Intel Corporation

Gm Global Technolgoy Operations, Inc.

Tzach Ashkenazi

Itay Kaufman

Jill MacDonald Boyce

Prasoonkumar Surti

Michael Apodaca

Kai Xiao

Wenlong Li

Jonathan Distler

Roland Mishaev

Scott R Janus

Atsuo Kuwahara

Jason Daniel Tanner

Narayan Biswal

Xiaofeng Tong

Maria Bortman

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

Yuri Shpalensky

Gaby Prechner

Shaul Oron

Eyal Ruhm

Tzachi Hershkovich

Ilya Romm

Eli Turiel

Adam Kaplan

Ben Raziel

Asaf Shiloni

Ilan Beer

Gilad Bauman

Eytan Kats

A system and method for multi-camera vehicle top view object detection that includes capturing and sending video streams of a surrounding environment to a controller from multiple outward looking cameras that include each camera's detecting three-dimensional objects that are associated with that camera's coordinate frame, where one field of view partially overlaps another field of view. Each detected three-dimensional object from the outward looking cameras are transformed and projected onto a two-dimensional coordinate frame and image frame of each camera where a ranked two-dimensional affinity score between each of a pair of detected objects from the cameras are computed where if the affinity score for any object in each of the pair of detected objects is greater than a threshold amount, that object is removed from a list of ranked detected objects and an updated list of ranked detected objects is generated.

Multi-camera top view object detection and suppression

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

A mechanism is described for facilitating monochrome bit depth coding. The apparatus comprises one or more processors to receive depth data and convert the depth data into color space data, including converting a first segment of the depth data into a monochrome component of the color space data and converting a second segment of the depth data into one or more color components of the color space data.

Bit depth coding mechanism

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 are generally directed to neural network based patch blending for immersive video. An embodiment of a system includes one or more processor cores; a memory to store data for images in immersive video; and a neural network training framework. The neural network training framework is to generate a trained neural network for blending of a view of an object with patches generated for one or more detected occlusions for the object.

Neural network based patch blending for immersive video

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

Petach Tikva, Israel

Tzach Ashkenazi