Aquifi, Inc.

Hover, Inc.

Packsize LLC

Imimtek, Inc.

Packsize International, LLC

Giridhar Murali

Carlo Dal Mutto

Giuliano Pasqualotto

William Castillo

Kinh Tieu

Britta Silke Hummel

Brandon Scott

Michele Stoppa

Francesco Peruch

Jeffrey Sommers

Abbas Rafii

Giulio Marin

Matthew Thomas

Amir Hossein Khalili

Manish Upendran

Dario Rethage

Alvise Memo

Ethan Cheng

Teresa Mao

Kai Jia

David Royston Cutts

Ahmed Tashrif Kamal

Francisco Avila-Beltran

Yunwen Zhou

Keith Blackstone

Jena Dzitsiuk

Domenico Curro

Atulya Shree

Panfeng Li

Alrik Firl

Jonathan Mark Igner

Disclosed are techniques for enhancing two-dimensional (2D) image capture of subjects (e.g., a physical structure, such as a residential building) to maximize the feature correspondences available for three-dimensional (3D) model reconstruction. More specifically, disclosed is a computer-vision network configured to provide viewfinder interfaces and analyses to guide the improved capture of an intended subject for specified purposes. Additionally, the computer-vision network can be configured to generate a metric representing a quality of feature correspondences between images of a complete set of images used for reconstructing a 3D model of a physical structure. The computer-vision network can also be configured to generate feedback at or before image capture time to guide improvements to the quality of feature correspondences between a pair of images.

Techniques for enhanced image capture using a computer-vision network

Disclosed are techniques for generating a photorealistic image by augmenting or compositing at least a portion of a physical structure (e.g., a house) depicted in a two-dimensional (2D) image with synthetic image data. Additionally, disclosed are techniques for augmenting the depicted physical structure and applying a scene effect to the synthetic image data to create a photorealistic effect.

Systems and methods for selective image compositing

Systems and methods are provided for pitch determination. An example method includes obtaining an image depicting a structure, the image being captured via a user device positioned proximate to the structure. The image is segmented to identify, at least, a roof facet of the structure. An eave vector and a rake vector which are associated with the roof facet are determined. A normal vector of the roof facet is calculated based on the eave vector and the rake vector, and compared to a vector indicating a vertical direction such as gravity. The angle made out by the normal and a gravity vector may be utilized to calculate the pitch of the roof facet.

Systems and methods for pitch determination

A method for computing dimensions of an object in a scene includes: controlling, by a processor, a depth camera system to capture at least a frame of the scene, the frame including a color image and a depth image arranged in a plurality of pixels; detecting, by the processor, an object in the frame; determining, by the processor, a ground plane in the frame, the object resting on the ground plane; computing, by the processor, a rectangular outline bounding a projection of a plurality of pixels of the object onto the ground plane; computing, by the processor, a height of the object above the ground plane; and outputting, by the processor, computed dimensions of the object in accordance with a length and a width of the rectangular outline and the height.

Systems and methods for volumetric sizing

System and method are provided for scaling a 3-D representation of a building structure. The method includes obtaining world map data including a first track of real-world poses for a plurality of images. The plurality of images comprises non-camera anchors. The method also includes detecting a discrepancy in at least one real-world pose of the first track. The method also includes in response to detecting a discrepancy, generating a new track of real-world poses. The method also includes calculating a scaling factor for a 3-D representation of the building structure based on sampling across a plurality of tracks. The plurality of tracks comprises at least the first track and the new track.

3-D reconstruction using augmented reality frameworks

A method for generating a three-dimensional (3D) model of an object includes: capturing images of the object from a plurality of viewpoints, the images including color images; generating a 3D model of the object from the images, the 3D model including a plurality of planar patches; for each patch of the planar patches: mapping image regions of the images to the patch, each image region including at least one color vector; and computing, for each patch, at least one minimal color vector among the color vectors of the image regions mapped to the patch; generating a diffuse component of a bidirectional reflectance distribution function (BRDF) for each patch of planar patches of the 3D model in accordance with the at least one minimal color vector computed for each patch; and outputting the 3D model with the BRDF for each patch.

System and method for three-dimensional scanning and for capturing a bidirectional reflectance distribution function

Disclosed are techniques for generating a photorealistic image by augmenting or compositing at least a portion of a physical structure (e.g., a house) depicted in a two-dimensional (2D) image with synthetic image data. Additionally, disclosed are techniques for augmenting the depicted physical structure using a minimum amount of three-dimensional (3D) geometric data and applying a scene effect to the synthetic image data to create a photorealistic effect.

A method for computing a three-dimensional (3D) model of an object includes: receiving, by a processor, a first chunk including a 3D model of a first portion of the object, the first chunk being generated from a plurality of depth images of the first portion of the object; receiving, by the processor, a second chunk including a 3D model of a second portion the object, the second chunk being generated from a plurality of depth images of the second portion of the object; computing, by the processor, a registration of the first chunk with the second chunk, the registration corresponding to a transformation aligning corresponding portions of the first and second chunks; aligning, by the processor, the first chunk with the second chunk in accordance with the registration; and outputting, by the processor, a 3D model corresponding to the first chunk merged with the second chunk.

Systems and methods for scanning three-dimensional objects

A three-dimensional scanning system includes: a camera configured to capture images; a processor; and memory coupled to the camera and the processor, the memory being configured to store: the images captured by the camera; and instructions that, when executed by the processor, cause the processor to: control the camera to capture one or more initial images of a subject from a first pose of the camera; compute a guidance map in accordance with the one or more initial images to identify one or more next poses; control the camera to capture one or more additional images from at least one of the one or more next poses; update the guidance map in accordance with the one or more additional images; and output the images captured by the camera to generate a three-dimensional model.

System and method for assisted 3D scanning

Growing community of inventors

Sunnyvale, CA, United States of America

Giridhar Murali