Qualcomm Incorporated

James Wilson Nash

Kalin Mitkov Atanassov

Sergiu Radu Goma

Hasib Siddiqui

Albrecht Johannes Lindner

Vikas Ramachandra

Stephen Michael Verrall

Venkata Ravi Kiran Dayana

Narayana Karthik Sadanandam Ravirala

Evgeni Petrovich Gousev

Russell Wayne Gruhlke

Khurshid Syed Alam

John Michael Wyrwas

Karthikeyan Shanmugavadivelu

Magdi Mohamed

Adarsh Abhay Golikeri

Sami Khawam

Ioannis Nousias

Robert Mitchell Kleiman

Shandon Campbell

Mark Ian Roy Muir

Jason Chung

Hasib Ahmed Siddiqui

Systems and techniques are provided for wireless communication. For example, a process can include obtaining a first image of an environment, the first image including a pattern of light. The process can further include determining a pixel window for a pixel of the first image; determining a set of transform pixels based on the pattern of light, wherein the set of transform pixels are a subset of pixels from the pixel window; performing a census transform based on the pixel and the set of transform pixels to obtain census transform information for the first image; and generating depth data based on the census transform information for the first image and census transform information for a second image.

Stereo vision with census transform

A method performed by an electronic device is described. The method includes obtaining a first image from a first camera, the first camera having a first focal length and a first field of view. The method also includes obtaining a second image from a second camera, the second camera having a second focal length and a second field of view disposed within the first field of view. The method further includes aligning at least a portion of the first image and at least a portion of the second image to produce aligned images. The method additionally includes fusing the aligned images based on a diffusion kernel to produce a fused image. The diffusion kernel indicates a threshold level over a gray level range. The method also includes outputting the fused image. The method may be performed for each of a plurality of frames of a video feed.

Systems and methods for fusing images

Aspects of the present disclosure relate to systems and methods for active depth sensing. An example apparatus configured to perform active depth sensing includes a projector. The projector is configured to emit a first distribution of light during a first time and emit a second distribution of light different from the first distribution of light during a second time. A set of final depth values of one or more objects in a scene is based on one or more reflections of the first distribution of light and one or more reflections of the second distribution of light. The projector may include a laser array, and the apparatus may be configured to switch between a first plurality of lasers of the laser array to emit light during the first time and a second plurality of laser to emit light during the second time.

Alternating light distributions for active depth sensing

Techniques are disclosed for depth map generation in a structured light system where an optical transmitter is tilted relative to an optical receiver. The optical transmitter has a transmitter optical axis around which structured light spreads, and the optical receiver has a receiver optical axis around which a reflection of the structured light can be captured. The transmitter optical axis and the receiver optical axis intersect one another. A processing circuit compensates for the angle in the tilt in the reflected pattern to generate the depth map.

Depth map generation in structured light system

Aspects relate to processing captured images from structured light systems. An example device may include one or more processors and a memory. The memory may include instructions that, when executed by the one or more processors, cause the device to receive a captured image of a scene from a structured light receiver, analyze one or more first portions of the captured image at a first scale, and analyze one or more second portions of the captured image at a second scale finer than the first scale. The analysis of the one or more second portions may be based on the analysis of the one or more first portions. The instructions further may cause the device to determine for each of the one or more second portions a codeword from a codeword distribution and determine one or more depths in the scene based on the one or more determined codewords.

Multiple scale processing for received structured light

A device for image processing includes an optical receiver configured to receive a reflection of a coded pattern from an object to generate an image, and processing circuitry. The processing circuitry is configured to determine an estimated position of zero order light in the image, determine a spatial region of the coded pattern that corresponds to a position of the zero order light in the coded pattern, map the spatial region to the estimated position of the zero order light in the image to generate a corrected image, and generate a depth map for the coded pattern based on the corrected image.

Zero order light removal in active sensing systems

Aspects of the present disclosure relate to systems and methods for time-of-flight ranging. An example time-of-flight system includes a transmitter including a plurality of light emitters for transmitting focused light, the plurality of light emitters including a first group of light emitters for transmitting focused light with a first field of transmission and a second group of light emitters for transmitting focused light with a second field of transmission. The first field of transmission at a depth from the transmitter is larger than the second field of transmission at the depth from the transmitter. The time-of-flight system also includes a receiver to receive reflections of the transmitted light.

Time of flight ranging with varying fields of emission

Aspects of the present disclosure relate to systems and methods for structured light (SL) depth systems. A depth finding system includes one or more processors and a memory, coupled to the one or more processors, includes instructions that, when executed by the one or more processors, cause the system to capture a plurality of frames based on transmitted pulses of light, where each of the frames is captured by scanning a sensor array after a respective one of the pulses has been transmitted, and generate an image depicting reflections of the transmitted light by combining the plurality of frames, where each of the frames provides a different portion of the image.

Multi-phase active light depth system

Systems, methods, and devices for generating a depth map of a scene are provided. The method comprises projecting, onto the scene, a codeword pattern including a plurality of light points including a first set of light points projected at a first intensity and a second set of light points projected at a second intensity greater than the first intensity. The method further comprises detecting, from the scene, a reflection of the codeword pattern. The method further comprises generating a first depth map layer at a first resolution. The method further comprises generating a second depth map layer at a second resolution lower than the first resolution. The method further comprises generating the depth map of the scene, wherein the depth map includes depth information for the scene according to each of the first depth map layer and the second depth map layer.

Systems and methods for generating a structured light depth map with a non-uniform codeword pattern

A device includes a first camera and a processor configured to detect one or more first keypoints within a first image captured by the first camera at a first time, detect one or more second keypoints within a second image captured by a second camera at the first time, and detect the one or more first keypoints within a third image captured by the first camera at a second time. The processor is configured to determine a pose estimation based on coordinates of the one or more first keypoints of the first image relative to a common coordinate system, coordinates of the one or more second keypoints of the second image relative to the common coordinate system, and coordinates of the one or more first keypoints of the third image relative to the common coordinate system. The first coordinate system is different than the common coordinate system.

Pose estimation using multiple cameras

Systems and method for refining a depth map of a scene based upon a captured image of the scene. A captured depth map of the scene may contain outage areas or other areas of low confidence. The depth map may be aligned with a color image of the scene, and the depth values of the depth map may be adjusted based upon corresponding color values of the color image. An amount of refinement for each depth value of the aligned depth map is based upon the confidence value of the depth value and a smoothing function based upon a corresponding location of the depth value on the color image.

Refinement of structured light depth maps using RGB color data

A method for displaying preview images is disclosed. In one aspect, the method includes: receiving first images captured by a first camera having a first field-of-view (FOV), receiving second images captured by a second camera having a second FOV that is different than the first FOV, and displaying preview images generated based on the first and second images. The method may further include determining a spatial transform based on depth information associated with individual pixels in the first and second images, and upon receiving instructions to zoom in or out beyond a camera switching threshold, modifying the second image using the spatial transform and displaying the first image and the modified second image consecutively.

Depth-based zoom function using multiple cameras

Systems and methods are disclosed for processing spectral imaging (SI) data. A training operation estimates reconstruction matrices based on a spectral mosaic of an SI sensor, generates directionally interpolated maximum a-priori (MAP) estimations of image data based on the estimated reconstruction matrices. The training operation may determine filter coefficients for each of a number of cross-band interpolation filters based at least in part on the MAP estimations, and may determine edge classification factors based at least in part on the determined filter coefficients. The training operation may configure a cross-band interpolation circuit based at least in part on the determined filter coefficients and the determined edge classification factors. The configured cross-band interpolation circuit captures mosaic data using the SI sensor, and recovers full-resolution spectral data from the captured mosaic data.

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San Diego, CA, United States of America

James Wilson Nash