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    Large-scale, dynamic graph storage and processing system
    31.
    发明授权
    Large-scale, dynamic graph storage and processing system 有权

    公开(公告)号：US10162550B2

    公开(公告)日：2018-12-25

    申请号：US14831792

    申请日：2015-08-20

    Applicant: NEC Laboratories America, Inc.

    Inventor： Kunal Rao ,  Giuseppe Coviello ,  Srimat Chakradhar ,  Souvik Bhattacherjee ,  Srihari Cadambi

    IPC: G06F3/06 ,  G06F17/30 ,  G06T11/20

    Abstract: A graph storage and processing system is provided. The system includes a scalable, distributed, fault-tolerant, in-memory graph storage device for storing base graph data representative of graphs. The system further includes a real-time, in memory graph storage device for storing update graph data representative of graph updates for the graphs with respect to a time threshold. The system also includes an in-memory graph sampler for sampling the base graph data to generate sampled portions of the graphs and for storing the sampled portions of the graph. The system additionally includes a query manager for providing a query interface between applications and the system and for forming graph data representative of a complete graph from at least the base graph data and the update graph data, if any. The system also includes a graph computer for processing the sampled portions using batch-type computations to generate approximate results for graph-based queries.

    Compact, Clustering-Based Indexes for Large-Scale Real-Time Lookups on Streaming Videos
    34.
    发明申请
    Compact, Clustering-Based Indexes for Large-Scale Real-Time Lookups on Streaming Videos 有权
    基于紧凑型，基于聚类的索引，用于流式视频上的大规模实时查询

    公开(公告)号：US20160299920A1

    公开(公告)日：2016-10-13

    申请号：US15088452

    申请日：2016-04-01

    Applicant: NEC Laboratories America, Inc.

    Inventor： Min Feng ,  Giuseppe Coviello ,  Srimat Chakradhar ,  Nitin Agrawal ,  Yi Yang

    IPC: G06F17/30 ,  G06K9/62 ,  G06K9/00

    CPC classification number: G06F17/30277 ,  G06F17/30256 ,  G06F17/30781 ,  G06K9/00268 ,  G06K9/00711 ,  G06K9/6219 ,  G06K9/6223 ,  G06K9/6272

    Abstract: Systems and methods for recognizing a face are disclosed and includes receiving images of faces; generating feature vectors of the images; generating clusters of feature vectors each with a centroids or a cluster representative; for a query to search for a face, generating corresponding feature vectors for the face and comparing the feature vector with the centroids of all clusters; for clusters above a similarity threshold, comparing cluster members with the corresponding feature vector; and indicating as matching candidates for cluster members with similarity above a threshold.

    Abstract translation: 公开了用于识别面部的系统和方法，并且包括接收面部图像; 生成图像的特征向量; 产生每个具有质心或簇代表的特征向量簇; 用于搜索面部的查询，为面部生成相应的特征向量并将特征向量与所有聚类的质心进行比较; 对于高于相似性阈值的簇，将簇成员与对应的特征向量进行比较; 并且指示作为具有高于阈值的相似性的聚类成员的匹配候选。

    VIDEO ANALYTICS ACCURACY USING TRANSFER LEARNING
    37.
    发明公开
    VIDEO ANALYTICS ACCURACY USING TRANSFER LEARNING 审中-公开

    公开(公告)号：US20240037778A1

    公开(公告)日：2024-02-01

    申请号：US18361340

    申请日：2023-07-28

    Applicant: NEC Laboratories America, Inc.

    Inventor： Kunal Rao ,  Giuseppe Coviello ,  Murugan Sankaradas ,  Oliver Po ,  Srimat Chakradhar ,  Sibendu Paul

    IPC: G06T7/70 ,  G06T7/00 ,  G06V10/25 ,  G06V40/10

    CPC classification number: G06T7/70 ,  G06T7/0002 ,  G06V10/25 ,  G06V40/103 ,  G06V2201/07 ,  G06T2207/30242

    Abstract: Systems and methods are provided for increasing accuracy of video analytics tasks in real-time by acquiring a video using video cameras, and identifying fluctuations in the accuracy of video analytics applications across consecutive frames of the video. The identified fluctuations are quantified based on an average relative difference of true-positive detection counts across consecutive frames. Fluctuations in accuracy are reduced by applying transfer learning to a deep learning model initially trained using images, and retraining the deep learning model using video frames. A quality of object detections is determined based on an amount of track-ids assigned by a tracker across different video frames. Optimization of the reduction of fluctuations includes iteratively repeating the identifying, the quantifying, the reducing, and the determining the quality of object detections until a threshold is reached. Model predictions for each frame in the video are generated using the retrained deep learning model.

    Dynamic microservice intercommunication configuration
    38.
    发明授权
    Dynamic microservice intercommunication configuration 有权

    公开(公告)号：US11785065B2

    公开(公告)日：2023-10-10

    申请号：US17720776

    申请日：2022-04-14

    Applicant: NEC Laboratories America, Inc.

    Inventor： Giuseppe Coviello ,  Kunal Rao ,  Wang-Pin Hsiung ,  Oliver Po ,  Srimat Chakradhar

    IPC: H04L65/60

    CPC classification number: H04L65/60

    Abstract: Methods and systems for managing communications include identifying a system condition in a distributed computing system comprising a first microservice in communication with a second microservice. A communications method is identified responsive to the identified system condition using a reinforcement learning model that associates communication methods with system conditions. The identified communications method is implemented for communications between the first microservice and the second microservice, such that the first microservice and the second microservice use the identified communications method to transmit data.

    FACE CLUSTERING IN VIDEO STREAMS
    39.
    发明申请
    FACE CLUSTERING IN VIDEO STREAMS 有权

    公开(公告)号：US20210319226A1

    公开(公告)日：2021-10-14

    申请号：US17194911

    申请日：2021-03-08

    Applicant: NEC Laboratories America, Inc.

    Inventor： Biplob Debnath ,  Srimat Chakradhar ,  Giuseppe Coviello ,  Murugan Sankaradas

    IPC: G06K9/00 ,  G06K9/40 ,  G06K9/62

    Abstract: Methods and systems for video analysis and response include detecting face images within video streams. Noisy images are filtered from the detected face images. Batches of the remaining detected face images are clustered to generate mini-clusters, constrained by temporal locality. The mini-clusters are globally clustered to generate merged clusters formed of face images for respective people, using camera-chain information to constrain a set of the video streams being considered. Analytics are performed on the merged clusters to identify a tracked individual's movements through an environment. A response is performed to the tracked individual's movements.

    COMBINED PERSON DETECTION AND FACE RECOGNITION FOR PHYSICAL ACCESS CONTROL
    40.
    发明申请
    COMBINED PERSON DETECTION AND FACE RECOGNITION FOR PHYSICAL ACCESS CONTROL 有权

    公开(公告)号：US20210264137A1

    公开(公告)日：2021-08-26

    申请号：US17178444

    申请日：2021-02-18

    Applicant: NEC Laboratories America, Inc.

    Inventor： Kunal Rao ,  Yi Yang ,  Giuseppe Coviello ,  Srimat Chakradhar

    IPC: G06K9/00 ,  G06T7/20 ,  G08B13/196

    Abstract: Methods and systems for managing access include detecting a person within a region of interest in a video stream. It is determined that a clear image of the person's face is not available within the region of interest. Tracking information of the person is matched to historical face tracking information for the person in a previously captured frame. The person's face from the previously captured video frame is matched to an authentication list, responsive to detecting the person within the region of interest, to determine that the detected person is unauthorized for access. A response to the determination that the detected person is unauthorized for access is performed.

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