公开(公告)号：US20230306603A1

公开(公告)日：2023-09-28

申请号：US18131650

申请日：2023-04-06

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel

IPC: G06T7/11 ,  G06T7/20 ,  G06T7/174 ,  G06T7/00 ,  G06T7/70 ,  G06V20/40 ,  G06F18/24 ,  G06F18/21 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06T7/11 ,  G06F18/217 ,  G06F18/24 ,  G06T7/174 ,  G06T7/20 ,  G06T7/70 ,  G06T7/97 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/49 ,  G06T2200/24 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

公开(公告)号：US11676278B2

公开(公告)日：2023-06-13

申请号：US16584709

申请日：2019-09-26

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel

IPC: G06K9/00 ,  G06T7/11 ,  G06T7/20 ,  G06T7/174 ,  G06T7/00 ,  G06T7/70 ,  G06V20/40 ,  G06F18/24 ,  G06F18/21 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06T7/11 ,  G06F18/217 ,  G06F18/24 ,  G06T7/174 ,  G06T7/20 ,  G06T7/70 ,  G06T7/97 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/49 ,  G06T2200/24 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

公开(公告)号：US20210118146A1

公开(公告)日：2021-04-22

申请号：US17132810

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Ke Ding ,  Manan Goel

IPC: G06T7/12 ,  G06T7/33

Abstract: Methods, systems, and apparatus for high-fidelity vision tasks using deep neural networks are disclosed. An example apparatus includes a feature extractor to extract low-level features and edge-enhanced features of an input image processed using a convolutional neural network, an eidetic memory block generator to generate an eidetic memory block using the extracted low-level features or the extracted edge-enhanced features, and an interactive segmentation network to perform image segmentation using the eidetic memory block, the eidetic memory block used to propagate domain-persistent features through the segmentation network.

公开(公告)号：US20210110198A1

公开(公告)日：2021-04-15

申请号：US17131525

申请日：2020-12-22

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel ,  Ke Ding

IPC: G06K9/62 ,  G06T7/10 ,  G06N3/04

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for interactive image segmentation. An example apparatus includes an inception controller to execute an inception sublayer of a convolutional neural network (CNN) including two or more inception-atrous-collation (IAC) layers, the inception sublayer including two or more convolutions including respective kernels of varying sizes to generate multi-scale inception features, the inception sublayer to receive one or more context features indicative of user input; an atrous controller to execute an atrous sublayer of the CNN, the atrous sublayer including two or more atrous convolutions including respective kernels of varying sizes to generate multi-scale atrous features; and a collation controller to execute a collation sublayer of the CNN to collate the multi-scale inception features, the multi-scale atrous features, and eidetic memory features.

公开(公告)号：US20210034163A1

公开(公告)日：2021-02-04

申请号：US17074038

申请日：2020-10-19

Applicant: Intel Corporation

Inventor： Manan Goel ,  Saurin Shah ,  Lakshman Krishnamurthy ,  Steven Xing ,  Matthew Pinner ,  Kevin James Doucette

IPC: G06F3/01 ,  G06K9/00 ,  G06F3/03 ,  G10H1/00 ,  G06F3/16 ,  G06F3/042

Abstract: Gesture-controlled virtual reality systems and methods of controlling the same are disclosed herein. An example apparatus includes an on-body sensor to output first signals associated with at least one of movement of a body part of a user or a position of the body part relative to a virtual object and an off-body sensor to output second signals associated with at least one of the movement or the position relative to the virtual object. The apparatus also includes at least one processor to generate gesture data based on at least one of the first or second signals, generate position data based on at least one of the first or second signals, determine an intended action of the user relative to the virtual object based on the position data and the gesture data, and generate an output of the virtual object in response to the intended action.

公开(公告)号：US20180107278A1

公开(公告)日：2018-04-19

申请号：US15388079

申请日：2016-12-22

Applicant: Intel Corporation

Inventor： Manan Goel ,  Saurin Shah ,  Lakshman Krishnamurthy ,  Steven Xing ,  Matthew Pinner ,  Kevin James Doucette

IPC: G06F3/01 ,  G06F3/16 ,  G06K9/00 ,  G06F3/03 ,  G10H1/00

CPC classification number: G06F3/017 ,  G06F3/011 ,  G06F3/014 ,  G06F3/0304 ,  G06F3/0426 ,  G06F3/162 ,  G06K9/00335 ,  G10H1/0008 ,  G10H2220/101 ,  G10H2220/201 ,  G10H2220/391 ,  G10H2220/395 ,  G10H2220/401 ,  G10H2220/425 ,  G10H2220/455

Abstract: Gesture-controlled virtual reality systems and methods of controlling the same are disclosed herein. An example apparatus includes at least two of an on-body sensor, an off-body sensor, and an RF local triangulation system to detect at least one of a position or a movement of a body part of a user relative to a virtual instrument. The example apparatus includes a processor to generate an audio output of the virtual instrument in response to the at least one of the position or the movement.