公开(公告)号：US07039239B2

公开(公告)日：2006-05-02

申请号：US10072756

申请日：2002-02-07

申请人： Alexander C. Loui ,  Sanjiv Kumar

发明人： Alexander C. Loui ,  Sanjiv Kumar

IPC分类号： G06K9/62

CPC分类号： G06K9/4647 ,  G06K9/00624 ,  G06K9/6226 ,  G06K9/6268 ,  G06K9/6292

摘要： A method for classification of image regions by probabilistic merging of a class probability map and a cluster probability map includes the steps of a) extracting one or more features from an input image composed of image pixels; b) performing unsupervised learning based on the extracted features to obtain a cluster probability map of the image pixels; c) performing supervised learning based on the extracted features to obtain a class probability map of the image pixels; and d) combining the cluster probability map from unsupervised learning and the class probability map from supervised learning to generate a modified class probability map to determine the semantic class of the image regions. In one embodiment the extracted features include color and textual features.

公开(公告)号：US08989503B2

公开(公告)日：2015-03-24

申请号：US13565919

申请日：2012-08-03

申请人： Mrityunjay Kumar ,  Alexander C. Loui ,  Bruce Harold Pillman

发明人： Mrityunjay Kumar ,  Alexander C. Loui ,  Bruce Harold Pillman

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：US08976299B2

公开(公告)日：2015-03-10

申请号：US13413982

申请日：2012-03-07

申请人： Mrityunjay Kumar ,  Abdolreza Abdolhosseini Moghadam ,  Alexander C. Loui ,  Jiebo Luo

发明人： Mrityunjay Kumar ,  Abdolreza Abdolhosseini Moghadam ,  Alexander C. Loui ,  Jiebo Luo

IPC分类号： H04N7/50 ,  G11B27/28 ,  H04N5/14 ,  H04N21/44 ,  H04N21/8549

CPC分类号： H04N5/144 ,  G11B27/28 ,  H04N21/44008 ,  H04N21/8549

摘要： A method for determining a scene boundary location dividing a first scene and a second scene in an input video sequence. The scene boundary location is determined responsive to a merit function value, which is a function of the candidate scene boundary location. The merit function value for a particular candidate scene boundary location is determined by representing the dynamic scene content for the input video frames before and after candidate scene boundary using sparse combinations of a set of basis functions, wherein the sparse combinations of the basis functions are determined by finding a sparse vector of weighting coefficients for each of the basis functions. The weighting coefficients determined for each of the input video frames are combined to determine the merit function value. The candidate scene boundary providing the smallest merit function value is designated to be the scene boundary location.

摘要翻译： 一种用于确定在输入视频序列中划分第一场景和第二场景的场景边界位置的方法。 响应于作为候选场景边界位置的函数的优值函数值来确定场景边界位置。 通过使用一组基函数的稀疏组合表示候选场景边界之前和之后的输入视频帧的动态场景内容来确定特定候选场景边界位置的优值函数值，其中确定基函数的稀疏组合 通过找出每个基本函数的加权系数的稀疏矢量。 为每个输入视频帧确定的加权系数被组合以确定优值函数值。 提供最小优值函数值的候选场景边界被指定为场景边界位置。

公开(公告)号：US08786889B2

公开(公告)日：2014-07-22

申请号：US13598310

申请日：2012-08-29

申请人： Minwoo Park ,  Dhiraj Joshi ,  Alexander C. Loui

发明人： Minwoo Park ,  Dhiraj Joshi ,  Alexander C. Loui

IPC分类号： G06K15/00 ,  G06F3/12 ,  G06K9/20 ,  G06K9/34

CPC分类号： G09G5/006 ,  G09G5/26 ,  G09G5/40 ,  G09G2340/10 ,  H04L51/32

摘要： Computing a scale factor to insert a first set of shapes into a second set of shapes to form a combined image includes receiving the two sets of shapes, using a processor to convert the first set of shapes into a set of rectangles and the second set of shapes into a set of intervals and computing the scale factor for either the set of intervals or the set of rectangles to generate the combined image by iteratively inserting the set of rectangles into the set of intervals and updating the scale factor in response to a residual area or an overflow area until all the rectangles in the set of rectangles have been inserted into the set of intervals and the residual area in the set of intervals is below a threshold, and storing the combined image in memory.

摘要翻译： 计算比例因子以将第一组形状插入到第二组形状中以形成组合图像包括使用处理器来接收两组形状，以将第一组形状转换为一组矩形，并且第二组 形成一组间隔，并且通过迭代地将该组矩形迭代地插入到该组间隔中并且响应于剩余区域更新比例因子来计算间隔集合或矩形集合的比例因子以生成组合图像 或溢出区域，直到该组矩形中的所有矩形已经被插入到该组间隔中，并且该间隔集合中的剩余区域低于阈值，并将组合的图像存储在存储器中。

公开(公告)号：US20140063555A1

公开(公告)日：2014-03-06

申请号：US13598202

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

IPC分类号： G06K9/36 ,  G06K15/02

CPC分类号： G06T11/60 ,  G06F17/211

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 method further includes receiving at least one closed shape corresponding to a space for the tag layout. A processor computes a scale factor for at least one of the closed shape or the size of the text labels in the set of tags to generate the tag layout of the set of tags within the closed shape such that all the tags in the set of tags fit within the closed shape and the tags are placed in the space based at least upon the ordering of the tags in the set of tags.

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。 该方法还包括接收与用于标签布局的空间相对应的至少一个封闭形状。 处理器为标签集合中的文本标签的封闭形状或大小中的至少一个计算缩放因子，以生成封闭形状内的标签组的标签布局，使得标签集合中的所有标签 适合于封闭形状，并且标签至少基于标签组中的标签的顺序放置在空间中。

公开(公告)号：US20130235275A1

公开(公告)日：2013-09-12

申请号：US13413982

申请日：2012-03-07

申请人： Mrityunjay Kumar ,  Abdolreza Abdolhosseini Moghadam ,  Alexander C. Loui ,  Jiebo Luo

发明人： Mrityunjay Kumar ,  Abdolreza Abdolhosseini Moghadam ,  Alexander C. Loui ,  Jiebo Luo

IPC分类号： H04N5/14

CPC分类号： H04N5/144 ,  G11B27/28 ,  H04N21/44008 ,  H04N21/8549

摘要： A method for determining a scene boundary location dividing a first scene and a second scene in an input video sequence. The scene boundary location is determined responsive to a merit function value, which is a function of the candidate scene boundary location. The merit function value for a particular candidate scene boundary location is determined by representing the dynamic scene content for the input video frames before and after candidate scene boundary using sparse combinations of a set of basis functions, wherein the sparse combinations of the basis functions are determined by finding a sparse vector of weighting coefficients for each of the basis functions. The weighting coefficients determined for each of the input video frames are combined to determine the merit function value. The candidate scene boundary providing the smallest merit function value is designated to be the scene boundary location.

摘要翻译： 一种用于确定在输入视频序列中划分第一场景和第二场景的场景边界位置的方法。 响应于作为候选场景边界位置的函数的优值函数值确定场景边界位置。 通过使用一组基函数的稀疏组合表示候选场景边界之前和之后的输入视频帧的动态场景内容来确定特定候选场景边界位置的优值函数值，其中确定基函数的稀疏组合 通过找出每个基本函数的加权系数的稀疏矢量。 为每个输入视频帧确定的加权系数被组合以确定优值函数值。 提供最小优值函数值的候选场景边界被指定为场景边界位置。

公开(公告)号：US20130051670A1

公开(公告)日：2013-02-28

申请号：US13221078

申请日：2011-08-30

申请人： Madirakshi Das ,  Alexander C. Loui

发明人： Madirakshi Das ,  Alexander C. Loui

IPC分类号： G06K9/46

CPC分类号： G06K9/6212 ,  G06F17/30056 ,  G06F17/30265

摘要： A method of identifying groups of related digital images in a digital image collection, comprising: analyzing each of the digital images to generate associated feature descriptors related to image content or image capture conditions; storing the feature descriptors associated with the digital images in a metadata database; automatically analyzing the metadata database to identify a plurality of frequent itemsets, wherein each of the frequent itemsets is a co-occurring feature descriptor group that occurs in at least a predefined fraction of the digital images; determining a probability of occurrence for each the identified frequent itemsets; determining a quality score for each of the identified frequent itemsets responsive to the determined probability of occurrence; ranking the frequent itemsets based at least on the determined quality scores; and identifying one or more groups of related digital images corresponding to one or more of the top ranked frequent itemsets.

摘要翻译： 一种在数字图像集合中识别相关数字图像组的方法，包括：分析每个数字图像以生成与图像内容或图像捕获条件相关的相关联的特征描述符; 将与数字图像相关联的特征描述符存储在元数据数据库中; 自动分析所述元数据数据库以识别多个频繁项集，其中所述频繁项集中的每一个是发生在所述数字图像的至少预定义分数中的共同出现的特征描述符组; 确定每个所识别的频繁项集的出现概率; 响应于所确定的发生概率，确定每个所识别的频繁项集的质量得分; 至少基于确定的质量得分对频繁项集进行排序; 以及识别与一个或多个最高排名的频繁项集相对应的一组或多组相关数字图像。

公开(公告)号：US20120281969A1

公开(公告)日：2012-11-08

申请号：US13099391

申请日：2011-05-03

申请人： Wei Jiang ,  Alexander C. Loui ,  Courtenay Cotton

发明人： Wei Jiang ,  Alexander C. Loui ,  Courtenay Cotton

IPC分类号： G11B27/00

CPC分类号： G11B27/034 ,  G11B27/11

摘要： A method for producing an audio-visual slideshow for a video sequence having an audio soundtrack and a corresponding video track including a time sequence of image frames, comprising: segmenting the audio soundtrack into a plurality of audio segments; subdividing the audio segments into a sequence of audio frames; determining a corresponding audio classification for each audio frame; automatically selecting a subset of the audio segments responsive to the audio classification for the corresponding audio frames; for each of the selected audio segments automatically analyzing the corresponding image frames to select one or more key image frames; merging the selected audio segments to form an audio summary; forming an audio-visual slideshow by combining the selected key frames with the audio summary, wherein the selected key frames are displayed synchronously with their corresponding audio segment; and storing the audio-visual slideshow in a processor-accessible storage memory.

摘要翻译： 一种用于产生具有音频声轨和包括图像帧的时间序列的对应视频轨迹的视频序列的视听幻灯片放映方法，包括：将所述音频音轨分割为多个音频段; 将音频段细分成音频帧序列; 确定每个音频帧的相应音频分类; 响应于相应音频帧的音频分类自动选择音频段的子集; 对于每个所选择的音频片段，自动分析对应的图像帧以选择一个或多个关键图像帧; 合并所选音频片段以形成音频摘要; 通过将所选择的关键帧与音频摘要组合来形成视听幻灯片，其中所选择的关键帧与其对应的音频片段同步显示; 以及将视听幻灯片放映在处理器可访问的存储存储器中。

公开(公告)号：US20120275701A1

公开(公告)日：2012-11-01

申请号：US13094217

申请日：2011-04-26

申请人： Minwoo Park ,  Alexander C. Loui ,  Mrityunjay Kumar

发明人： Minwoo Park ,  Alexander C. Loui ,  Mrityunjay Kumar

IPC分类号： G06K9/34

CPC分类号： G06K9/4671 ,  G06K9/34 ,  G06T7/11 ,  G06T7/162 ,  G06T2207/20072 ,  G06T2207/20164

摘要： A method for identifying high saliency regions in a digital image, comprising: segmenting the digital image into a plurality of segmented regions; determining a saliency value for each segmented region, merging neighboring segmented regions that share a common boundary in response to determining that one or more specified merging criteria are satisfied; and designating one or more of the segmented regions to be high saliency regions. The determination of the saliency value for a segmented region includes: determining a surround region including a set of image pixels surrounding the segmented region; analyzing the image pixels in the segmented region to determine one or more segmented region attributes; analyzing the image pixels in the surround region to determine one or more corresponding surround region attributes; determining a region saliency value responsive to differences between the one or more segmented region attributes and the corresponding surround region attributes.

摘要翻译： 一种用于识别数字图像中的高显着区域的方法，包括：将所述数字图像分割成多个分割区域; 确定每个分段区域的显着值，以响应于确定满足一个或多个指定的合并标准来合并共享公共边界的相邻分割区域; 并且将一个或多个分割区域指定为高显着区域。 分割区域的显着性值的确定包括：确定围绕分割区域的一组图像像素的环绕区域; 分析分割区域中的图像像素以确定一个或多个分段区域属性; 分析环绕区域中的图像像素以确定一个或多个相应的环绕区域属性; 响应于所述一个或多个分段区域属性和对应的环绕区域属性之间的差异来确定区域显着值。

公开(公告)号：US20120203764A1

公开(公告)日：2012-08-09

申请号：US13021188

申请日：2011-02-04

申请人： Mark D. Wood ,  Alexander C. Loui

发明人： Mark D. Wood ,  Alexander C. Loui

IPC分类号： G06F17/30

CPC分类号： G06F17/30867 ,  G06F17/30244 ,  G06F17/30247 ,  G06F17/30268 ,  G06F17/30525 ,  G06F17/3074 ,  G06F17/30781 ,  G06F17/30997

摘要： A method of identifying one or more particular images from an image collection, includes indexing the image collection to provide image descriptors for each image in the image collection such that each image is described by one or more of the image descriptors; receiving a query from a user specifying at least one keyword for an image search; and using the keyword(s) to search a second collection of tagged images to identify co-occurrence keywords. The method further includes using the identified co-occurrence keywords to provide an expanded list of keywords; using the expanded list of keywords to search the image descriptors to identify a set of candidate images satisfying the keywords; grouping the set of candidate images according to at least one of the image descriptors, and selecting one or more representative images from each grouping; and displaying the representative images to the user.

摘要翻译： 一种从图像集合识别一个或多个特定图像的方法，包括索引图像集合以为图像集合中的每个图像提供图像描述符，使得每个图像由一个或多个图像描述符描述; 从用户接收指定用于图像搜索的至少一个关键字的查询; 以及使用关键字搜索标记图像的第二集合以识别同现关键字。 该方法还包括使用所识别的同现关键词来提供扩展的关键字列表; 使用扩展的关键字列表来搜索图像描述符以识别满足关键词的一组候选图像; 根据至少一个图像描述符对候选图像集合进行分组，并从每个分组中选择一个或多个代表图像; 并向用户显示代表图像。