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    SYSTEM AND METHOD OF USING MULTI-FRAME IMAGE FEATURES FOR OBJECT DETECTION
    1.
    发明申请
    SYSTEM AND METHOD OF USING MULTI-FRAME IMAGE FEATURES FOR OBJECT DETECTION 审中-公开

    公开(公告)号：US20190332889A1

    公开(公告)日：2019-10-31

    申请号：US16347237

    申请日：2017-10-27

    Applicant: Konica Minolta Laboratory U.S.A., Inc.

    Inventor： Logan Courtney ,  Haisong Gu

    IPC: G06K9/62 ,  G06N3/04 ,  G06K9/46 ,  G06K9/00

    Abstract: A method, a system, and a computer readable recording medium are disclosed for performing object recognition. The method includes receiving image data from an image; performing a multilayer feature extraction on the image data; generating current feature maps from the multilayer feature extraction; generating a region of proposal network map from at least the current feature maps, the region of proposal network map having one or more regions of interest; inputting previously generated feature maps and the current feature maps into a classifier with the region of proposed network map; and classifying the one or more regions of interest in the region of proposal network map.

    METHOD AND SYSTEM FOR REAL-TIME INSIGHT DETECTION USING EEG SIGNALS
    2.
    发明申请
    METHOD AND SYSTEM FOR REAL-TIME INSIGHT DETECTION USING EEG SIGNALS 审中-公开
    使用脑电信号实时检测的方法和系统

    公开(公告)号：US20150216468A1

    公开(公告)日：2015-08-06

    申请号：US14169728

    申请日：2014-01-31

    Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.

    Inventor： Michel Vidal-Naquet ,  Hideki Tanaka ,  Haisong Gu

    IPC: A61B5/00 ,  A61B5/0476

    CPC classification number: A61B5/04012 ,  A61B5/048 ,  A61B5/165 ,  A61B5/7257 ,  A61B5/726 ,  A61B5/7267

    Abstract: A method, system and computer readable medium for detecting creativity in real-time are disclosed. The method includes sensing electrical activity along a scalp of a subject during a learning phase, the learning phase including presenting to the subject one or more tasks configured to generate electrical activity corresponding to cortical events that are likely to correspond to a creative type experience and cortical events that are likely to correspond to a non-creative type experience. Features from the electrical activity obtained during the learning phase are extracted to create a brainwave profile for the subject. Real-time electrical activity along the scalp of the subject is sensed during a performance of one or more real-time tasks, and the electrical activity of the subject is compared to previously recorded electrical activity using the brainwave profile for the subject to classify the electrical activity obtained during the performance of the one or more real-time.

    Abstract translation: 公开了用于实时检测创造力的方法，系统和计算机可读介质。 该方法包括在学习阶段感测沿着对象的头皮的电活动，所述学习阶段包括向所述对象呈现一个或多个任务，所述任务被配置为产生对应于可能对应于创造性类型体验的皮层事件的皮质事件和皮层 可能与非创意类型体验相对应的事件。 提取在学习期间获得的电活动的特征以产生用于受试者的脑波分布。 在执行一个或多个实时任务期间感测沿着对象头皮的实时电活动，并且使用所述对象的脑波分布将对象的电活动与先前记录的电活动进行比较，以对所述对象进行电分类 在执行一次或多次实时期间获得的活动。

    Method and system for recognition of abnormal behavior
    6.
    发明授权
    Method and system for recognition of abnormal behavior 有权
    识别异常行为的方法和系统

    公开(公告)号：US09355306B2

    公开(公告)日：2016-05-31

    申请号：US14039437

    申请日：2013-09-27

    Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.

    Inventor： Dongdong Wu ,  Yongmian Zhang ,  Haisong Gu

    IPC: G06K9/42 ,  G06K9/00

    CPC classification number: G06K9/00342 ,  G06K2009/00738

    Abstract: A method for recognizing abnormal behavior is disclosed, the method includes: capturing at least one video stream of data on one or more subjects; extracting body skeleton data from the at least one video stream of data; classifying the extracted body skeleton data as normal behavior or abnormal behavior; and generating an alert, if the extracted skeleton data is classified as abnormal behavior.

    Abstract translation: 公开了一种用于识别异常行为的方法，所述方法包括：在一个或多个主体上捕获至少一个视频数据流; 从所述至少一个视频数据流中提取身体骨骼数据; 将提取的身体骨骼数据分类为正常行为或异常行为; 并且如果所提取的骨架数据被分类为异常行为，则生成警报。

    METHOD AND SYSTEM FOR RECOGNIZING AN OBJECT
    7.
    发明申请
    METHOD AND SYSTEM FOR RECOGNIZING AN OBJECT 有权
    用于识别对象的方法和系统

    公开(公告)号：US20160048727A1

    公开(公告)日：2016-02-18

    申请号：US14461057

    申请日：2014-08-15

    Applicant: Konica Minolta Laboratory U.S.A., Inc.

    Inventor： Yongmian ZHANG ,  Hung-Shou Tai ,  Haisong Gu

    IPC: G06K9/00 ,  H04N5/33

    CPC classification number: G06K9/00389 ,  G06K9/6212 ,  H04N5/332

    Abstract: A method, a system, and a non-transitory computer readable medium for recognizing an object are disclosed, the method including: emitting an array of infrared rays from an infrared emitter towards a projection region, the projection region including a first object; generating a reference infrared image by recording an intensity of ray reflection from the projection region without the first object; generating a target infrared image by recording the intensity of ray reflection from the projection region with the first object; comparing the target infrared image to the reference infrared image to generate a predetermined intensity threshold; and extracting the first object from the target infrared image, if the intensity of ray reflection of the target infrared image of the first object exceeds the predetermined intensity threshold.

    Abstract translation: 公开了一种用于识别对象的方法，系统和非暂时计算机可读介质，所述方法包括：从红外发射器朝向投影区域发射红外线阵列，所述投影区域包括第一对象; 通过从没有第一物体的投影区域记录射线反射的强度来产生参考红外图像; 通过从第一物体记录来自投影区域的射线反射强度来产生目标红外图像; 将目标红外图像与参考红外图像进行比较以产生预定强度阈值; 并且如果第一对象的目标红外图像的射线反射强度超过预定强度阈值，则从目标红外图像提取第一对象。

    Method and system for emotion and behavior recognition
    9.
    发明授权
    Method and system for emotion and behavior recognition 有权
    情感和行为识别的方法和系统

    公开(公告)号：US09489570B2

    公开(公告)日：2016-11-08

    申请号：US14145132

    申请日：2013-12-31

    Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.

    Inventor： Chen Cao ,  Yongmian Zhang ,  Haisong Gu

    IPC: G06K9/00 ,  G06K9/62 ,  G06T7/00 ,  G06K9/46 ,  G06T7/20 ,  G06K9/32

    CPC classification number: G06K9/00342 ,  G06K9/00369 ,  G06K9/00718 ,  G06K9/00771 ,  G06K9/3241 ,  G06K9/4642 ,  G06K9/469 ,  G06K9/6212 ,  G06T7/20 ,  G06T2207/10016 ,  G06T2207/20076 ,  G06T2207/30196

    Abstract: A method and system for recognizing behavior is disclosed, the method includes: capturing at least one video stream of data on one or more subjects; extracting body skeleton data from the at least one video stream of data; computing feature extractions on the extracted body skeleton data to generate a plurality of 3 dimensional delta units for each frame of the extracted body skeleton data; generating a plurality of histogram sequences for each frame by projecting the plurality of 3 dimensional delta units for each frame to a spherical coordinate system having a plurality of spherical bins; generating an energy map for each of the plurality of histogram sequences by mapping the plurality of spherical bins versus time; applying a Histogram of Oriented Gradients (HOG) algorithm on the plurality of energy maps to generate a single column vector; and classifying the single column vector as a behavior and/or emotion.

    Abstract translation: 公开了一种用于识别行为的方法和系统，所述方法包括：在一个或多个主题上捕获至少一个视频数据流; 从所述至少一个视频数据流中提取身体骨骼数据; 对所提取的身体骨骼数据进行计算特征提取，以生成所提取的身体骨骼数据的每个帧的多个3维增量单位; 通过将每个帧的多个三维三角洲单元投影到具有多个球形仓的球面坐标系统来为每个帧生成多个直方图序列; 通过将所述多个球形仓相对于时间映射来生成所述多个直方图序列中的每一个的能量图; 在多个能量图上应用定向梯度（HOG）直方图以产生单列向量; 并将单列向量分类为行为和/或情感。

    METHOD AND SYSTEM OF TEMPORAL SEGMENTATION FOR GESTURE ANALYSIS
    10.
    发明申请
    METHOD AND SYSTEM OF TEMPORAL SEGMENTATION FOR GESTURE ANALYSIS 审中-公开
    方法分析的时间分割方法与系统

    公开(公告)号：US20160078287A1

    公开(公告)日：2016-03-17

    申请号：US14473679

    申请日：2014-08-29

    Applicant: Konica Minolta Laboratory U.S.A., Inc.

    Inventor： Quentin AUGE ,  Yongmian Zhang ,  Haisong Gu

    IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62

    CPC classification number: G06K9/00342 ,  G06K9/00201 ,  G06K9/00765

    Abstract: A method, system and non-transitory computer readable medium for recognizing gestures are disclosed, the method includes capturing at least one three-dimensional (3D) video stream of data on a subject; extracting a time-series of skeletal data from the at least one 3D video stream of data; isolating a plurality of points of abrupt content change called temporal cuts, the plurality of temporal cuts defining a set of non-overlapping adjacent segments partitioning the time-series of skeletal data; identifying among the plurality of temporal cuts, temporal cuts of the time-series of skeletal data having a positive acceleration; and classifying each of the one or more pair of consecutive cuts with the positive acceleration as a gesture boundary.

    Abstract translation: 公开了一种用于识别手势的方法，系统和非暂时性计算机可读介质，所述方法包括：在对象上捕获数据的至少一个三维（3D）视频流; 从所述至少一个3D视频数据流中提取骨架数据的时间序列; 分离称为时间切割的多个突变内容变化点，所述多个时间切割定义了划分所述时间序列骨骼数据的一组不重叠的相邻分段; 在多个时间切割之间识别具有正加速度的骨架数据的时间序列的时间切割; 并且将正加速度的一个或多个连续切片中的每一个分类为手势边界。

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