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公开(公告)号：US10043551B2
公开(公告)日：2018-08-07
申请号：US14750426
申请日：2015-06-25
Applicant: Intel Corporation
Inventor： Glen J. Anderson , Kathy Yuen , Joshua Ekandem , Omesh Tickoo , Ravishankar Iyer
IPC: H04N5/77 , H04N9/80 , G11B27/11 , G11B27/34 , G11B27/031 , G06K9/00 , H04N21/422 , H04N21/4223 , H04N21/433 , H04N21/44 , H04N21/472 , H04N21/8549 , H04N5/76 , G11B27/28
Abstract: Examples include a determination how to manage storage of a video clip generated from recorded video based upon a sensor event. Managing storage of the video clip may include determining whether to save or delete the video clip based on an imprint associated with an object that indicates whether the object is included in the video clip.
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公开(公告)号：US20170185846A1
公开(公告)日：2017-06-29
申请号：US14998322
申请日：2015-12-24
Applicant: INTEL CORPORATION
Inventor： Myung Hwangbo , Krishna Kumar Singh , Teahyung Lee , Omesh Tickoo
CPC classification number: G06K9/00751 , G06K9/00718 , G06K9/00765 , G06K9/46 , G06K9/628
Abstract: An apparatus for video summarization using sematic information is described herein. The apparatus includes a controller, a scoring mechanism, and a summarizer. The controller is to segment an incoming video stream into a plurality of activity segments, wherein each frame is associated with an activity. The scoring mechanism is to calculate a score for each frame of each activity, wherein the score is based on a plurality of objects in each frame. The summarizer is to summarize the activity segments based on the score for each frame.
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73.发明申请公开(公告)号：US20160091964A1
公开(公告)日：2016-03-31
申请号：US14498704
申请日：2014-09-26
Applicant: Intel Corporation
Inventor： Ravishankar R. Iyer , Omesh Tickoo , Glen J. Anderson
Abstract: Generally discussed herein are systems and apparatuses for gesture-based augmented reality. Also discussed herein are methods of using the systems and apparatuses. According to an example a method may include detecting, in image data, an object and a gesture, in response to detecting the object in the image data, providing data indicative of the detected object, in response to detecting the gesture in the image data, providing data indicative of the detected gesture, and modifying the image data using the data indicative of the detected object and the data indicative of the detected gesture.
Abstract translation: 这里通常讨论的是用于基于手势的增强现实的系统和装置。 这里也讨论了使用系统和装置的方法。 根据示例，方法可以包括：响应于检测到图像数据中的手势，响应于检测到图像数据中的对象，检测图像数据中的对象和手势，提供指示检测到的对象的数据， 提供指示检测到的手势的数据，以及使用指示检测到的对象的数据和指示检测到的手势的数据修改图像数据。
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公开(公告)号：US20250153712A1
公开(公告)日：2025-05-15
申请号：US18956235
申请日：2024-11-22
Applicant: Intel Corporation
Inventor： David Gomez Gutierrez , Javier Felip Leon , Kshitij A. Doshi , Leobardo E. Campos Macias , Nilesh Amar Ahuja , Omesh Tickoo
Abstract: An apparatus comprising a memory to store an observed trajectory of a pedestrian, the observed trajectory comprising a plurality of observed locations of the pedestrian over a first plurality of timesteps; and a processor to generate a predicted trajectory of the pedestrian, the predicted trajectory comprising a plurality of predicted locations of the pedestrian over the first plurality of timesteps and over a second plurality of timesteps occurring after the first plurality of timesteps; determine a likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the first plurality of timesteps and the plurality of observed locations of the pedestrian over the first plurality of timesteps; and responsive to the determined likelihood of the predicted trajectory, provide information associated with the predicted trajectory to a vehicle to warn the vehicle of a potential collision with the pedestrian.
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公开(公告)号：US11836240B2
公开(公告)日：2023-12-05
申请号：US18157154
申请日：2023-01-20
Applicant: Intel Corporation
Inventor： Yen-Kuang Chen , Shao-Wen Yang , Ibrahima J. Ndiour , Yiting Liao , Vallabhajosyula S. Somayazulu , Omesh Tickoo , Srenivas Varadarajan
IPC: G06F21/44 , H04L9/06 , G06F21/64 , G06F21/53 , G06N5/022 , G06F21/45 , H04L9/32 , H04W4/70 , G06F16/538 , G06F16/535 , G06F16/54 , G06F21/62 , G06F9/50 , G06N3/04 , G06N3/063 , G06V10/44 , G06V20/00 , G06V40/20 , G06V40/16 , G06F9/48 , H04L67/51 , G06T7/11 , G06V10/96 , G06V30/262 , G06K15/02 , G06F18/24 , G06F18/21 , G06F18/22 , G06F18/211 , G06F18/213 , G06F18/2413 , G06N3/045 , G06V30/19 , G06V10/82 , G06V10/94 , G06V10/75 , G06V10/20 , G06V10/40 , G06N3/08 , H04L67/12 , H04N19/80 , G06F16/951 , H04N19/46 , G06T7/70 , H04W12/02 , H04L9/00 , H04N19/12 , H04N19/124 , H04N19/167 , H04N19/172 , H04N19/176 , H04N19/44 , H04N19/48 , H04N19/513 , G06T7/20 , G06F18/243 , G06V30/194 , H04N19/42 , H04N19/625 , H04N19/63 , G06T7/223 , H04L67/10
CPC classification number: G06F21/44 , G06F9/4881 , G06F9/5044 , G06F9/5066 , G06F9/5072 , G06F16/535 , G06F16/538 , G06F16/54 , G06F16/951 , G06F18/21 , G06F18/211 , G06F18/213 , G06F18/2163 , G06F18/22 , G06F18/24 , G06F18/24143 , G06F21/45 , G06F21/53 , G06F21/6254 , G06F21/64 , G06K15/1886 , G06N3/04 , G06N3/045 , G06N3/063 , G06N3/08 , G06N5/022 , G06T7/11 , G06T7/70 , G06V10/20 , G06V10/40 , G06V10/454 , G06V10/75 , G06V10/82 , G06V10/95 , G06V10/96 , G06V20/00 , G06V30/19173 , G06V30/274 , G06V40/161 , G06V40/20 , H04L9/0643 , H04L9/3239 , H04L67/12 , H04L67/51 , H04N19/46 , H04N19/80 , H04W4/70 , G06F18/24323 , G06F2209/503 , G06F2209/506 , G06F2221/2117 , G06T7/20 , G06T7/223 , G06T2207/10016 , G06T2207/20021 , G06T2207/20024 , G06T2207/20052 , G06T2207/20056 , G06T2207/20064 , G06T2207/20084 , G06T2207/20221 , G06T2207/30242 , G06V30/194 , G06V2201/10 , H04L9/50 , H04L67/10 , H04N19/12 , H04N19/124 , H04N19/167 , H04N19/172 , H04N19/176 , H04N19/42 , H04N19/44 , H04N19/48 , H04N19/513 , H04N19/625 , H04N19/63 , H04W12/02
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.
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Patent Agency Ranking
公开(公告)号：US11586854B2
公开(公告)日：2023-02-21
申请号：US16830341
申请日：2020-03-26
Applicant: Intel Corporation
Inventor： Nilesh Ahuja , Ibrahima Ndiour , Javier Felip Leon , David Gomez Gutierrez , Ranganath Krishnan , Mahesh Subedar , Omesh Tickoo
IPC: G06K9/00 , G06K9/62 , G05B13/04 , G06N3/084 , G05D1/00 , G05D1/02 , B60W60/00 , G05B13/02 , G06V20/20 , G06V20/58 , G06V40/10
Abstract: Vehicle navigation control systems in autonomous driving rely on accurate predictions of objects within the vicinity of the vehicle to appropriately control the vehicle safely through its surrounding environment. Accordingly this disclosure provides methods and devices which implement mechanisms for obtaining contextual variables of the vehicle's environment for use in determining the accuracy of predictions of objects within the vehicle's environment.
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公开(公告)号：US11531850B2
公开(公告)日：2022-12-20
申请号：US16947590
申请日：2020-08-07
Applicant: Intel Corporation
Inventor： Yen-Kuang Chen , Shao-Wen Yang , Ibrahima J. Ndiour , Yiting Liao , Vallabhajosyula S. Somayazulu , Omesh Tickoo , Srenivas Varadarajan
IPC: G06K9/62 , G06F9/48 , G06F9/50 , G06F16/535 , G06F16/538 , G06F16/951 , G06F21/44 , G06F21/45 , G06F21/53 , G06F21/62 , G06F21/64 , H04L9/06 , G06N5/02 , G06N3/04 , H04L9/32 , H04W4/70 , G06F16/54 , G06N3/063 , G06V10/20 , G06V10/40 , G06V10/75 , G06V10/44 , G06V20/00 , G06V40/20 , G06V40/16 , H04L67/51 , G06T7/11 , G06V10/96 , G06V30/262 , G06K15/02 , G06N3/08 , H04L67/12 , H04N19/80 , H04N19/46 , G06T7/70 , H04W12/02 , H04L9/00 , H04N19/12 , H04N19/124 , H04N19/167 , H04N19/172 , H04N19/176 , H04N19/44 , H04N19/48 , H04N19/513 , G06V30/194 , G06T7/20 , H04N19/42 , H04N19/625 , H04N19/63 , G06T7/223 , H04L67/10
Abstract: In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images. The processor may: identify an uncompressed image; access context information associated with the uncompressed image and the one or more compressed master images; determine, based on the context information, whether the uncompressed image is associated with a corresponding master image; upon a determination that the uncompressed image is associated with the corresponding master image, compress the uncompressed image into a corresponding compressed image with reference to the corresponding master image; upon a determination that the uncompressed image is not associated with the corresponding master image, compress the uncompressed image into the corresponding compressed image without reference to the one or more compressed master images; and store the corresponding compressed image on the storage device.
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公开(公告)号：US20220191537A1
公开(公告)日：2022-06-16
申请号：US17509246
申请日：2021-10-25
Applicant: Intel Corporation
Inventor： Yiting Liao , Yen-Kuang Chen , Shao-Wen Yang , Vallabhajosyula S. Somayazulu , Srenivas Varadarajan , Omesh Tickoo , Ibrahima J. Ndiour
IPC: H04N19/52 , H04N19/523 , G06N3/04 , G06K9/62 , H04N19/172 , G06V10/20
Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a communication interface, a compressed video stream captured by a camera, wherein the compressed video stream comprises: a first compressed frame; and a second compressed frame, wherein the second compressed frame is compressed based at least in part on the first compressed frame, and wherein the second compressed frame comprises a plurality of motion vectors; decompress the first compressed frame into a first decompressed frame; perform pixel-domain object detection to detect an object at a first position in the first decompressed frame; and perform compressed-domain object detection to detect the object at a second position in the second compressed frame, wherein the object is detected at the second position in the second compressed frame based on: the first position of the object in the first decompressed frame; and the plurality of motion vectors from the second compressed frame.
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公开(公告)号：US20210243012A1
公开(公告)日：2021-08-05
申请号：US16948304
申请日：2020-09-11
Applicant: Intel Corporation
Inventor： Yen-Kuang Chen , Shao-Wen Yang , Ibrahima J. Ndiour , Yiting Liao , Vallabhajosyula S. Somayazulu , Omesh Tickoo , Srenivas Varadarajan
IPC: H04L9/06 , G06F21/64 , G06F21/53 , G06N5/02 , G06K9/00 , G06N3/04 , H04L29/08 , G06F21/45 , H04L9/32 , H04W4/70 , G06F21/44 , G06K9/46 , G06K9/62 , G06F16/538 , G06F16/535 , G06F16/54 , G06F21/62 , G06F9/50 , G06N3/063 , G06N3/08 , H04N19/80 , G06F16/951 , G06K9/36 , H04N19/46 , G06T7/70 , G06K9/64 , G06K9/72
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.
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公开(公告)号：US10949674B2
公开(公告)日：2021-03-16
申请号：US16298549
申请日：2019-03-11
Applicant: Intel Corporation
Inventor： Myung Hwangbo , Krishna Kumar Singh , Teahyung Lee , Omesh Tickoo
Abstract: An apparatus for video summarization using sematic information is described herein. The apparatus includes a controller, a scoring mechanism, and a summarizer. The controller is to segment an incoming video stream into a plurality of activity segments, wherein each frame is associated with an activity. The scoring mechanism is to calculate a score for each frame of each activity, wherein the score is based on a plurality of objects in each frame. The summarizer is to summarize the activity segments based on the score for each frame.
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