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公开(公告)号：US08699852B2
公开(公告)日：2014-04-15
申请号：US13269753
申请日：2011-10-10
申请人： Wei Jiang , Alexander C. Loui
发明人： Wei Jiang , Alexander C. Loui
IPC分类号： H04N5/92
CPC分类号： H04N21/8405 , G06F17/30784 , G06K9/00718 , G06K9/00744 , H04N21/2743 , H04N21/4332 , H04N21/44008
摘要： A method for determining a semantic concept classification for a digital video clip, comprising: receiving an audio-visual dictionary including a plurality of audio-visual grouplets, the audio-visual grouplets including visual background and foreground codewords, audio background and foreground codewords, wherein the codewords in a particular audio-visual grouplet were determined to be correlated with each other; determining reference video codeword similarity scores for a set of reference video clips; determining codeword similarity scores for the digital video clip; determining a reference video similarity score for each reference video clip representing a similarity between the digital video clip and the reference video clip responsive to the audio-visual grouplets, the codeword similarity scores and the reference video codeword similarity scores; and determining one or more semantic concept classifications using trained semantic classifiers responsive to the determined reference video similarity scores.
摘要翻译： 一种用于确定数字视频剪辑的语义概念分类的方法，包括：接收包括多个视听小组的视听词典，所述视听小组包括视觉背景和前景码字，音频背景和前景码字，其中 确定特定视听小组中的码字彼此相关; 确定一组参考视频剪辑的参考视频码字相似性得分; 确定所述数字视频剪辑的码字相似性得分; 响应于所述视听小组，所述码字相似度得分和所述参考视频码字相似性得分，确定表示所述数字视频剪辑和所述参考视频剪辑之间的相似性的每个参考视频剪辑的参考视频相似性分数; 以及响应于所确定的参考视频相似性分数，使用经过训练的语义分类器来确定一个或多个语义概念分类。
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公开(公告)号：US20140063536A1
公开(公告)日：2014-03-06
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
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。
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公开(公告)号：US08625904B2
公开(公告)日：2014-01-07
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： G06K9/68
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; 自动分析元数据数据库以识别多个频繁项集，其中每个频繁项集是在数字图像的至少预定义分数中出现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。
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公开(公告)号：US08611677B2
公开(公告)日：2013-12-17
申请号：US12273600
申请日：2008-11-19
申请人： Madirakshi Das , Alexander C. Loui , Mark D. Wood
发明人： Madirakshi Das , Alexander C. Loui , Mark D. Wood
CPC分类号： G06F17/30598 , G06F17/30247 , G06F17/30265 , G06K9/00664
摘要： A method of automatically classifying images in a consumer digital image collection, includes generating an event representation of the image collection; computing global time-based features for each event within the hierarchical event representation; computing content-based features for each image in an event within the hierarchical event representation; combining content-based features for each image in an event to generate event-level content-based features; and using time-based features and content-based features for each event to classify an event into one of a pre-determined set of semantic categories.
摘要翻译： 一种在消费者数字图像集合中自动分类图像的方法，包括：生成图像集合的事件表示; 计算分层事件表示中每个事件的全局时基特征; 在层次事件表示内的事件中计算每个图像的基于内容的特征; 在事件中为每个图像组合基于内容的特征以生成基于事件级的基于内容的特征; 以及为每个事件使用基于时间的特征和基于内容的特征来将事件分类成预定义的语义类别集合之一。
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公开(公告)号：US20130251340A1
公开(公告)日：2013-09-26
申请号：US13425455
申请日：2012-03-21
申请人： Wei Jiang , Alexander C. Loui
发明人： Wei Jiang , Alexander C. Loui
IPC分类号： H04N5/91
CPC分类号： G06K9/00718 , G06K9/00744 , G06K9/4676
摘要： A method for determining a semantic concept classification for a digital video clip based on a grouplet dictionary that includes a plurality of temporally-correlated grouplets. The temporally-correlated grouplets include textual codewords and either visual codewords or audio codewords, wherein the codewords in a particular temporally-correlated grouplet were determined to be correlated with each other based on analysis of a set of training videos. Reference video codeword similarity scores are determined for a set of reference video clips, and codeword similarity scores are determined for the digital video clip. A reference video similarity score is determined for each reference video clip representing a similarity between the digital video clip and the reference video clip based on the reference video codeword similarity scores, the codeword similarity scores, and the temporally-correlated grouplets. One or more semantic concept classifications are determined using trained semantic classifiers responsive to the determined reference video similarity scores.
摘要翻译： 一种用于基于包括多个时间相关小区的小组字典来确定数字视频剪辑的语义概念分类的方法。 时间相关小区包括文本码字和视觉码字或音频码字，其中基于一组训练视频的分析，将特定时间相关小区小区中的码字确定为彼此相关。 对于一组参考视频剪辑确定参考视频码字相似性分数，并且为数字视频剪辑确定码字相似性分数。 基于参考视频码字相似度分数，码字相似度分数和时间相关小区，为表示数字视频剪辑和参考视频剪辑之间的相似性的每个参考视频剪辑确定参考视频相似性分数。 响应于所确定的参考视频相似性分数，使用经过训练的语义分类器来确定一个或多个语义概念分类。
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公开(公告)号：US20130089303A1
公开(公告)日：2013-04-11
申请号：US13269742
申请日：2011-10-10
申请人： Wei Jiang , Alexander C. Loui
发明人： Wei Jiang , Alexander C. Loui
IPC分类号： H04N5/93
CPC分类号： H04N5/93 , G11B27/28 , H04N21/233 , H04N21/23418
摘要： A method for determining a semantic concept classification for a digital video clip, comprising: receiving an audio-visual dictionary including a plurality of audio-visual grouplets, the audio-visual grouplets including visual background and foreground codewords, audio background and foreground codewords, wherein the codewords in a particular audio-visual grouplet were determined to be correlated with each other; analyzing the digital video clip to determine a set of visual features and a set of audio features; determining similarity scores between the digital video clip and each of the audio-visual grouplets by comparing the set of visual features to any visual background and foreground codewords associated with a particular audio-visual grouplet, and comparing the set of audio features to any audio background and foreground codewords associated with the particular audio-visual grouplet; and determining one or more semantic concept classifications using trained semantic classifiers.
摘要翻译： 一种用于确定数字视频剪辑的语义概念分类的方法，包括：接收包括多个视听小组的视听词典，所述视听小组包括视觉背景和前景码字，音频背景和前景码字，其中 确定特定视听小组中的码字彼此相关; 分析数字视频剪辑以确定一组视觉特征和一组音频特征; 通过将视觉特征的集合与与特定视听小组相关联的任何视觉背景和前景码字进行比较，以及将该组音频特征与任何音频背景进行比较来确定数字视频剪辑和每个视听小组之间的相似性得分 以及与特定视听小组相关联的前景码字; 以及使用经训练的语义分类器确定一个或多个语义概念分类。
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公开(公告)号：US08401292B2
公开(公告)日：2013-03-19
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。
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公开(公告)号：US08213725B2
公开(公告)日：2012-07-03
申请号：US12408140
申请日：2009-03-20
申请人： Alexander C. Loui , Wei Jiang
发明人： Alexander C. Loui , Wei Jiang
IPC分类号： G06K9/62
CPC分类号： G06F17/30256 , G06F17/30802 , G06F17/30805 , G06F17/30808 , G06K9/00664 , G06K9/00711
摘要： A method for facilitating semantic event classification of a group of image records related to an event. The method using an event detector system for providing: extracting a plurality of visual features from each of the image records; wherein the visual features include segmenting an image record into a number of regions, in which the visual features are extracted; generating a plurality of concept scores for each of the image records using the visual features, wherein each concept score corresponds to a visual concept and each concept score is indicative of a probability that the image record includes the visual concept; generating a feature vector corresponding to the event based on the concept scores of the image records; and supplying the feature vector to an event classifier that identifies at least one semantic event classifier that corresponds to the event.
摘要翻译： 一种用于促进与事件相关的一组图像记录的语义事件分类的方法。 该方法使用事件检测器系统来提供：从每个图像记录提取多个视觉特征; 其中所述视觉特征包括将图像记录分割成其中提取所述视觉特征的多个区域; 使用所述视觉特征为每个所述图像记录生成多个概念分数，其中每个概念分数对应于视觉概念，并且每个概念分数指示所述图像记录包括所述视觉概念的概率; 基于所述图像记录的概念分数生成与所述事件相对应的特征向量; 以及将特征向量提供给识别与该事件相对应的至少一个语义事件分类器的事件分类器。
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公开(公告)号：US20110081082A1
公开(公告)日：2011-04-07
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。
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公开(公告)号：US20100124378A1
公开(公告)日：2010-05-20
申请号：US12273600
申请日：2008-11-19
申请人： Madirakshi Das , Alexander C. Loui , Mark D. Wood
发明人： Madirakshi Das , Alexander C. Loui , Mark D. Wood
IPC分类号： G06K9/62
CPC分类号： G06F17/30598 , G06F17/30247 , G06F17/30265 , G06K9/00664
摘要： A method of automatically classifying images in a consumer digital image collection, includes generating an event representation of the image collection; computing global time-based features for each event within the hierarchical event representation; computing content-based features for each image in an event within the hierarchical event representation; combining content-based features for each image in an event to generate event-level content-based features; and using time-based features and content-based features for each event to classify an event into one of a pre-determined set of semantic categories.
摘要翻译： 一种在消费者数字图像集合中自动分类图像的方法，包括生成图像集合的事件表示; 计算分层事件表示中每个事件的全局时基特征; 在层次事件表示内的事件中计算每个图像的基于内容的特征; 在事件中为每个图像组合基于内容的特征以生成基于事件级的基于内容的特征; 以及为每个事件使用基于时间的特征和基于内容的特征来将事件分类成预定义的语义类别集合之一。
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