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1. 发明授权

US08462996B2 Method and system for measuring human response to visual stimulus based on changes in facial expression 有权
公开(公告)号：US08462996B2
公开(公告)日：2013-06-11
申请号：US12154002
申请日：2008-05-19
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06K9/00
CPC分类号： G06K9/00335 , G06K9/00315
摘要： The present invention is a method and system for measuring human emotional response to visual stimulus, based on the person's facial expressions. Given a detected and tracked human face, it is accurately localized so that the facial features are correctly identified and localized. Face and facial features are localized using the geometrically specialized learning machines. Then the emotion-sensitive features, such as the shapes of the facial features or facial wrinkles, are extracted. The facial muscle actions are estimated using a learning machine trained on the emotion-sensitive features. The instantaneous facial muscle actions are projected to a point in affect space, using the relation between the facial muscle actions and the affective state (arousal, valence, and stance). The series of estimated emotional changes renders a trajectory in affect space, which is further analyzed in relation to the temporal changes in visual stimulus, to determine the response.

2. 发明授权

US08379937B1 Method and system for robust human ethnicity recognition using image feature-based probabilistic graphical models 有权
标题翻译：使用基于图像特征的概率图形模型进行强壮人类种族识别的方法和系统
公开(公告)号：US08379937B1
公开(公告)日：2013-02-19
申请号：US12286233
申请日：2008-09-29
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06K9/00281 , G06K9/4609
摘要： The present invention is a method and system to provide a face-based automatic ethnicity recognition system that utilizes ethnicity-sensitive image features and probabilistic graphical models to represent ethnic classes. The ethnicity-sensitive image features are derived from groups of image features so that each grouping of the image features contributes to more accurate recognition of the ethnic class. The ethnicity-sensitive image features can be derived from image filters that are matched to different colors, sizes, and shapes of facial features—such as eyes, mouth, or complexion. The ethnicity-sensitive image features serve as observable quantities in the ethnic class-dependent probabilistic graphical models, where each probabilistic graphical model represents one ethnic class. A given input facial image is corrected for pose and lighting, and ethnicity-sensitive image features are extracted. The extracted image features are fed to the ethnicity-dependent probabilistic graphical models to determine the ethnic class of the input facial image.
摘要翻译：本发明是一种提供基于脸部的自动种族识别系统的方法和系统，该系统利用民族敏感的图像特征和概率图形模型来表示族裔阶层。种族敏感的图像特征是从图像特征的组中导出的，使得每一组图像特征有助于更准确地识别民族阶层。种族敏感的图像特征可以从匹配于不同颜色，尺寸和面部特征（例如眼睛，嘴巴或肤色）的形状的图像滤波器导出。种族敏感的图像特征在民族阶级依赖概率图形模型中可以作为可观察量，其中每个概率图形模型代表一个民族阶级。针对姿态和照明校正给定的输入面部图像，并提取种族敏感的图像特征。提取的图像特征被馈送到种族依赖概率图形模型以确定输入面部图像的民族类别。

3. 发明申请

US20080109397A1 Automatic detection and aggregation of demographics and behavior of people 有权
标题翻译：人口统计学和人际行为的自动检测和聚合
公开(公告)号：US20080109397A1
公开(公告)日：2008-05-08
申请号：US12002398
申请日：2007-12-17
申请人： Rajeev Sharma , Hankyu Moon , Namsoon Jung
发明人： Rajeev Sharma , Hankyu Moon , Namsoon Jung
IPC分类号： G06F17/30
CPC分类号： G06Q30/02
摘要： The present invention is a system and framework for automatically measuring and correlating visual characteristics of people and accumulating the data for the purpose of demographic and behavior analysis. The demographic and behavior characteristics of people are extracted from a sequence of images using techniques from computer vision. The demographic and behavior characteristics are combined with a timestamp and a location marker to provide a feature vector of a person at a particular time at a particular location. These feature vectors are then accumulated and aggregated automatically in order to generate a data set that can be statistically analyzed, data mined and/or queried.
摘要翻译：本发明是用于自动测量和关联人的视觉特征并且为了人口和行为分析的目的而累积数据的系统和框架。使用计算机视觉技术从图像序列中提取人的人口和行为特征。人口统计学和行为特征与时间戳和位置标记组合，以在特定位置处的特定时间提供人的特征向量。然后，这些特征向量自动累积和聚合，以便生成可以进行统计分析，数据挖掘和/或查询的数据集。

4. 发明授权

US09740977B1 Method and system for recognizing the intentions of shoppers in retail aisles based on their trajectories 有权
公开(公告)号：US09740977B1
公开(公告)日：2017-08-22
申请号：US12455295
申请日：2009-05-29
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06N5/00 , G06N7/00 , G06T7/00
CPC分类号： G06N5/00 , G06K9/00771 , G06N7/005 , G06Q30/02 , G06T7/00
摘要： The present invention is a method and system for automatically recognizing which products a shopper intends to find or purchase based on the shopper's trajectory in a retail aisle. First, the system detects and tracks the person to generate the trajectory of the shopper. Then some of the dynamic features are extracted from the shopper trajectory. The shopper trajectory features of a given trajectory are typically the positions, the motion orientations, and speeds at each point of the trajectory. A shopper behavior model is designed based on some of the primitive actions of shoppers. The last step of the method is to analyze a given shopper trajectory to estimate the shopper's intention. The step either utilizes decision rules based on the extracted shopper trajectory features, or utilizes a trained Hidden Markov Model, to estimate the progression of the primitive actions from the trajectory. The decoded progression of the shopper behavior states is then interpreted to finally determine the shopper's intention.

5. 发明授权

US08081816B1 Apparatus and method for hardware implementation of object recognition from an image stream using artificial neural network 有权
标题翻译：使用人工神经网络从图像流硬件实现对象识别的装置和方法
公开(公告)号：US08081816B1
公开(公告)日：2011-12-20
申请号：US12157087
申请日：2008-06-06
申请人： Kevin Maurice Irick , Vijaykrishnan Narayanan , Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Kevin Maurice Irick , Vijaykrishnan Narayanan , Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06K9/62
CPC分类号： G06K9/00986 , G06K9/00979 , G06N3/063
摘要： The present invention is an apparatus and method for object recognition from at least an image stream from at least an image frame utilizing at least an artificial neural network. The present invention further comprises means for generating multiple components of an image pyramid simultaneously from a single image stream, means for providing the active pixel and interlayer neuron data to at least a subwindow processor, means for multiplying and accumulating the product of a pixel data or interlayer data and a synapse weight, and means for performing the activation of an accumulation. The present invention allows the artificial neural networks to be reconfigurable, thus embracing a broad range of object recognition applications in a flexible way. The subwindow processor in the present invention also further comprises means for performing neuron computations for at least a neuron. An exemplary embodiment of the present invention is used for object recognition, including face detection and gender recognition, in hardware. The apparatus comprises a digital circuitry system or IC that embodies the components of the present invention.
摘要翻译：本发明是一种用于至少利用至少一个人造神经网络的至少一个图像帧的图像流进行物体识别的装置和方法。本发明还包括用于从单个图像流同时生成图像金字塔的多个分量的装置，用于向至少一个子窗口处理器提供活动像素和层间神经元数据的装置，用于乘法和累加像素数据的乘积的装置，层间数据和突触重量，以及用于执行累积的激活的装置。本发明允许人造神经网络是可重构的，因此以灵活的方式包含广泛的对象识别应用。本发明的子窗口处理器还包括用于对至少神经元进行神经元计算的装置。本发明的一个示例性实施例用于硬件中的对象识别，包括面部检测和性别识别。该装置包括体现本发明组件的数字电路系统或IC。

6. 发明申请

US20090158309A1 Method and system for media audience measurement and spatial extrapolation based on site, display, crowd, and viewership characterization 审中-公开
标题翻译：基于网站，展示，人群和观众特征的媒体观众测量和空间外推的方法和系统
公开(公告)号：US20090158309A1
公开(公告)日：2009-06-18
申请号：US12001611
申请日：2007-12-12
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： H04H60/33
CPC分类号： H04N21/44218 , G06K9/00778 , H04H60/33 , H04N21/4223
摘要： The present invention provides a comprehensive method to design an automatic media viewership measurement system, from the problem of sensor placement for an effective sampling of the viewership to the method of extrapolating spatially sampled viewership data. The system elements that affect the viewership—site, display, crowd, and audience—are identified first. The site-viewership analysis derives some of the crucial elements in determining an effective data sampling plan: visibility, occupancy, and viewership relevancy. The viewership sampling map is computed based on the visibility map, the occupancy map, and the viewership relevancy map; the viewership measurement sensors are placed so that the sensor coverage maximizes the viewership sampling map. The crowd-viewership analysis derives a model of the viewership in relation to the system parameters so that the viewership extrapolation can effectively adapt to the time-changing spatial distribution of the viewership; the step identifies crowd dynamics, and its invariant features as the crucial elements that extract the influence of the site, display, and the crowd to the temporal changes of viewership. The extrapolation map is formulated around these quantities, so that the site-wide viewership can be effectively estimated from the sampled viewership measurement.
摘要翻译：本发明提供了一种全面的方法来设计一种自动媒体观看量度系统，从传感器放置的问题出发，将收视率有效抽样的方法推广到空间采样的收视率数据外推法。影响观众网站，展示，人群和观众的系统元素首先被识别。站点收视率分析得出了确定有效数据抽样计划的一些关键因素：可见度，占用率和观众关联度。基于可见度图，占用地图和观看者相关性图来计算观众抽样图; 放置观众测量传感器，使得传感器覆盖最大化观众抽样图。人群观众分析得出与体系参数相关的观众模型，使得观众推论能够有效地适应观众的时空变化空间分布; 该步骤确定人群动态，其不变特征作为提取站点影响力，显示和人群对观看时间变化的关键要素。外推图是围绕这些数量制定的，因此可以从采样的收视率测量中有效地估计网站范围的收视率。

7. 发明授权

US11004093B1 Method and system for detecting shopping groups based on trajectory dynamics 有权
公开(公告)号：US11004093B1
公开(公告)日：2021-05-11
申请号：US12459281
申请日：2009-06-29
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06Q30/02 , G06K9/00 , G06T7/292 , G06T7/277
摘要： The present invention is a method and system for detecting shopping groups based on the dynamic relation between shoppers' trajectories. First, shopper trajectories are generated using video images or positioning devices. Then, group behavior features are extracted from a candidate shopping group trajectory pair. The group behavior features of a given pair of trajectories are typically the changes in positional differences and the average speed of these trajectories. From a model of shopping group behavior, a given pair of candidate shopping group trajectories is analyzed to determine the group score—the likelihood of the pair of shoppers indeed belonging to the same group. Lastly, the system utilizes graph segmentation framework to find clusters where trajectories belonging to each cluster have tight group scores with each other.

8. 发明授权

US09317785B1 Method and system for determining ethnicity category of facial images based on multi-level primary and auxiliary classifiers 有权
标题翻译：基于多级主辅分类器确定面部图像种族类别的方法和系统
公开(公告)号：US09317785B1
公开(公告)日：2016-04-19
申请号：US14257816
申请日：2014-04-21
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung , Joonhwa Shin
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung , Joonhwa Shin
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06K9/6267 , G06K9/00234 , G06K9/00288 , G06K9/6292 , G06K9/6857 , G06K2009/00322 , G06T2207/30201
摘要： The present invention is a system and method for performing ethnicity classification based on the facial images of people, using multi-category decomposition architecture of classifiers, which include a set of predefined auxiliary classifiers that are specialized to auxiliary features of the facial images. In the multi-category decomposition architecture, which is a hybrid multi-classifier architecture specialized to ethnicity classification, the task of learning the concept of ethnicity against significant within-class variations, is handled by decomposing the set of facial images into auxiliary demographics classes; the ethnicity classification is performed by an array of classifiers where each classifier, called an auxiliary class machine, is specialized to the given auxiliary class. The facial image data is annotated to assign the age and gender labels as well as the ethnicity labels. Each auxiliary class machine is trained to output both the given auxiliary class membership likelihood and the ethnicity likelihoods. Faces are detected from the input image, individually tracked, and fed to all the auxiliary class machines to compute the desired auxiliary class membership and ethnicity likelihood outputs. The outputs from all the auxiliary class machines are combined in a manner to make a final decision on the ethnicity of the given face.
摘要翻译：本发明是一种使用分类器的多类别分解架构，基于人脸部图像进行种族分类的系统和方法，其包括专门针对面部图像的辅助特征的一组预定义的辅助分类器。在专门用于种族分类的混合多分类架构的多类别分解架构中，通过将面部图像集合分解为辅助人口统计学类来处理种族对概念内部变化的概念的任务; 种族分类由分类器阵列执行，其中每个分类器（称为辅助类机器）专用于给定的辅助类。注意面部图像数据以分配年龄和性别标签以及种族标签。训练每个辅助类机器输出给定的辅助类成员资格似然率和种族可能性。从输入图像检测到面部，单独跟踪并馈送到所有辅助类机器，以计算所需的辅助类成员和种族似然输出。所有辅助类机器的输出结合起来，对给定面孔的种族做出最终决定。

9. 发明授权

US08325982B1 Method and system for detecting and tracking shopping carts from videos 有权
标题翻译：用于从视频中检索和跟踪购物车的方法和系统
公开(公告)号：US08325982B1
公开(公告)日：2012-12-04
申请号：US12460818
申请日：2009-07-23
申请人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Rajeev Sharma , Namsoon Jung
IPC分类号： G06K9/00 , H04N5/225
CPC分类号： G06K9/3233 , G06K9/00771 , G06T7/215
摘要： The present invention is a method and system for detecting and tracking shopping carts from video images in a retail environment. First, motion blobs are detected and tracked from the video frames. Then these motion blobs are examined to determine whether or not some of them contain carts, based on the presence or absence of linear edge motion. Linear edges are detected within consecutive video frames, and their estimated motions vote for the presence of a cart. The motion blobs receiving enough votes are classified as cart candidate blobs. A more elaborate model of passive motions within blobs containing a cart is constructed. The detected cart candidate blob is then analyzed based on the constructed passive object motion model to verify whether or not the blob indeed shows the characteristic passive motion of a person pushing a cart. Then the finally-detected carts are corresponded across the video frames to generate cart tracks.
摘要翻译：本发明是一种用于在零售环境中从视频图像检测和跟踪购物车的方法和系统。首先，从视频帧中检测和跟踪运动斑点。然后根据是否存在线性边缘运动来检查这些运动斑点以确定它们中的一些是否包含推车。线性边缘在连续的视频帧内被检测到，并且它们的估计的动作投票给购物车的存在。获得足够投票的动作斑点被分类为购物车候选点。构建了一个更加精细的被动运动模型，其中包含一个推车的斑点内。然后基于所构造的被动对象运动模型来分析检测到的购物车候选Blob，以验证该小块是否确实显示推送推车的人的特征被动运动。然后，最终检测到的车在视频帧上对应，以产生购物车轨道。

10. 发明授权

US08165386B1 Apparatus and method for measuring audience data from image stream using dynamically-configurable hardware architecture 有权
标题翻译：使用动态可配置硬件架构从图像流测量观众数据的装置和方法
公开(公告)号：US08165386B1
公开(公告)日：2012-04-24
申请号：US12583323
申请日：2009-08-18
申请人： Hankyu Moon , Kevin Maurice Irick , Vijaykrishnan Narayanan , Rajeev Sharma , Namsoon Jung
发明人： Hankyu Moon , Kevin Maurice Irick , Vijaykrishnan Narayanan , Rajeev Sharma , Namsoon Jung
IPC分类号： G06K9/62
CPC分类号： G06K9/00993 , G06K9/00973
摘要： The present invention is an embedded audience measurement platform, which is called HAM. The HAM includes hardware, apparatus, and method for measuring audience data from image stream using dynamically-configurable hardware architecture. The HAM provides an end-to-end solution for audience measurement, wherein reconfigurable computational modules are used as engines per node to power the complete solution implemented in a flexible hardware architecture. The HAM is also a complete system for broad audience measurement, which has various components built into the system. Examples of the components comprise demographics classification, gaze estimation, emotion recognition, behavior analysis, and impression measurement.
摘要翻译：本发明是一种称为HAM的嵌入式观众测量平台。 HAM包括使用动态可配置的硬件架构来测量来自图像流的观众数据的硬件，装置和方法。 HAM为观众测量提供端到端解决方案，其中可重构计算模块用作每个节点的引擎，为在灵活的硬件架构中实现的完整解决方案提供动力。 HAM也是一个完整的系统，用于广泛的受众测量，其中包含系统内置的各种组件。组件的示例包括人口统计分类，注视估计，情感识别，行为分析和印象测量。

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