-
公开(公告)号：US20190354801A1
公开(公告)日：2019-11-21
申请号：US16400429
申请日：2019-05-01
Applicant: NEC Laboratories America, Inc.
Inventor： Kihyuk Sohn , Manmohan Chandraker , Xiang Yu
Abstract: A method for implementing an unsupervised cross-domain distance metric adaptation framework with a feature transfer network for enhancing facial recognition includes recursively training a feature transfer network and automatic labeling of target domain data using a clustering method, and implementing the feature transfer network and the automatic labeling to perform a facial recognition task.
-
公开(公告)号：US10289825B2
公开(公告)日：2019-05-14
申请号：US15637644
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Xiang Yu , Eric Lau , Elsa Wong
IPC: G06K9/00 , G06F21/32 , G06N20/00 , G06N99/00 , G07C9/00 , H04L29/06 , G06F21/62 , G06K9/46 , G06K9/66
Abstract: A login access control system is provided. The login access control system includes a camera configured to capture an input image of a subject purported to be a person and attempting to login to a system to access secure data. The login access control system further includes a memory storing a deep learning model configured to perform multi-task learning for a pair of tasks including a liveness detection task and a face recognition task. The login access control system also includes a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized for access to the secure data and a liveness of the subject. The liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.
-
公开(公告)号：US10289824B2
公开(公告)日：2019-05-14
申请号：US15637465
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Xiang Yu , Eric Lau , Elsa Wong
IPC: G06K9/00 , G06F21/32 , G06N20/00 , G06N99/00 , G07C9/00 , H04L29/06 , G06F21/62 , G06K9/46 , G06K9/66
Abstract: A facility access control system and corresponding method are provided. The facility access control system includes a camera configured to capture an input image of a subject attempting to enter or exit a restricted facility. The facility access control system further includes a memory storing a deep learning model configured to perform multi-task learning for a pair of tasks including a liveness detection task and a face recognition task. The facility access control system also includes a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized for access to the facility and a liveness of the subject. The liveness detection task is configured to evaluate a plurality of different distracter modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.
-
公开(公告)号：US20190138812A1
公开(公告)日：2019-05-09
申请号：US16112040
申请日：2018-08-24
Applicant: NEC Laboratories America, Inc.
Inventor： Kihyuk Sohn , Manmohan Chandraker , Xiang Yu
Abstract: A computer-implemented method, system, and computer program product are provided for activity recognition in a mobile device. The method includes receiving a plurality of unlabeled videos from one or more cameras. The method also includes generating a classified video for each of the plurality of unlabeled videos by classifying an activity in each of the plurality of unlabeled videos. The method additionally includes storing the classified video in a location in a memory designated for videos of the activity in each of the classified videos.
-
公开(公告)号：US20190096125A1
公开(公告)日：2019-03-28
申请号：US16145621
申请日：2018-09-28
Applicant: NEC Laboratories America, Inc.
Inventor： Samuel Schulter , Paul Vernaza , Manmohan Chandraker , Menghua Zhai
Abstract: Systems and methods for generating an occlusion-aware bird's eye view map of a road scene include identifying foreground objects and background objects in an input image to extract foreground features and background features corresponding to the foreground objects and the background objects, respectively. The foreground objects are masked from the input image with a mask. Occluded objects and depths of the occluded objects are inferred by predicting semantic features and depths in masked areas of the masked image according to contextual information related to the background features visible in the masked image. The foreground objects and the background objects are mapped to a three-dimensional space according to locations of each of the foreground objects, the background objects and occluded objects using the inferred depths. A bird's eye view is generated from the three-dimensional space and displayed with a display device.
-
Patent Agency Ranking
公开(公告)号：US20190095705A1
公开(公告)日：2019-03-28
申请号：US16145537
申请日：2018-09-28
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Xi Yin , Kihyuk Sohn , Manmohan Chandraker
Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.
-
公开(公告)号：US20190095700A1
公开(公告)日：2019-03-28
申请号：US16145608
申请日：2018-09-28
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Xi Yin , Kihyuk Sohn , Manmohan Chandraker
Abstract: A computer-implemented method, system, and computer program product are provided for facial recognition. The method includes receiving, by a processor device, a plurality of images. The method also includes extracting, by the processor device with a feature extractor utilizing a convolutional neural network (CNN) with an enlarged intra-class variance of long-tail classes, feature vectors for each of the plurality of images. The method additionally includes generating, by the processor device with a feature generator, discriminative feature vectors for each of the feature vectors. The method further includes classifying, by the processor device utilizing a fully connected classifier, an identity from the discriminative feature vector. The method also includes control an operation of a processor-based machine to react in accordance with the identity.
-
公开(公告)号：US20190066326A1
公开(公告)日：2019-02-28
申请号：US16100445
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 pose estimation. The method includes receiving, by a processor, a plurality of images from one or more cameras. The method also includes generating, by the processor with a feature extraction convolutional neural network (CNN), a feature map for each of the plurality of images. The method additionally includes estimating, by the processor with a feature weighting network, a score map from a pair of the feature maps. The method further includes predicting, by the processor with a pose estimation CNN, a pose from the score map and a combined feature map. The method also includes controlling an operation of a processor-based machine to change a state of the processor-based machine, responsive to the pose.
-
公开(公告)号：US10115032B2
公开(公告)日：2018-10-30
申请号：US15342700
申请日：2016-11-03
Applicant: NEC Laboratories America, Inc.
Inventor： Manmohan Chandraker , Christopher Bongsoo Choy , Silvio Savarese
Abstract: A computer-implemented method for training a convolutional neural network (CNN) is presented. The method includes extracting coordinates of corresponding points in the first and second locations, identifying positive points in the first and second locations, identifying negative points in the first and second locations, training features that correspond to positive points of the first and second locations to move closer to each other, and training features that correspond to negative points in the first and second locations to move away from each other.
-
公开(公告)号：US20180268202A1
公开(公告)日：2018-09-20
申请号：US15888747
申请日：2018-02-05
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Kihyuk Sohn , Manmohan Chandraker
CPC classification number: G06K9/00288 , G06F16/71 , G06F16/743 , G06F16/784 , G06K9/00201 , G06K9/00208 , G06K9/00214 , G06K9/00255 , G06K9/00275 , G06K9/00771 , G06K9/00899 , G06K9/4628 , G06K9/6256 , G06T19/20 , G06T2210/44
Abstract: A video surveillance system is provided. The system includes a device configured to capture an input image of a subject located in an area. The system further includes a processor. The processor estimates, using a three-dimensional Morphable Model (3DMM) conditioned Generative Adversarial Network, 3DMM coefficients for the subject of the input image. The subject varies from an ideal front pose. The processor produces, using an image generator, a synthetic frontal face image of the subject of the input image based on the input image and coefficients. An area spanning the frontal face of the subject is made larger in the synthetic than in the input image. The processor provides, using a discriminator, a decision of whether the subject of the synthetic image is an actual person. The processor provides, using a face recognition engine, an identity of the subject in the input image based on the synthetic and input images.
-
-
-
-
-
-
-
-
-
Search Results
230
records
(took 0.025 seconds)
