Intel Corporation

Maria Bortman

Tzach Ashkenazi

Itay Kaufman

Jonathan Distler

Yuri Shpalensky

Roland Mishaev

Prasoonkumar Surti

Jill MacDonald Boyce

Michael Apodaca

Kai Xiao

Scott R Janus

Atsuo Kuwahara

Jason Daniel Tanner

Narayan Biswal

Hugues Labbe

Gokcen Cilingir

Nilesh V Shah

Jong Dae Oh

Archie Sharma

Mayuresh M Varerkar

Wenlong Li

Xiaofeng Tong

Stanley J Baran

Barnan Das

Srikanth Potluri

Jeffrey Tripp

Atul Divekar

Gaby Prechner

Ilya Romm

Asaf Shiloni

Alex Gendelman

Techniques related to generating a fine super resolution image from a low resolution image including a person wearing a predetermined uniform are discussed. Such techniques include applying a pretrained convolutional neural network to a stacked image including image channels from a coarse super resolution image, label data corresponding to the coarse super resolution image from available labels relevant to the uniform, and pose data corresponding to the person to determine the fine super resolution image.

Method and apparatus for person super resolution from low resolution image

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

Methods and apparatus to generate photo-realistic three-dimensional models of a photographed environment are disclosed. An apparatus includes an object position calculator to determine a three-dimensional (3D) position of an object detected within a first image of an environment and within a second image of the environment. The apparatus further includes a 3D model generator to generate a 3D model of the environment based on the first image and the second image. The apparatus also includes a model integrity analyzer to detect a difference between the 3D position of the object and the 3D model. The 3D model generator automatically modifies the 3D model based on the difference in response to the difference satisfying a confidence threshold.

Methods and apparatus to generate photo-realistic three-dimensional models of a photographed environment

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

Techniques related to providing high perceptual quality video from highly compressed and decompressed reconstructed video are discussed. Such techniques include applying a pretrained decompression upsampling portion of a generative adversarial network to the decompressed reconstructed video to upsample and improve the perceptual quality of the decompressed reconstructed video to generate output video.

Visual quality optimized video compression

Embodiments described herein provide an apparatus comprising a processor to separate a three-dimensional (3D) scene in a point cloud data set comprising a plurality of voxels into a 3D grid of cells, each cell in the 3D grid of cells comprising a plurality of faces, execute a 3D clustering algorithm to create a plurality of 3D clusters, define a transparency level for each face of each cell in the plurality of cells, detect a surface layer of cells for the plurality of clusters in the 3D scene, and delete, from the plurality of clusters, cells which are not in the surface layer of cells. Other embodiments may be described and claimed.

Point cloud operations

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

Growing community of inventors

Ashkelon, Israel

Maria Bortman