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121.发明申请公开(公告)号：US20190066373A1
公开(公告)日：2019-02-28
申请号：US16029126
申请日：2018-07-06
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Mohammed E.F. Salem , Muhammad Zeeshan Zia , Paul Vernaza , Manmohan Chandraker
CPC classification number: G06K9/00798 , G06K9/00785 , G06K9/00825 , G06K9/46 , G06K9/4628 , G06K9/6262 , G06K9/6274 , G06K9/6276 , G06K9/629 , G06K9/66 , G06N3/0454 , G06N3/08 , G06T17/05 , G06T2200/08 , G06T2207/20081
Abstract: Systems and methods for correspondence estimation and flexible ground modeling include communicating two-dimensional (2D) images of an environment to a correspondence estimation module, including a first image and a second image captured by an image capturing device. First features, including geometric features and semantic features, are hierarchically extract from the first image with a first convolutional neural network (CNN) according to activation map weights, and second features, including geometric features and semantic features, are hierarchically extracted from the second image with a second CNN according to the activation map weights. Correspondences between the first features and the second features are estimated, including hierarchical fusing of geometric correspondences and semantic correspondences. A 3-dimensional (3D) model of a terrain is estimated using the estimated correspondences belonging to the terrain surface. Relative locations of elements and objects in the environment are determined according to the 3D model of the terrain. A user is notified of the relative locations.
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公开(公告)号：US20190064851A1
公开(公告)日：2019-02-28
申请号：US16100479
申请日：2018-08-10
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Manmohan Chandraker , Hyo Jin Kim
Abstract: A computer-implemented method, system, and computer program product are provided for a stabilization system utilizing pose estimation in an aerial drone. The method includes receiving, by a pose estimation system, a plurality of images from one or more cameras. The method also includes predicting, by the pose estimation system, a pose from the score map and a combined feature map, the combined feature map correlated from a pair of the plurality of images. The method additionally includes moving, by a propulsion system, the aerial drone responsive to the pose.
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123.发明申请公开(公告)号：US20180307947A1
公开(公告)日：2018-10-25
申请号：US15906710
申请日：2018-02-27
Applicant: NEC Laboratories America, Inc.
Inventor： Wongun Choi , Samuel Schulter , Kihyuk Sohn , Manmohan Chandraker
CPC classification number: G06K9/6259 , G06K9/03 , G06K9/6201 , G06K9/66 , G06N3/0454 , G06N3/0472 , G06N3/08 , G06T11/001 , G06T11/60
Abstract: A system is provided for unsupervised cross-domain image generation relative to a first and second image domain that each include real images. A first generator generates synthetic images similar to real images in the second domain while including a semantic content of real images in the first domain. A second generator generates synthetic images similar to real images in the first domain while including a semantic content of real images in the second domain. A first discriminator discriminates real images in the first domain against synthetic images generated by the second generator. A second discriminator discriminates real images in the second domain against synthetic images generated by the first generator. The discriminators and generators are deep neural networks and respectively form a generative network and a discriminative network in a cyclic GAN framework configured to increase an error rate of the discriminative network to improve synthetic image quality.
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124.发明申请公开(公告)号：US20180268266A1
公开(公告)日：2018-09-20
申请号：US15889958
申请日：2018-02-06
Applicant: NEC Laboratories America, Inc.
Inventor： Kihyuk Sohn , Xiang Yu , Manmohan Chandraker
CPC classification number: G06K9/66 , G06K9/00268 , G06K9/00288 , G06K9/00718 , G06K9/00744 , G06K9/00771 , G06K9/4628 , G06K9/6201 , G06K9/6217 , G06K9/6262 , G06K9/6274 , G06K2009/00738 , G06N3/02 , G06N3/0454 , G06N3/08 , G06N3/088 , G06N20/00 , G06T7/70 , G06T9/002 , G06T2207/20081 , G08B13/196 , G08B13/19613
Abstract: A surveillance system is provided that includes a device configured to capture a video sequence, formed from a set of unlabeled testing video frames, of a target area. The surveillance system further includes a processor configured to pre-train a recognition engine formed from a reference set of CNNs on a still image domain that includes labeled training still image frames. The processor adapts the recognition engine to a video domain to form an adapted recognition engine, by applying a non-reference set of CNNs to domains including the still image and video domains and a degraded image domain. The degraded image domain includes labeled synthetically degraded versions of the frames included in the still image domain. The video domain includes random unlabeled training video frames. The processor recognizes, using the adapted engine, at least one object in the target area. A display device displays the recognized objects.
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125.发明申请公开(公告)号：US20180268222A1
公开(公告)日：2018-09-20
申请号：US15890005
申请日：2018-02-06
Applicant: NEC Laboratories America, Inc.
Inventor： Kihyuk Sohn , Xiang Yu , Manmohan Chandraker
CPC classification number: G06K9/66 , G06K9/00268 , G06K9/00288 , G06K9/00718 , G06K9/00744 , G06K9/00771 , G06K9/4628 , G06K9/6201 , G06K9/6217 , G06K9/6262 , G06K9/6274 , G06K2009/00738 , G06N3/02 , G06N3/0454 , G06N3/08 , G06N3/088 , G06N20/00 , G06T7/70 , G06T9/002 , G06T2207/20081 , G08B13/196 , G08B13/19613
Abstract: An action recognition system is provided that includes a device configured to capture a video sequence formed from a set of unlabeled testing video frames. The system further includes a processor configured to pre-train a recognition engine formed from a reference set of CNNs on a still image domain that includes labeled training still image frames. The processor adapts the recognition engine to a video domain to form an adapted engine, by applying non-reference CNNs to domains that include the still image and video domains and a degraded image domain that includes labeled synthetically degraded versions of the frames in the still image domain. The video domain includes random unlabeled training video frames. The processor recognizes, using the adapted engine, an action performed by at least one object in the sequence, and controls a device to perform a response action in response to an action type of the action.
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Patent Agency Ranking
126.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：US09904855B2
公开(公告)日：2018-02-27
申请号：US14882794
申请日：2015-10-14
Applicant: NEC Laboratories America, Inc.
Inventor： Manmohan Chandraker , Chao-Yeh Chen , Wongun Choi
CPC classification number: G06K9/00785 , G06K9/00134 , G06K9/0014 , G06K9/00147 , G06K9/52 , G06K2209/05 , G06T7/207 , G06T7/246 , G06T7/251 , G06T7/579 , G06T2200/04 , G06T2207/20016 , G06T2207/20081 , G06T2207/30236 , G06T2207/30241 , G06T2207/30244 , G06T2207/30252 , G08G1/16 , G08G1/166
Abstract: Systems and methods are disclosed to provide an Advanced Warning System (AWS) for a driver of a vehicle, by capturing traffic scene types from a single camera video; generating real-time monocular SFM and 2D object detection from the single camera video; detecting a ground plane from the real-time monocular SFM and the 2D object detection; performing dense 3D estimation from the real-time monocular SFM and the 2D object detection; generating a joint 3D object localization from the ground plane and dense 3D estimation; and communicating a situation that requires caution to the driver.
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公开(公告)号：US20180047272A1
公开(公告)日：2018-02-15
申请号：US15637360
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Wongun Choi , Eric Lau , Elsa Wong , Guobin Chen
IPC: G08B21/02
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
Abstract: A baby detection system and corresponding method are provided. The baby detection system includes a camera configured to capture an input image of a subject purported to be a baby and presented at an electronic-gate system. The baby detection system further includes a memory storing a deep learning model configured to perform a baby detection task for an electronic-gate application corresponding to the electronic-gate system. The baby detection system also includes a processor configured to apply the deep learning model to the input image to provide a baby detection result of either a presence or an absence of an actual baby in relation to the subject purported to be the baby. The baby detection task is configured to evaluate one or more different distractor modalities corresponding to one or more different physical spoofing materials to prevent baby spoofing for the baby detection task.
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公开(公告)号：US20180046645A1
公开(公告)日：2018-02-15
申请号：US15637433
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Wongun Choi , Eric Lau , Elsa Wong , Guobin Chen
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
Abstract: A smuggling detection system and corresponding method are provided. The smuggling detection system includes a camera configured to capture an input image of a subject purported to be a baby. The smuggling detection system further includes a memory storing a deep learning model configured to perform a baby detection task for a smuggling detection application. The smuggling detection system also includes a processor configured to apply the deep learning model to the input image to provide a baby detection result of either a presence or an absence of an actual baby in relation to the subject purported to be the baby. The baby detection task is configured to evaluate one or more different distractor modalities corresponding to one or more different physical spoofing materials to prevent baby spoofing for the baby detection task.
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公开(公告)号：US20160137206A1
公开(公告)日：2016-05-19
申请号：US14879264
申请日：2015-10-09
Applicant: NEC Laboratories America, Inc.
Inventor： Manmohan Chandraker , Vikas Dhiman
CPC classification number: B60W40/04 , B60R2300/108 , B60R2300/804 , G06K9/00798 , G06K9/00805 , G06T7/215 , G06T7/277 , G06T7/579 , G06T17/00 , G06T2207/10016 , G06T2207/20076 , G06T2207/30241 , G06T2207/30252 , H04N5/225 , H04N7/183
Abstract: Systems and methods are disclosed for road scene understanding of vehicles in traffic by capturing images of traffic with a camera coupled to a vehicle; generating a continuous model of occlusions with a continuous occlusion mode for traffic participants to enhance point track association accuracy without distinguishing between moving and static objects; applying the continuous occlusion model to handle visibility constraints in object tracks; and combining point track association and soft object track modeling to improve 3D localization accuracy.
Abstract translation: 公开了通过使用耦合到车辆的照相机捕获交通图像来进行交通车辆道路现场理解的系统和方法; 以连续遮挡模式为流量参与者生成连续的闭塞模型，以增强点轨道关联精度，而不区分移动和静态对象; 应用连续遮挡模型来处理物体轨迹中的可视约束; 并结合点轨道关联和软物体轨迹建模来提高3D定位精度。
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