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    • 3. 发明授权
    • Interactive framework for understanding user's perception of multimedia data
    • 用于了解用户对多媒体数据的感知的交互框架
    • US06408293B1
    • 2002-06-18
    • US09328968
    • 1999-06-09
    • Gaurav AggarwalPradeep Kumar DubeySugata GhosalAshutosh KulshreshthaTumkur Venkatanarayana Rao Ravi
    • Gaurav AggarwalPradeep Kumar DubeySugata GhosalAshutosh KulshreshthaTumkur Venkatanarayana Rao Ravi
    • G06F1730
    • G06F17/30256Y10S707/99933Y10S707/99935Y10S707/99943
    • A methodology of highly interactive intra-object relevance feedback is used to retrieve multimedia data from a database. The query object could consist of one or more images, images derived from video, a video sequence, or an audio clip. The query is adjusted using the information fed-back by the user about the relevance of previously extracted part(s) from the object itself, such that the adjusted query is a better approximation to the user's perception. The information fed-back by the user during intra-query modification is used for intra-object learning of the user's perception. The refined query is subsequently used for inter-object relevance feedback where data is retrieved from the database based on parameters learnt by intra-query object feedback mechanism, and the user provides feedback by ranking the retrieved objects in order of their relevance to him or her. In the system according to the invention, inter-object learning of user's perception is expedited by utilizing the learnt parameters in the intra-object relevance feedback. Furthermore, the methodology of the invention allows for building refined queries based on part(s) or sub-sequence(s) of the query object rather than the entire object itself, thereby reducing the number of irrelevant objects, retrieved from the database. The methodology allows synthesis and modification of the input query object itself in the event a query object is not directly available, and, also to learn the user's perception.
    • 高度交互的对象内相关反馈的方法用于从数据库检索多媒体数据。 查询对象可以包括一个或多个图像,从视频,视频序列或音频剪辑导出的图像。 使用用户反馈的关于先前提取的部分与对象本身的相关性的信息来调整查询,使得经调整的查询更好地逼近用户的感知。 用户在查询修改期间反馈的信息用于用户感知的对象内学习。 精确查询随后用于对象间相关性反馈,其中基于由查询内对象反馈机制学习的参数从数据库检索数据,并且用户按照与他或她的相关性的顺序对所检索的对象进行排序来提供反馈 。 在根据本发明的系统中,通过利用对象内相关性反馈中的学习参数来加快用户感知的对象间学习。 此外,本发明的方法允许基于查询对象的部分或子序列而不是整个对象本身构建精简查询,从而减少从数据库检索的不相关对象的数量。 该方法允许在查询对象不直接可用的情况下对输入查询对象本身进行合成和修改,还可以了解用户的感知。
    • 4. 发明授权
    • Semi-fragile watermarks
    • 半脆弱水印
    • US06834344B1
    • 2004-12-21
    • US09398203
    • 1999-09-17
    • Gaurav AggarwalPradeep K. DubeyAshutosh KulshreshthaMarco MartensCharles P. TresserChai W. Wu
    • Gaurav AggarwalPradeep K. DubeyAshutosh KulshreshthaMarco MartensCharles P. TresserChai W. Wu
    • H04L900
    • G06T1/005G06T1/0042H04N1/32144H04N1/32154H04N2201/327
    • A method is presented for marking high-quality digital images with a robust and invisible watermark. It requires the mark to survive and remain detectable and authenticatable through all image manipulations that in themselves do not damage the image beyond useability. These manipulations include JPEG “lossy” compression and, in the extreme, the printing and rescanning of the image. The watermark also has the property that it can detect if the essential contents of the image has changed. The first phase of the method comprises extracting a digest or number N from the image so that N only (or mostly) depends on the essential information content, such that the same number N can be obtained from a scan of a high quality print of the image, from the compressed form of the image, or in general, from the image after minor modifications (introduced inadvertently by processing, noise etc.). The second phase comprises the marking. This can be done in form of an invisible robust watermark, or in form of some visible signature or watermark.
    • 提出了一种用强大且不可见的水印标记高质量数字图像的方法。 它需要标记生存,并通过所有图像操作保持可检测和可认证,这本身不会损害图像超出可用性。 这些操作包括JPEG“有损”压缩,在极端情况下,打印和重新扫描图像。 该水印还具有可以检测图像的基本内容是否已改变的属性。 该方法的第一阶段包括从图像中提取摘要或数字N,使得仅N(或主要地)取决于基本信息内容,使得可以从扫描的高质量打印获得相同数量N 图像,从图像的压缩形式,或一般来说,从稍后修改的图像(通过处理,噪声等无意中引入)。 第二阶段包括标记。 这可以以不可见的鲁棒水印的形式或以一些可见的签名或水印的形式来完成。
    • 5. 发明授权
    • Method for controlled and meaningful shape modifications
    • 控制和有意义的形状修改的方法
    • US06625330B1
    • 2003-09-23
    • US09516142
    • 2000-03-01
    • Pradeep Kumar DubeySugata GhosalAshutosh KulshreshthaAbhinanda Sarkar
    • Pradeep Kumar DubeySugata GhosalAshutosh KulshreshthaAbhinanda Sarkar
    • G06K932
    • G06K9/6204
    • A method of doing meaningful modifications on an image is presented. These modifications can then be used in variety of applications related to image shape manipulation and similar shape retrieval. The method extracts macrofeatures and microfeature from a given shape. Deformations are done on the macrofeatures only. These deformations are either predefined, or are taken from a deformation library, or are calculated from the shape itself, The microfeatures are then added to the deformed macrofeatures to get a deformed shape. The shape deformations then allow user's perception of shape similarity to be learned, which is reflected in the values of parameters in a parameterized shape similarity metric. The user can use one of the deformed shapes as the initial query point, instead of the shape he or she started with. The shape database compression is achieved by storing only the identification of a similar shape and value of global deformations which will generate this shape approximately, instead of storing every shape feature individually.
    • 提出了对图像进行有意义的修改的方法。 然后,这些修改可用于与图像形状操纵和类似形状检索有关的各种应用。 该方法从给定的形状提取宏特征和微特征。 变形仅在宏观特征上进行。 这些变形是预定义的,或者是从变形库中获取的,或者是根据形状本身计算的。然后将微特征加到变形的宏观特征中以得到变形的形状。 形状变形然后允许用户对形状相似度的感知被学习,这反映在参数化形状相似性度量中的参数值中。 用户可以使用其中一个变形的形状作为初始查询点,而不是他或她开始的形状。 形状数据库压缩是通过仅存储将产生该形状的全局变形的类似形状和值的识别来实现的,而不是分别存储每个形状特征。
    • 8. 发明授权
    • Map spam detection
    • 地图垃圾邮件检测
    • US08694489B1
    • 2014-04-08
    • US12896240
    • 2010-10-01
    • Baris YukselAshutosh Kulshreshtha
    • Baris YukselAshutosh Kulshreshtha
    • G06F7/00G06F17/30
    • G06Q30/02G06F17/3087
    • A determination of whether a mapped business listing that is produced as a search result corresponds to an actual location of operation is based on different factors. One factor identifies whether the business listing is associated with a business category that appears as search results for a particular geographic area in numbers that exceed average proportions for the same business category density in similarly situated geographic areas. Another factor determines whether different business listings in the same geographic area include the same identifying data. Specific characteristics of a neighborhood where the business listing is mapped provide an additional factor for identifying whether a search result for a business listing is map spam. The different factors may be considered together to determine the likelihood that a mapped search result is spam.
    • 确定作为搜索结果生成的映射业务列表是否与实际操作位置相对应是基于不同的因素。 一个因素是确定业务列表是否与业务类别相关联,该业务类别作为特定地理区域的搜索结果显示,该业务类别的数量超过了类似位置的地理区域中相同业务类别密度的平均比例。 另一个因素决定了相同地理区域中的不同商家列表是否包含相同的标识数据。 业务列表映射的邻域的具体特征提供了用于识别商业列表的搜索结果是否是垃圾邮件的附加因素。 可以一起考虑不同的因素以确定映射的搜索结果是垃圾邮件的可能性。