-
公开(公告)号：US08731291B2
公开(公告)日：2014-05-20
申请号：US13624985
申请日：2012-09-24
IPC分类号： G06K9/00
CPC分类号： G06K9/00664
摘要： A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by partitioning the input digital image into small sub-images and analyzing the sub-images to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. The inequality index is compared to a predefined threshold to classify the input digital image as a rich-content image or a low-content image. For rich-content images, the estimated clutter level is determined responsive to a set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. For low-content images, the estimated clutter level is determined responsive to an overall luminance level.
摘要翻译： 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过将输入的数字图像分割成小的子图像并分析子图像来确定一组图像特征来确定不等式索引。 图像特征与一组指定的参考特征相关联，并且基于参考特征的统计变化来确定不等式指数。 将不等式指数与预定阈值进行比较，以将输入数字图像分类为富内容图像或低内容图像。 对于富含内容的图像，响应于与输入数字图像的空间结构或语义内容相关的一组场景内容特征来确定估计的杂波水平，通过分析输入的数字图像来确定。 对于低内容图像，估计的杂波电平是根据整体亮度水平确定的。
-
公开(公告)号：US20140086495A1
公开(公告)日：2014-03-27
申请号：US13624986
申请日：2012-09-24
IPC分类号： G06K9/68
CPC分类号： G06K9/00664
摘要： A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by analyzing the input digital image to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. A set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. The estimated clutter is determined responsive to the inequality index and the scene content features.
摘要翻译： 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过分析输入数字图像来确定一组图像特征来确定不等式指数。 图像特征与一组指定的参考特征相关联，并且基于参考特征的统计变化来确定不等式指数。 通过分析输入数字图像来确定与输入数字图像的空间结构或语义内容相关的一组场景内容特征。 响应于不等式指数和场景内容特征确定估计的杂波。
-
公开(公告)号：US20140086487A1
公开(公告)日：2014-03-27
申请号：US13624985
申请日：2012-09-24
IPC分类号： G06K9/62
CPC分类号： G06K9/00664
摘要： A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by partitioning the input digital image into small sub-images and analyzing the sub-images to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. The inequality index is compared to a predefined threshold to classify the input digital image as a rich-content image or a low-content image. For rich-content images, the estimated clutter level is determined responsive to a set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. For low-content images, the estimated clutter level is determined responsive to an overall luminance level.
摘要翻译： 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过将输入的数字图像分割成小的子图像并分析子图像来确定一组图像特征来确定不等式索引。 图像特征与一组指定的参考特征相关联，并且基于参考特征的统计变化来确定不等式指数。 将不等式指数与预定阈值进行比较，以将输入数字图像分类为富内容图像或低内容图像。 对于富含内容的图像，响应于与输入数字图像的空间结构或语义内容相关的一组场景内容特征来确定估计的杂波水平，通过分析输入的数字图像来确定。 对于低内容图像，估计的杂波电平是根据整体亮度水平确定的。
-
公开(公告)号：US20140063556A1
公开(公告)日：2014-03-06
申请号：US13598260
申请日：2012-08-29
申请人： Minwoo Park , Dhiraj Joshi , Alexander C. Loui , Amit Singhal
发明人： Minwoo Park , Dhiraj Joshi , Alexander C. Loui , Amit Singhal
CPC分类号： G06T11/60 , G06F17/214 , G06T11/00
摘要： Generating a tag layout from a set of tags and an ordering of the set of tags, wherein each tag includes a text label and a size for the text label, is disclosed. The system includes a processor accessible memory for receiving an ordered set of tags, each tag including a text label and a size for the text label, and at least one closed shape corresponding to a space for the tag layout. The system further includes a processor for generating the tag layout by computing a scale factor for either the closed shape or the size of the text labels in the set of tags such that all the tags in the set of tags fit within the closed shape, and the processor stores the generated tag layout in the memory.
摘要翻译： 公开了一组标签生成标签布局以及该标签集的顺序，其中每个标签包括文本标签和文本标签的尺寸。 该系统包括用于接收有序集合标签的处理器可访问存储器，每个标签包括文本标签和文本标签的尺寸，以及至少一个对应于标签布局的空间的封闭形状。 该系统还包括一个处理器，用于通过计算一组标签中的封闭形状或文本标签的尺寸的比例因子来生成标签布局，使得该组标签中的所有标签都适合于闭合形状，以及 处理器将生成的标签布局存储在存储器中。
-
公开(公告)号：US20140058982A1
公开(公告)日：2014-02-27
申请号：US13591472
申请日：2012-08-22
IPC分类号： G06F15/18
CPC分类号： G10L25/51
摘要： A method for controlling a device responsive to an audio signal captured using an audio sensor. A data processor is used to automatically analyze the audio signal using a plurality of semantic concept detectors to determine corresponding preliminary semantic concept detection values, each semantic concept detector being adapted to detect a particular semantic concept. The preliminary semantic concept detection values are analyzed using a joint likelihood model based on predetermined pair-wise likelihoods that particular pairs of semantic concepts co-occur to determine updated semantic concept detection values. One or more semantic concepts are determined based on the updated semantic concept detection values, and the device is controlled responsive to identified semantic concepts. The semantic concept detectors and the joint likelihood model are trained together with a joint training process using training audio signals, at least some of which are known to be associated with a plurality of semantic concepts.
摘要翻译： 一种用于响应于使用音频传感器捕获的音频信号来控制设备的方法。 数据处理器用于使用多个语义概念检测器自动分析音频信号，以确定对应的初步语义概念检测值，每个语义概念检测器适于检测特定的语义概念。 基于预定的成对似然性，使用联合似然模型来分析初步语义概念检测值，特定的语义概念对共同出现以确定更新的语义概念检测值。 基于更新的语义概念检测值来确定一个或多个语义概念，并且响应于所识别的语义概念控制所述设备。 语义概念检测器和联合似然模型与使用训练音频信号的联合训练过程一起训练，其中至少一些已知与多个语义概念相关联。
-
公开(公告)号：US20140037216A1
公开(公告)日：2014-02-06
申请号：US13565919
申请日：2012-08-03
IPC分类号： G06K9/48
CPC分类号： G06K9/00765 , G06K9/00 , G06K9/00751 , G06K9/48 , G06K9/6249 , G06K2009/4695
摘要： A method for identifying a set of key video frames from a video sequence comprising extracting feature vectors for each video frame and applying a group sparsity algorithm to represent the feature vector for a particular video frame as a group sparse combination of the feature vectors for the other video frames. Weighting coefficients associated with the group sparse combination are analyzed to determine video frame clusters of temporally-contiguous, similar video frames. The video sequence is segmented into scenes by identifying scene boundaries based on the determined video frame clusters.
摘要翻译： 一种用于从视频序列中识别一组关键视频帧的方法，包括提取每个视频帧的特征向量，并且应用组稀疏算法来表示特定视频帧的特征向量作为另一个的特征向量的组稀疏组合 视频帧。 分析与组稀疏组合相关联的加权系数，以确定时间上相邻的类似视频帧的视频帧聚类。 通过基于确定的视频帧聚类识别场景边界，将视频序列分割成场景。
-
公开(公告)号：US08634662B2
公开(公告)日：2014-01-21
申请号：US12862806
申请日：2010-08-25
申请人： Madirakshi Das , Alexander C. Loui
发明人： Madirakshi Das , Alexander C. Loui
IPC分类号： G06K9/62
CPC分类号： G06K9/6221 , G06F17/30265 , G06K9/00677 , G06K9/00684 , G06K9/342
摘要： A method of detecting recurring events in a digital image collection taken over a pre-determined period of time is disclosed. The method uses a processor for analyzing the digital image collection to produce a two-dimensional representation of the distribution of image capture activity over time and detecting recurring events by identifying spatial clusters in the two-dimensional representation.
摘要翻译： 公开了一种在预定时间段内检测到的数字图像集合中的循环事件的检测方法。 该方法使用处理器来分析数字图像集合以产生图像捕获活动随时间的分布的二维表示，并通过识别二维表示中的空间聚类来检测循环事件。
-
公开(公告)号：US20130235939A1
公开(公告)日：2013-09-12
申请号：US13413962
申请日：2012-03-07
IPC分类号： H04N7/30
CPC分类号： H04N19/90 , H04N19/537 , H04N19/59
摘要： A method for representing a video sequence including a time sequence of input video frames, the input video frames including some common scene content that is common to all of the input video frames and some dynamic scene content that changes between at least some of the input video frames. Affine transform are determined to align the common scene content in the input video frames. A common video frame including the common scene content is determined by forming a sparse combination of a first basis functions. A dynamic video frame is determined for each input video frame by forming a sparse combination of a second basis functions, wherein the dynamic video frames can be combined with the respective affine transforms and the common video frame to provide reconstructed video frames.
摘要翻译： 一种用于表示包括输入视频帧的时间序列的视频序列的方法，所述输入视频帧包括所有输入视频帧共同的一些常见场景内容和在至少一些输入视频之间改变的一些动态场景内容 框架。 确定仿射变换以使输入视频帧中的公共场景内容对齐。 通过形成第一基本函数的稀疏组合来确定包括公共场景内容的公共视频帧。 通过形成第二基本函数的稀疏组合，为每个输入视频帧确定动态视频帧，其中动态视频帧可以与各自的仿射变换和公共视频帧组合以提供重构的视频帧。
-
公开(公告)号：US08135221B2
公开(公告)日：2012-03-13
申请号：US12574716
申请日：2009-10-07
CPC分类号： G06K9/00765 , G10L25/00
摘要： A method for determining a classification for a video segment, comprising the steps of: breaking the video segment into a plurality of short-term video slices, each including a plurality of video frames and an audio signal; analyzing the video frames for each short-term video slice to form a plurality of region tracks; analyzing each region track to form a visual feature vector and a motion feature vector; analyzing the audio signal for each short-term video slice to determine an audio feature vector; forming a plurality of short-term audio-visual atoms for each short-term video slice by combining the visual feature vector and the motion feature vector for a particular region track with the corresponding audio feature vector; and using a classifier to determine a classification for the video segment responsive to the short-term audio-visual atoms.
摘要翻译： 一种用于确定视频段的分类的方法，包括以下步骤：将视频段分解成多个短视频片段，每个短片段包括多个视频帧和音频信号; 分析每个短期视频片段的视频帧以形成多个区域轨道; 分析每个区域轨迹以形成视觉特征向量和运动特征向量; 分析每个短期视频片段的音频信号以确定音频特征向量; 通过将特定区域轨道的视觉特征向量和运动特征向量与相应的音频特征向量组合，形成每个短期视频片段的多个短期视听原子; 并且使用分类器来确定响应于短期视听原子的视频片段的分类。
-
公开(公告)号：US20110206284A1
公开(公告)日：2011-08-25
申请号：US12710666
申请日：2010-02-23
申请人： Madirakshi Das , Alexander C. Loui
发明人： Madirakshi Das , Alexander C. Loui
IPC分类号： G06K9/62
CPC分类号： G06K9/6267 , G06F17/30274 , G06K9/00563 , G06K9/00677 , H04N5/2251 , H04N5/232
摘要： A method for organizing an event timeline for a digital image collection, includes using a processor for detecting events in the digital image collection and each event's associated timespan; determining the detected events that are significant in the digital image collection; and organizing the event timeline so that the event timeline shows the significant events and a clustered representation of the other events, made available to the user at different time granularities. The organized event timeline is also used for selecting images for generating output.
摘要翻译： 一种用于组织数字图像集合的事件时间线的方法，包括使用处理器来检测数字图像集合中的事件和每个事件的相关联的时间段; 确定在数字图像收集中显着的检测到的事件; 并组织事件时间线，以便事件时间线显示其他事件的重要事件和聚集表示，使用户以不同的时间粒度可用。 组织的事件时间轴也用于选择用于生成输出的图像。
-
-
-
-
-
-
-
-
-
搜索结果
119 条记录 (耗时 0.044 秒)
