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    • 81. 发明授权
    • Identifying high saliency regions in digital images
    • 识别数字图像中的高显着区域
    • US08401292B2
    • 2013-03-19
    • US13094217
    • 2011-04-26
    • Minwoo ParkAlexander C. LouiMrityunjay Kumar
    • Minwoo ParkAlexander C. LouiMrityunjay Kumar
    • G06K9/34
    • G06K9/4671G06K9/34G06T7/11G06T7/162G06T2207/20072G06T2207/20164
    • 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.
    • 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。
    • 87. 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
    • System and method to compose a slide show
    • 组合幻灯片的系统和方法
    • US07394969B2
    • 2008-07-01
    • US10316556
    • 2002-12-11
    • Zhaohui SunAlexander C. LouiJonathan K. Riek
    • Zhaohui SunAlexander C. LouiJonathan K. Riek
    • H04N5/91
    • G06F17/30056G11B27/034G11B2220/2545G11B2220/2562H04N5/765H04N5/775H04N5/781H04N5/85H04N5/907
    • A method of composing a multimedia slide show. In a preferred embodiment, the method comprises the steps of: selecting a plurality of digital images; encoding each of the plurality of digital images to generate a normal resolution image portion and a high resolution image portion; multiplexing each corresponding normal and high resolution image portion to generate a single high resolution still image; determining a time parameter for each of the high resolution still images; selecting an audio portion for at least one of the plurality of digital images; concatenating the plurality of high resolution still images to generate a video bitstream; generating an audio bitstream by encoding the audio portion; and multiplexing the video bitstream and audio bitstream to generate the multimedia slide show.
    • 组合多媒体幻灯片的方法。 在优选实施例中,该方法包括以下步骤:选择多个数字图像; 编码所述多个数字图像中的每一个以生成正常分辨率图像部分和高分辨率图像部分; 复用每个对应的正常和高分辨率图像部分以产生单个高分辨率静止图像; 确定每个所述高分辨率静止图像的时间参数; 为所述多个数字图像中的至少一个选择音频部分; 连接多个高分辨率静止图像以产生视频位流; 通过对音频部分进行编码来产生音频比特流; 并且多路复用视频比特流和音频比特流以产生多媒体幻灯片放映。
    • 90. 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。