Packsize LLC

Aquifi, Inc.

Francesco Peruch

Carlo Dal Mutto

Kinh Tieu

Giridhar Murali

Abbas Rafii

Giulio Marin

Jason A Trachewsky

Giuliano Pasqualotto

Aryan Hazeghi

Ethan Cheng

Michele Stoppa

Tony Zuccarino

Robert Hayes

Chase Garber

Alexander Ou

Keith Blackstone

Pietro Salvagnini

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

A method for performing automatic visual inspection includes: capturing visual information of an object using a scanning system including a plurality of cameras; extracting, by a computing system including a processor and memory, one or more feature maps from the visual information using one or more feature extractors; classifying, by the computing system, the object by supplying the one or more feature maps to a complex classifier to compute a classification of the object, the complex classifier including: a plurality of simple classifiers, each simple classifier of the plurality of simple classifiers being configured to compute outputs representing a characteristic of the object; and one or more logical operators configured to combine the outputs of the simple classifiers to compute the classification of the object; and outputting, by the computing system, the classification of the object as a result of the automatic visual inspection.

Systems and methods for joint learning of complex visual inspection tasks using computer vision

A method for estimating tightly enclosing bounding boxes by a computing system includes: controlling a scanning system including one or more depth cameras to capture visual information of the scene including one or more objects; detecting the one or more objects of the scene based on the visual information; singulating each the one or more objects from the frame of the scene to generate one or more 3D models corresponding to the one or more objects, the one or more 3D models including a partial 3D model of a corresponding one of the one or more objects; extrapolating a more complete 3D model of the corresponding one of the one or more objects based on the partial 3D model; and estimating a tightly enclosing bounding box of the corresponding one of the one or more objects based on the more complete 3D model.

Systems and methods for object dimensioning based on partial visual information

A method for automatically recognizing content of labels on objects includes: capturing visual information of an object using a scanning system including one or more cameras, the object having one or more labels on one or more exterior surfaces; detecting, by a computing system, one or more surfaces of the object having labels; rectifying, by the computing system, the visual information of the one or more surfaces of the object to compute one or more rectified images; and decoding, by the computing system, content of a label depicted in at least one of the one or more rectified images.

Systems and methods for text and barcode reading under perspective distortion

A system for acquiring three-dimensional (3-D) models of objects includes a first camera group including: a first plurality of depth cameras having overlapping fields of view; a first processor; and a first memory storing instructions that, when executed by the first processor, cause the first processor to: control the first depth cameras to simultaneously capture a first group of images of a first portion of a first object; compute a partial 3-D model representing the first portion of the first object; and detect defects in the first object based on the partial 3-D model representing the first portion of the first object.

Systems and methods for three-dimensional data acquisition and processing under timing constraints

A method for capturing a depth map includes: controlling a plurality of cameras to capture, concurrently, a plurality of first images during a first exposure interval, each of the cameras concurrently capturing a corresponding one of the first images, the cameras having overlapping fields of view; controlling a projection source to emit light at a first illumination level during the first exposure interval; controlling the cameras to capture, concurrently, a plurality of second images during a second exposure interval, each of the cameras concurrently capturing a corresponding one of the second images; controlling the projection source to emit light at a second illumination level during the second exposure interval, the second illumination level being different from the first illumination level; combining the first images with the second images to generate a depth map; and outputting the depth map.

System and method for high dynamic range depth capture using multiple cameras

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

A pattern projection system includes a coherent light source, a repositionable DOE disposed to receive coherent light from said coherent light source and disposed to output at least one pattern of projectable light onto a scene to be imaged by an (x,y) two-dimensional optical acquisition system. Coherent light speckle artifacts in the projected pattern are reduced by rapidly controllably repositioning the DOE or the entire pattern projection system. Different projectable patterns are selected from a set of M patterns that are related to each other by a translation and/or rotation operation in two-dimensional cosine space. A resultant (x,y,z) depth map has improved quality and robustness due to projection of the selected patterns. Three-dimensional (x,y,z) depth data obtained from two-dimensional imaged data including despeckling is higher quality data than if projected patterns without despeckling were used.

Systems and methods for compact space-time stereo three-dimensional depth sensing

A projection system configured to emit patterned light along a projection optical axis includes: a diffractive optical element configured to perform a collimation function on the light emitted by the light emitter and to perform a pattern generation function to replicate the collimated light in a pattern, the pattern having substantially no collimated zero-order; and a light emitter configured to emit light toward the diffractive optical element, wherein the collimation function is configured to collimate the light emitted from the light emitter, and wherein the pattern generation function is configured to replicate the collimated light to produce the patterned light.

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Sunnyvale, CA, United States of America

Francesco Peruch