公开(公告)号：US20050105764A1

公开(公告)日：2005-05-19

申请号：US10917063

申请日：2004-08-12

申请人： Mei Han ,  Yihong Gong ,  Hai Tao

发明人： Mei Han ,  Yihong Gong ,  Hai Tao

IPC分类号： G01S5/16 ,  G06K9/00 ,  G06T7/20 ,  G08C19/00 ,  H04N5/76 ,  H04N7/18

CPC分类号： G06T7/20 ,  G01S5/16 ,  G06K9/00295 ,  G06K9/00771 ,  G06K9/32 ,  G06T2207/30241 ,  H04N5/76 ,  H04N7/188

摘要： A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and/or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

摘要翻译： 视频监控系统使用基于规则的推理和多重假设评分来根据通过区域模式的移动来检测预定义的行为。 轨迹假设产卵允许轨迹分裂和/或合并，并包括局部修剪以管理假设增长。 假设基于许多标准进行评分，示例性地包括至少一个非空间参数。 在假设产卵过程期间计算的连接概率基于许多标准，示例性地包括对象大小。 对象检测和概率评分说明性地基于对象类。

公开(公告)号：US20050104962A1

公开(公告)日：2005-05-19

申请号：US10917985

申请日：2004-08-12

申请人： Mei Han ,  Yihong Gong ,  Hai Tao

发明人： Mei Han ,  Yihong Gong ,  Hai Tao

IPC分类号： G06K9/00 ,  H04N7/18 ,  H04N9/47

CPC分类号： G06K9/00771 ,  G06K9/00335 ,  G08B13/19608

摘要： A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and/or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

摘要翻译： 视频监控系统使用基于规则的推理和多重假设评分来根据通过区域模式的移动来检测预定义的行为。 轨迹假设产卵允许轨迹分裂和/或合并，并包括局部修剪以管理假设增长。 假设基于许多标准进行评分，示例性地包括至少一个非空间参数。 在假设产卵过程期间计算的连接概率基于许多标准，示例性地包括对象大小。 对象检测和概率评分说明性地基于对象类。

公开(公告)号：US20050104959A1

公开(公告)日：2005-05-19

申请号：US10916966

申请日：2004-08-12

申请人： Mei Han ,  Yihong Gong ,  Hai Tao

发明人： Mei Han ,  Yihong Gong ,  Hai Tao

IPC分类号： G08B13/196 ,  H04N9/47

CPC分类号： G08B13/19652 ,  G08B13/19604 ,  G08B13/19608 ,  G08B13/19615

摘要： A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and/or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

摘要翻译： 视频监控系统使用基于规则的推理和多重假设评分来根据通过区域模式的移动来检测预定义的行为。 轨迹假设产卵允许轨迹分裂和/或合并，并包括局部修剪以管理假设增长。 假设基于许多标准进行评分，示例性地包括至少一个非空间参数。 在假设产卵过程期间计算的连接概率基于许多标准，示例性地包括对象大小。 对象检测和概率评分说明性地基于对象类。

公开(公告)号：US20120053214A1

公开(公告)日：2012-03-01

申请号：US13320203

申请日：2009-05-12

申请人： Mei Han ,  Yan Feng ,  Yuanyuan Sun

发明人： Mei Han ,  Yan Feng ,  Yuanyuan Sun

IPC分类号： A61K31/4245 ,  C12N5/02 ,  A61P9/00 ,  A61P17/00 ,  A61P7/00 ,  A61P25/00 ,  A61P25/28 ,  A61P25/16 ,  A61P25/08 ,  A61P25/22 ,  A61P7/06 ,  A61P35/02 ,  A61P37/00 ,  A61P17/02 ,  C07D271/113

CPC分类号： C07D271/07

摘要： The invention provides small molecule compounds capable of accelerating proliferation of stem cells and uses thereof. The compounds play an important role in the research of stem cell proliferation mechanism. The invention further relates to the uses of the compounds and relevant compounds thereof in the preparation of stem cell proliferation accelerators and the preparation of medicines accelerating stem cell proliferation. The invention also relates to the uses of the compounds in the preparation of medicines for the treatment of various diseases arising from functional cells loss or damage. The diseases arising from stem cell trauma comprise diseases related to the degeneration or damage of nervous system cells, blood system diseases, diseases related to the loss or damage of cardiovascular cells, skin burn and the like.

摘要翻译： 本发明提供能够促进干细胞增殖的小分子化合物及其用途。 该化合物在干细胞增殖机制研究中起着重要作用。 本发明还涉及化合物及其相关化合物在制备干细胞增殖促进剂中的用途以及促进干细胞增殖的药物的制备。 本发明还涉及该化合物在制备用于治疗由功能性细胞损失或损伤引起的各种疾病的药物中的用途。 由干细胞创伤引起的疾病包括与神经系统细胞的退化或损伤相关的疾病，血液系统疾病，与心血管细胞的损失或损伤有关的疾病，皮肤灼伤等。

公开(公告)号：US07976595B2

公开(公告)日：2011-07-12

申请号：US12031180

申请日：2008-02-14

申请人： Xin Wang ,  Minglin Zhang ,  Qingrui Zhu ,  Min Zhu ,  Jiyong Zhang ,  Xinfang Jiang ,  Yifei Zhang ,  Yongkui Sun ,  Mei Han ,  Weihua Zhang

发明人： Xin Wang ,  Minglin Zhang ,  Qingrui Zhu ,  Min Zhu ,  Jiyong Zhang ,  Xinfang Jiang ,  Yifei Zhang ,  Yongkui Sun ,  Mei Han ,  Weihua Zhang

IPC分类号： C01B3/36 ,  C01B6/24 ,  C01B3/02 ,  C01B3/24 ,  C10J3/00 ,  B01J7/00

CPC分类号： C10J3/485 ,  C10J3/503 ,  C10J3/506 ,  C10J3/723 ,  C10J2200/15 ,  C10J2300/093 ,  C10J2300/0959 ,  C10J2300/0973

摘要： A method of gasification burner online feeding for a coal-water slurry gasifier, where a coal-water slurry line and an oxidizer line are both protected by shield gas. The method may realize online, pressurized and continuous feeding of the gasification burners which are fixed after they stalled for other reasons than their own, thus greatly reducing the probability of accidental shutdown of gasifiers and improving the reliability of long-term service of the multi-nozzle opposed gasifier.

摘要翻译： 一种用于水煤浆气化炉的气化燃烧器在线进料方法，其中煤水浆料管线和氧化剂管线均被保护气体保护。 该方法可实现气化燃烧器的在线，加压和连续进料，由于其自​​身的其他原因而停止，从而大大降低了气化器意外关闭的可能性，提高了多功能燃烧器长期服务的可靠性， 喷嘴对置气化器。

公开(公告)号：US07440615B2

公开(公告)日：2008-10-21

申请号：US11553043

申请日：2006-10-26

申请人： Yihong Gong ,  Mei Han ,  Wei Xu

发明人： Yihong Gong ,  Mei Han ,  Wei Xu

IPC分类号： G06K9/34

CPC分类号： G06K9/38 ,  G06T7/12 ,  G06T7/181 ,  G06T7/194 ,  G06T7/215 ,  G06T7/277 ,  G06T2207/10016 ,  H04N7/141

摘要： A fully automatic, computationally efficient segmentation method of video employing sequential clustering of sparse image features. Both edge and corner features of a video scene are employed to capture an outline of foreground objects and the feature clustering is built on motion models which work on any type of object and moving/static camera in which two motion layers are assumed due to camera and/or foreground and the depth difference between the foreground and background. Sequential linear regression is applied to the sequences and the instantaneous replacements of image features in order to compute affine motion parameters for foreground and background layers and consider temporal smoothness simultaneously. The Foreground layer is then extracted based upon sparse feature clustering which is time efficient and refined incrementally using Kalman filtering.

摘要翻译： 一种使用稀疏图像特征的顺序聚类的全自动，计算效率高的视频分割方法。 使用视频场景的边缘和角落特征来捕获前景对象的轮廓，并且特征聚类建立在对任何类型的对象和移动/静态相机工作的运动模型上，其中由于相机而假设两个运动层， /或前景和前景和背景之间的深度差。 序列线性回归应用于图像特征的序列和瞬时替换，以便计算前景和背景层的仿射运动参数，同时考虑时间平滑度。 然后基于稀疏特征聚类提取前景层，这是使用卡尔曼滤波进行时间有效和精确地提取的。

公开(公告)号：US07136507B2

公开(公告)日：2006-11-14

申请号：US10917985

申请日：2004-08-12

申请人： Mei Han ,  Yihong Gong ,  Hai Tao

发明人： Mei Han ,  Yihong Gong ,  Hai Tao

IPC分类号： G06K9/00

CPC分类号： G06K9/00771 ,  G06K9/00335 ,  G08B13/19608

摘要： A video surveillance system uses rule-based reasoning and multiple-hypothesis scoring to detect predefined behaviors based on movement through zone patterns. Trajectory hypothesis spawning allows for trajectory splitting and/or merging and includes local pruning to managed hypothesis growth. Hypotheses are scored based on a number of criteria, illustratively including at least one non-spatial parameter. Connection probabilities computed during the hypothesis spawning process are based on a number of criteria, illustratively including object size. Object detection and probability scoring is illustratively based on object class.

公开(公告)号：US06246412B1

公开(公告)日：2001-06-12

申请号：US09099097

申请日：1998-06-18

申请人： Heung-Yeung Shum ,  Mei Han ,  Richard S. Szeliski

发明人： Heung-Yeung Shum ,  Mei Han ,  Richard S. Szeliski

IPC分类号： G06T1500

CPC分类号： G06T15/10

摘要： A system and process for refining a model of a 3D scene using one or more panoramic views of the scene. An image of a panoramic view is displayed on a screen and a previously constructed model of the 3D scene is projected onto the screen image. Once the model is projected, any portion thereof that is not aligned with its corresponding feature in the screen image is moved so as to be in alignment. Plane normals and line directions for previously modeled planes in the 3D scene are then estimated using, inter alia, the newly aligned lines of the previous model. There may also be new, unmodeled features appearing in the screen image. These features can also be modeled, if desired. Next, plane distances and vertex point locations of each plane in the 3D scene that is to be modeled are estimated. In general, this entails solving of a system of linear geometric constraint equations created from the aforementioned plane normals and line directions, and preferably, user-designated parameters associated with the geometry of the scene. If the initial model employed in the refinement process was constructed using similar methods, then it is preferred to include the associated constraint equations in the system of equations. The system of equations is solve using any of various methods and the refined model of the 3D scene is constructed. If additional panoramic views of the scene are available, the model can be refined even further using the just-described system and process.

摘要翻译： 一种使用场景的一个或多个全景图来精炼3D场景的模型的系统和过程。 将全景图像显示在屏幕上，将3D场景的先前构造的模型投影到屏幕图像上。 一旦模型投影，其与屏幕图像中其对应特征不对准的任何部分被移动以便对准。 然后使用特别是先前模型的新对齐的线来估计3D场景中先前建模的平面的平面法线和线方向。 屏幕图像中也可能出现新的未建模的功能。 如果需要，也可以对这些特征进行建模。 接下来，估计要被建模的3D场景中的每个平面的平面距离和顶点位置。 一般来说，这需要解决由上述平面法线和线方向创建的线性几何约束方程，并且优选地，与场景的几何形状相关联的用户指定的参数。 如果使用类似方法构建精化过程中使用的初始模型，则优选在方程组中包括相关约束方程。 使用各种方法中的任意一种求解方程组，并构建了3D场景的精细模型。 如果场景的其他全景视图可用，则可以使用刚刚描述的系统和过程进一步改进模型。