turned on when a scene illumination is insufficient to increase an accuracy of the depth information.