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公开(公告)号：US20180129910A1
公开(公告)日：2018-05-10
申请号：US15709748
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
CPC classification number: G06K9/6256 , B60T2201/022 , B60W30/00 , G05D1/0221 , G06F17/5009 , G06K9/00201 , G06K9/00208 , G06K9/00624 , G06K9/00771 , G06K9/00805 , G06K9/4628 , G06K9/6255 , G06N3/02 , G06N3/084 , G06T7/55 , G06T7/74 , G06T11/60 , G06T15/10 , G06T15/40 , G06T2207/20101 , G06T2207/30261 , G06T2210/22 , G08G1/0962 , G08G1/166 , H04N7/00
Abstract: A system and method are provided. The system includes an image capture device configured to capture an actual image depicting an object. The system also includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, a set of synthetic images with corresponding intermediate shape concept labels. The processor is also configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is further configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D geometric structure and a 3D geometric structure of the object depicted in the actual image.
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2.发明申请公开(公告)号：US20180130355A1
公开(公告)日：2018-05-10
申请号：US15709814
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
CPC classification number: G06K9/6256 , B60T2201/022 , B60W30/00 , G05D1/0221 , G06F17/5009 , G06K9/00201 , G06K9/00208 , G06K9/00624 , G06K9/00771 , G06K9/00805 , G06K9/4628 , G06K9/6255 , G06N3/02 , G06N3/084 , G06T7/55 , G06T7/74 , G06T11/60 , G06T15/10 , G06T15/40 , G06T2207/20101 , G06T2207/30261 , G06T2210/22 , G08G1/0962 , G08G1/166 , H04N7/00
Abstract: A system and method are provided for driving assistance. The system includes an image capture device configured to capture an actual image relative to an outward view from a motor vehicle and depicting an object. The system further includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is further configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D and 3D geometric structure of the object. The processor is additionally configured to perform an action to mitigate a likelihood of harm involving the motor vehicle, based on the image pair.
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3.发明申请公开(公告)号：US20180129865A1
公开(公告)日：2018-05-10
申请号：US15709897
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
CPC classification number: G06K9/6256 , B60T2201/022 , B60W30/00 , G05D1/0221 , G06F17/5009 , G06K9/00201 , G06K9/00208 , G06K9/00624 , G06K9/00771 , G06K9/00805 , G06K9/4628 , G06K9/6255 , G06N3/02 , G06N3/0454 , G06N3/082 , G06N3/084 , G06T7/55 , G06T7/74 , G06T11/60 , G06T15/10 , G06T15/40 , G06T2207/20101 , G06T2207/30261 , G06T2210/22 , G08G1/0962 , G08G1/166 , H04N7/00
Abstract: An action recognition system and method are provided. The action recognition system includes an image capture device configured to capture an actual image depicting an object. The action recognition system includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN thereto to generate an image pair including a 2D and 3D geometric structure of the object. The processor is configured to control a device to perform a response action in response to an identification of an action performed by the object, wherein the identification of the action is based on the image pair.
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Patent Agency Ranking
公开(公告)号：US10289936B2
公开(公告)日：2019-05-14
申请号：US15709849
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
IPC: G06K9/00 , G06K9/62 , G06F17/50 , G06N3/02 , G06T11/60 , G06T15/40 , G05D1/02 , G08G1/16 , G06T7/73 , G06N3/08 , G06T15/10 , B60W30/00 , G08G1/0962 , H04N7/00 , G06T7/55 , G06K9/46
Abstract: A surveillance system and method are provided. The surveillance system includes an image capture device configured to capture an actual image of a target area depicting an object. The surveillance system further includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, synthetic images with intermediate shape corresponding concept labels. The processor is further configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to generate an image pair including a 2D and 3D geometric structure of the object depicted in the actual image. The surveillance system further includes a display device configured to display the image pair.
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公开(公告)号：US10289935B2
公开(公告)日：2019-05-14
申请号：US15709814
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
IPC: G05D1/02 , G06K9/00 , G06K9/46 , G06K9/62 , G06N3/02 , G06N3/08 , G06T7/55 , G06T7/73 , G08G1/16 , H04N7/00 , B60W30/00 , G06F17/50 , G06T11/60 , G06T15/10 , G06T15/40 , G08G1/0962
Abstract: A system and method are provided for driving assistance. The system includes an image capture device configured to capture an actual image relative to an outward view from a motor vehicle and depicting an object. The system further includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is further configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D and 3D geometric structure of the object. The processor is additionally configured to perform an action to mitigate a likelihood of harm involving the motor vehicle, based on the image pair.
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公开(公告)号：US10289934B2
公开(公告)日：2019-05-14
申请号：US15709748
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
IPC: G06K9/00 , G06K9/62 , G06F17/50 , G06N3/02 , G06T11/60 , G06T15/40 , G05D1/02 , G08G1/16 , G06T7/73 , G06N3/08 , G06T15/10 , B60W30/00 , G08G1/0962 , H04N7/00 , G06T7/55 , G06K9/46
Abstract: A system and method are provided. The system includes an image capture device configured to capture an actual image depicting an object. The system also includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, a set of synthetic images with corresponding intermediate shape concept labels. The processor is also configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is further configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D geometric structure and a 3D geometric structure of the object depicted in the actual image.
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7.发明申请公开(公告)号：US20180130229A1
公开(公告)日：2018-05-10
申请号：US15709849
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
CPC classification number: G06K9/6256 , B60T2201/022 , B60W30/00 , G05D1/0221 , G06F17/5009 , G06K9/00201 , G06K9/00208 , G06K9/00624 , G06K9/00771 , G06K9/00805 , G06K9/4628 , G06K9/6255 , G06N3/02 , G06N3/084 , G06T7/55 , G06T7/74 , G06T11/60 , G06T15/10 , G06T15/40 , G06T2207/20101 , G06T2207/30261 , G06T2210/22 , G08G1/0962 , G08G1/166 , H04N7/00
Abstract: A surveillance system and method are provided. The surveillance system includes an image capture device configured to capture an actual image of a target area depicting an object. The surveillance system further includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, synthetic images with intermediate shape corresponding concept labels. The processor is further configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to generate an image pair including a 2D and 3D geometric structure of the object depicted in the actual image. The surveillance system further includes a display device configured to display the image pair.
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公开(公告)号：US10331974B2
公开(公告)日：2019-06-25
申请号：US15709897
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
IPC: G06K9/00 , G06K9/62 , G06F17/50 , G06N3/02 , G06T11/60 , G06T15/40 , G05D1/02 , G08G1/16 , G06T7/73 , G06N3/08 , G06T15/10 , B60W30/00 , G08G1/0962 , G06T7/55 , G06K9/46
Abstract: An action recognition system and method are provided. The action recognition system includes an image capture device configured to capture an actual image depicting an object. The action recognition system includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN thereto to generate an image pair including a 2D and 3D geometric structure of the object. The processor is configured to control a device to perform a response action in response to an identification of an action performed by the object, wherein the identification of the action is based on the image pair.
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