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：US20080267525A1

公开(公告)日：2008-10-30

申请号：US11869906

申请日：2007-10-10

申请人： Shengyang Dai ,  Mei Han ,  Wei Xu ,  Ying Wu ,  Yihong Gong

发明人： Shengyang Dai ,  Mei Han ,  Wei Xu ,  Ying Wu ,  Yihong Gong

IPC分类号： G06K9/40

CPC分类号： G06T3/403

摘要： Systems and methods are disclosed for processing a low resolution image by performing a high resolution edge segment extraction on the low resolution image; performing an image super resolution on each edge segment; performing reconstruction constraint reinforcement; and generating a high quality image from the low quality image.

摘要翻译： 公开了通过在低分辨率图像上执行高分辨率边缘段提取来处理低分辨率图像的系统和方法; 在每个边缘片段上执行图像超分辨率; 执行重建约束加固; 并从低质量图像生成高质量图像。

公开(公告)号：US08335403B2

公开(公告)日：2012-12-18

申请号：US11869906

申请日：2007-10-10

申请人： Shengyang Dai ,  Mei Han ,  Wei Xu ,  Ying Wu ,  Yihong Gong

发明人： Shengyang Dai ,  Mei Han ,  Wei Xu ,  Ying Wu ,  Yihong Gong

IPC分类号： G06K9/32

CPC分类号： G06T3/403

摘要： Systems and methods are disclosed for processing a low resolution image by performing a high resolution edge segment extraction on the low resolution image; performing an image super resolution on each edge segment; performing reconstruction constraint reinforcement; and generating a high quality image from the low quality image.

摘要翻译： 公开了通过在低分辨率图像上执行高分辨率边缘段提取来处理低分辨率图像的系统和方法; 在每个边缘片段上执行图像超分辨率; 执行重建约束加固; 并从低质量图像生成高质量图像。

公开(公告)号：US20070103595A1

公开(公告)日：2007-05-10

申请号：US11553552

申请日：2006-10-27

申请人： Yihong Gong ,  Mei Han ,  Dan Kong ,  Hai Tao ,  Wei Xu

发明人： Yihong Gong ,  Mei Han ,  Dan Kong ,  Hai Tao ,  Wei Xu

IPC分类号： H04N5/00

CPC分类号： H04N5/262 ,  H04N19/587 ,  H04N19/59

摘要： A video super-resolution method that combines information from different spatial-temporal resolution cameras by constructing a personalized dictionary from a high resolution image of a scene resulting in a domain specific prior that performs better than a general dictionary built from images.

摘要翻译： 一种视频超分辨率方法，其通过从场景的高分辨率图像构造个性化字典来组合来自不同空间 - 时间分辨率相机的信息，从而产生比由图像构建的通用字典更好的域特定。

公开(公告)号：US07499571B1

公开(公告)日：2009-03-03

申请号：US11525795

申请日：2006-09-22

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 ,  H04N5/225

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：US07148912B2

公开(公告)日：2006-12-12

申请号：US10917201

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： H04N7/18 ,  H04N5/225

CPC分类号： G08B31/00 ,  G08B13/19604 ,  G08B13/19608 ,  G08B13/19615 ,  G08B13/19652

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：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：US07088846B2

公开(公告)日：2006-08-08

申请号：US10916870

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： G08B13/19652 ,  G06K9/00335 ,  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：US20050105765A1

公开(公告)日：2005-05-19

申请号：US10917225

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 ,  G06T7/20 ,  G08B13/00 ,  G08B13/194 ,  G08B13/196 ,  H04N7/18

CPC分类号： G06T7/20 ,  G06K9/00295 ,  G06K9/00771 ,  G06T2207/30241 ,  G08B13/19602 ,  G08B13/19604 ,  G08B13/19608 ,  G08B13/19615 ,  G08B13/19652 ,  G08B31/00 ,  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：US20050104961A1

公开(公告)日：2005-05-19

申请号：US10917201

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 ,  H04N7/18

CPC分类号： G08B31/00 ,  G08B13/19604 ,  G08B13/19608 ,  G08B13/19615 ,  G08B13/19652

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。