Robert Boschgmbh

Google Inc.

Yen-Lin Chen

Liu Ren

Lincan Zou

Mao Ye

Kui Xu

Hong Luo

Xiaohua Jiang

Ben Wang

Jianjie Zhang

Chao Du

Zhenyu Zhou

Wenwei Guo

Joseph Eagar

Chao Do

A computer-implemented method includes capturing visual data of an environment using an image sensor of an electronic device and non-visual data of the environment using one or more non-image sensors of the electronic device. Feature descriptors of one or more objects in the environment are generated using the visual data of the environment and the non-visual data of the environment. A map of the environment is generated using the feature descriptors of the one or more objects. One or more virtual objects are anchored to at least one of the objects using the map. The visual data, the non-visual data, and the map are combined in a digital multimedia container file. The digital multimedia container file is stored on the electronic device or on another electronic device connected to the electronic device.

Augmented reality content experience sharing using digital multimedia files

A system for determining a quantitative accuracy of a test movement relative to a reference movement includes a display output device, a memory, and a processor operatively connected to the display output device and the memory. The memory stores motion capture data and programming instructions. The processor executes the programming instructions to determine a quantitative accuracy of the test movement relative to the reference movement. A method, executable by the processor, for determining the quantitative accuracy includes receiving, with the processor, motion capture data that includes the reference movement and the test movement. The motion data is split into individual movements, and the test movement is aligned with the reference movement. The processor computes a quantitative accuracy of the test movement relative to the reference movement, and generates, with the display output device, a visualization representative of the test movement. The computed accuracy is encoded into the visualization.

Method and system for automatic repetitive step and cycle detection for manual assembly line operations

A computing system includes a processing system with at least one processing unit. The processing system is configured to receive a depth map with a first boundary of an object. The processing system is configured to receive a color image that corresponds to the depth map. The color image includes a second boundary of the object. The processing system is configured to extract depth edge points of the first boundary from the depth map. The processing system is configured to identify target depth edge points on the depth map. The target depth edge points correspond to color edge points of the second boundary of the object in the color image. In addition, the processing system is configured to snap the depth edge points to the target depth edge points such that the depth map is enhanced with an object boundary for the object.

Systems and methods for dynamic occlusion handling

A method for automated generation of curves for computer graphics includes receiving a first control point corresponding to a first location in a two-dimensional plane and a second control point corresponding to a second location in the two-dimensional plane, receiving at least one constraint for at least one of the first control point and the second control point, and generating a first set of parameter points to generate a first spline connecting the first control point to the second control point based on the at least one constraint using a multigrid solver, the first set of parameter points including a first predetermined number of parameter points, each parameter point in the first set of parameter points corresponding to a location in the two-dimensional plane and a one-dimensional curvature parameter.

Method and system for automated generation of constrained curves in computer graphics

A glove for use in collecting data for sign language recognition comprises: multiple azimuth sensors arranged on the glove at positions corresponding to the phalanges and metacarpal bones of the hand and used for sensing postures of the hand. The azimuth sensors are only arranged on the glove at positions corresponding to the phalanges of the hand other than the distal phalange in proximity to the fingertip of at least one finger among the middle finger, the index finger, the ring finger, and the little finger. The glove reduces the number of the azimuth sensors arranged on the glove at positions corresponding to the phalanges of the hand, thus reducing costs while not affecting detection performance.

Glove for use in collecting data for sign language recognition

Growing community of inventors

San Jose, CA, United States of America

Yen-Lin Chen