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    • 2. 发明申请
    • METHOD AND SYSTEM FOR MULTI-OBJECT TRACKING
    • 用于多目标跟踪的方法和系统
    • WO2008008046A1
    • 2008-01-17
    • PCT/SG2007/000206
    • 2007-07-11
    • AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCHLI, LiyuanLUO, RuijiangMA, RuihuaLEMAN, KariantoKUMAR, PankajLEE, Beng HaiHUANG, Welmin
    • LI, LiyuanLUO, RuijiangMA, RuihuaLEMAN, KariantoKUMAR, PankajLEE, Beng HaiHUANG, Welmin
    • G06K9/00
    • H04N7/18G06K9/00771G06K9/32G06K9/38G06K2009/3291G06T5/50G06T7/11G06T7/174G06T7/194G06T7/254G06T2207/10016G06T2207/20081
    • A method and system for multi-object tracking in a video signal. The method comprises the steps of receiving first and second segmented images of two consecutive frames of the video signal respectively, at least one of the first and second segmented images including one or more foreground regions, each foreground region corresponding to one or more objects to be tracked; generating one or more directed acrylic graphs (DAGs) for zero or more parent nodes in the first segmented image and zero to more child nodes in the second segmented images, each DAG including at least one parent or child node; and for each parent node having two or more child nodes, a) sorting the corresponding objects of the foreground region contributing to said each parent node according to estimated depth in said first image; b) assigning the corresponding object having the lowest depth to one of the child nodes of said each parent node; c) removing a visual content of the assigned corresponding object from the visual data associated with said one child node; and iterating steps b) to c) in order of increasing depth of the corresponding objects for assigning all corresponding objects to the two or more child nodes; and then for each child node having only one corresponding object assigned thereto, update a state and the visual content of said one object based on the second image; for each child node having two or more corresponding objects assigned thereto, d) sorting the corresponding objects according to estimated depth in said ech child node in said second image; e) applying a means-shift calculation to locate the corresponding object having the lowest depth in said each child node; f) updating the state and the visual content of the located corresponding object based on the second image; g) removing the updated visual content of the located corresponding object from the visual data associated with said each child node; and iterating steps e) to g) in order of increasing depth of the corresponding objects for locating all corresponding objects in a corresponding region of said each child node.
    • 一种用于视频信号中多目标跟踪的方法和系统。 该方法包括以下步骤:分别接收视频信号的两个连续帧的第一和第二分割图像,第一和第二分割图像中的至少一个包括一个或多个前景区域,每个前景区域对应于一个或多个对象 跟踪; 为所述第一分割图像中的零个或多个父节点生成一个或多个定向丙烯酸图(DAG),并且在所述第二分割图像中生成零到更多子节点,每个DAG包括至少一个父节点或子节点; 并且对于具有两个或更多个子节点的每个父节点,a)根据所述第一图像中的估计深度对对所述每个父节点贡献的前景区域的对应对象进行排序; b)将具有最低深度的相应对象分配给所述每个父节点的子节点之一; c)从与所述一个子节点相关联的视觉数据中去除所分配的对应对象的视觉内容; 并且按照对应对象的深度增加的顺序迭代步骤b)至c),以将所有对应的对象分配给两个或多个子节点; 然后对于仅分配了一个对应对象的每个子节点,基于第二图像更新所述一个对象的状态和视觉内容; 对于具有分配给其的两个或更多个对应对象的每个子节点,d)根据所述第二图像中所述ech子节点中估计的深度对相应对象进行排序; e)应用平均移位计算来定位所述每个子节点中具有最低深度的相应对象; f)基于第二图像来更新所定位的相应对象的状态和视觉内容; g)从与所述每个子节点相关联的视觉数据中去除所定位的对应对象的更新的可视内容; 以及迭代步骤e)至g)按照用于定位所述每个子节点的对应区域中的所有相应对象的相应对象的深度的顺序。
    • 4. 发明申请
    • OBTAINING DATA FOR AUTOMATIC GLAUCOMA SCREENING, AND SCREENING AND DIAGNOSTIC TECHNIQUES AND SYSTEMS USING THE DATA
    • 获取用于自动GLAUCOMA筛选的数据,以及使用数据的筛选和诊断技术和系统
    • WO2011059409A1
    • 2011-05-19
    • PCT/SG2010/000434
    • 2010-11-16
    • LIU, JiangZHANG, ZhuoWONG, Wing, Kee, DamonTAN, Ngan, MengYIN, FengshouLEE, Beng HaiLI, HuiqiLIM, Joo, HweeCHEUNG, CarolAUNG, TinWONG, Tien, YinLIANG, ZiyangCHENG, JunMANI, Baskaran
    • LIU, JiangZHANG, ZhuoWONG, Wing, Kee, DamonTAN, Ngan, MengYIN, FengshouLEE, Beng HaiLI, HuiqiLIM, Joo, HweeCHEUNG, CarolAUNG, TinWONG, Tien, YinLIANG, ZiyangCHENG, JunMANI, Baskaran
    • A61B3/12
    • A61B3/0025A61B3/12A61B5/02007A61B5/7264A61B5/7267A61B5/7275G06T7/0012G06T7/40G06T2207/30041
    • A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode. Texture analysis is performed on the fundus images to classify them based on their quality, and only images which are determined to meet a quality criterion are subjected to an analysis to determine if they exhibit glaucoma indicators. Also, the images are put into a standard format. The system may include estimating the position of the optic cup by combining results from multiple optic cup segmentation techniques. The system may include estimating the position of the optic disc by applying edge detection to the funds image, excluding edge points that are unlikely to be optic disc boundary points, and estimating the position of an optic disc by fitting an ellipse to the remaining edge points.
    • 使用非立体眼底图像来获得多个青光眼指示符。 此外,用于受试者的基因组数据用于获得与与青光眼相关的一个或多个基因和/或SNP相关的遗传标记数据。 青光眼指标和遗传标记数据被输入到适应模型中,该模型用于产生指示受试者青光眼风险的输出。 综合来看,遗传指标和基因组数据对于青光眼的风险比孤立的两者之一更有信息。 自适应模型可以是两阶段模型,其具有第一阶段,其中通过第一自适应模型模块将个体遗传指标与基因组数据的相应部分组合以形成相应的第一输出,第二阶段中,第一输出是 通过第二自适应模式组合。 对眼底图像进行纹理分析,根据其质量对其进行分类,仅对满足质量标准的图像进行分析,以确定其是否呈现青光眼指标。 此外,图像被放入标准格式。 该系统可以包括通过组合来自多个光学杯分割技术的结果来估计光学杯的位置。 该系统可以包括通过对资金图像应用边缘检测来估计视盘的位置,不包括不太可能是视盘边界点的边缘点,以及通过将椭圆拟合到剩余边缘点来估计视盘的位置 。