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    • 82. 发明授权
    • Semantic event detection using cross-domain knowledge
    • 使用跨域知识的语义事件检测
    • US08213725B2
    • 2012-07-03
    • US12408140
    • 2009-03-20
    • Alexander C. LouiWei Jiang
    • Alexander C. LouiWei Jiang
    • G06K9/62
    • G06F17/30256G06F17/30802G06F17/30805G06F17/30808G06K9/00664G06K9/00711
    • 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.
    • 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。
    • 83. 发明申请
    • VIDEO CONCEPT CLASSIFICATION USING AUDIO-VISUAL ATOMS
    • 使用音频视频的视频概念分类
    • US20110081082A1
    • 2011-04-07
    • US12574716
    • 2009-10-07
    • Wei JiangCourtenay CottonShih-Fu ChangDaniel P. EllisAlexander C. Loui
    • Wei JiangCourtenay CottonShih-Fu ChangDaniel P. EllisAlexander C. Loui
    • G06K9/00G06K9/62G10L11/00
    • G06K9/00765G10L25/00
    • 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.
    • 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。
    • 86. 发明申请
    • CLASSIFYING COMPLETE AND INCOMPLETE DATE-TIME INFORMATION
    • 分类完整和不完整的日期信息
    • US20080205771A1
    • 2008-08-28
    • US11679914
    • 2007-02-28
    • Bryan D. KrausAlexander C. Loui
    • Bryan D. KrausAlexander C. Loui
    • G06K9/64
    • G06F17/30265G06F17/30247G06F17/3028G06K2209/27
    • A method for automatically classifying images into a final set of events including receiving a first plurality of images having date-time and a second plurality of images with incomplete date-time information; determining one or more time differences of the first plurality of images based on date-time clustering of the images and classify the first plurality of images into a first set of possible events; analyzing the second plurality of images using scene content and metadata cues and selecting images which correspond to different events in the first set of possible events and combining them into their corresponding possible events to thereby produce a second set of possible events; and using image scene content to verify the second set of possible events and to change the classification of images which correspond to different possible events to thereby provide the final set of events.
    • 一种用于将图像自动分类为最终事件集的方法,包括接收具有日期时间的第一多个图像和具有不完整的日期时间信息的第二多个图像; 基于所述图像的日期时间聚类确定所述第一多个图像的一个或多个时间差,并将所述第一多个图像分类为第一组可能事件; 使用场景内容和元数据提示来分析第二多个图像,并且选择对应于第一组可能事件中的不同事件的图像,并将它们组合成其相应的可能事件,从而产生第二组可能事件; 并且使用图像场景内容来验证第二组可能的事件并且改变对应于不同可能事件的图像的分类,从而提供最终的事件集合。
    • 88. 发明授权
    • Video structuring by probabilistic merging of video segments
    • 通过视频段的概率合并来构建视频
    • US07296231B2
    • 2007-11-13
    • US09927041
    • 2001-08-09
    • Alexander C. LouiDaniel Gatica-Perez
    • Alexander C. LouiDaniel Gatica-Perez
    • G06F3/00
    • G06K9/00711G06F17/30802G06F17/30852
    • A method for structuring video by probabilistic merging of video segments includes the steps of obtaining a plurality of frames of unstructured video; generating video segments from the unstructured video by detecting shot boundaries based on color dissimilarity between consecutive frames; extracting a feature set by processing pairs of segments for visual dissimilarity and their temporal relationship, thereby generating an inter-segment visual dissimilarity feature and an inter-segment temporal relationship feature; and merging video segments with a merging criterion that applies a probabilistic analysis to the feature set, thereby generating a merging sequence representing the video structure. The probabilistic analysis follows a Bayesian formulation and the merging sequence is represented in a hierarchical tree structure.
    • 通过视频段的概率合并来构造视频的方法包括以下步骤:获得多个非结构化视频帧; 通过基于连续帧之间的颜色不相似性来检测镜头边界,从非结构化视频生成视频片段; 通过处理用于视觉差异的片段对及其时间关系来提取特征集,由此产生片段间视觉差异特征和片段间时间关系特征; 以及将视频片段与将特征集合应用概率分析的合并标准合并,从而生成表示视频结构的合并序列。 概率分析遵循贝叶斯公式,并且合并序列以分层树结构表示。