Intel Corporation

Itay Kaufman

Tzach Ashkenazi

Maria Bortman

Jonathan Distler

Prasoonkumar Surti

Jill MacDonald Boyce

Michael Apodaca

Kai Xiao

Scott R Janus

Atsuo Kuwahara

Jason Daniel Tanner

Narayan Biswal

Stanley J Baran

Hugues Labbe

Gokcen Cilingir

Nilesh V Shah

Barnan Das

Jong Dae Oh

Archie Sharma

Mayuresh M Varerkar

Srikanth Potluri

Jeffrey Tripp

Atul Divekar

Or Weiser

Danny Khazov

Zohar Avnat

Roee Lazar

Techniques related to embedding a 3D object model within a 3D scene are discussed. Such techniques include determining two or more object mask images for two or more corresponding cameras trained on the 3D scene, projecting 3D points from the 3D object model to the image planes of the two or more cameras, and determining a position and orientation of the 3D object model in the scene using the object mask images and the projected 3D points.

Embedding complex 3D objects into an augmented reality scene using image segmentation

Techniques related to performing image registration are discussed. Such techniques include converting a source image region and a target image portion from a color image space to a semantic space and iteratively converging homography parameters using the source image region and target image portion in the semantic space by applying iterations with some homography parameters allowed to vary and others blocked from varying and subsequent iterations with all homography parameters allowed to vary.

Robust surface registration based on parameterized perspective of image templates

Embodiments described herein provide an apparatus comprising a processor to project and accumulate three-dimensional (3D) point data from a blob onto a plane; construct a histogram of the 3D point data; identify a center of mass of the blob based on histogram data; surround peaks in coordinates for data in the blob with a shape defined by a diameter of the blob based on the center of mass; obtain height data for the 3D point data; and calculate dimensions for a bounding box to surround the blob based on the shape and the height data. Other embodiments may be described and claimed.

System and method for 3D blob classification and transmission

An apparatus to facilitate processing video bit stream data is disclosed. The apparatus includes one or more processors to encode surface normals data with point cloud geometry data included in the video bit stream data for reconstruction of objects within the video bit stream data based on the surface normals data and a memory communicatively coupled to the one or more processors.

Surface normal vector processing mechanism

Embodiments described herein provide an apparatus comprising a processor to project and accumulate three-dimensional (3D) point data from a blob onto one of a floor plane or a ceiling plane, construct a histogram of the 3D point data, determine a center of mass of the point data from the blob, obtain height data for the 3D point data, and calculate dimensions for a bounding box to surround the blob. Other embodiments may be described and claimed.

Embodiments described herein provide an apparatus comprising a processor to project voxels from a point cloud data set into an n-DoF space, and define successively less granular supervoxels at successively higher layer of abstraction in a view of the point cloud data set, and a memory communicatively coupled to the processor. Other embodiments may be described and claimed.

Voxels sparse representation

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Petah Tikva, Israel

Itay Kaufman