A9.com, Inc.

Divyansh Agarwal

Arnab S Dhua

Himanshu Arora

Chun Kai Wang

Approaches described and suggested herein relate to generating three-dimensional representations of objects to be used to render virtual reality and augmented reality effects on personal devices such as smartphones and personal computers, for example. An initial surface mesh of an object is obtained. A plurality of silhouette masks of the object taken from a plurality of viewpoints is also obtained. A plurality of depth maps are generated from the initial surface mesh. Specifically, the plurality of depth maps are taken from the same plurality of viewpoints from which the silhouette images are taken. A volume including the object is discretized into a plurality of voxels. Each voxel is then determined to be either inside the object or outside of the object based on the silhouette masks and the depth data. A final mesh is then generated from the voxels that are determined to be inside the object.

Depth hull for rendering three-dimensional models

System and methods are provided that generate a three-dimensional model from a physical space. While a user is scanning and/or recording the physical space with a user computing device, user speech describing the physical space is recorded. A transcript is generated from the audio captured during the scan and/or image recording of the physical space. Keywords from the transcript are used to improve computer-vision object identification, which is incorporated in the three-dimensional model.

Three-dimensional room analysis with audio input

Approaches described and suggested herein relate to generating an enhanced point cloud representation of an objection and generating a surface mesh from the enhanced point cloud. The surface mesh can be used to render three-dimensional representations of objects on personal devices such as smartphones and personal computers, for example. Generating an enhanced point cloud of an object includes capturing a plurality of images of the object from a plurality of viewpoints about the object, generating an initial point cloud representation of the object from the plurality of images, generating a preliminary surface mesh from the point cloud using a Delauney-based meshing algorithm, and sampling points from the preliminary surface mesh. The sampled points are then added to the point cloud to form the enhanced point cloud. A final surface mesh can then be generated from the enhanced point cloud using a Poisson-based meshing algorithm.

Growing community of inventors

Mountain View, CA, United States of America

Divyansh Agarwal