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1.发明授权Image based detecting system and method for traffic parameters and computer program product thereof 有权基于图像的检测系统及其交通参数方法及其计算机程序产品公开(公告)号：US09058744B2
公开(公告)日：2015-06-16
申请号：US13046689
申请日：2011-03-11
申请人： Chung-Hsien Huang , Ruei-Cheng Wu
发明人： Chung-Hsien Huang , Ruei-Cheng Wu
CPC分类号： G08G1/054 , G06K9/00785
摘要： An image-based detecting system for traffic parameters first sets a range of a vehicle lane for monitoring control, and sets an entry detection window and an exit detection window in the vehicle lane. When the entry detection window detects an event of a vehicle passing by using the image information captured at the entry detection window, a plurality of feature points are detected in the entry detection window, and will be tracked hereafter. Then, the feature points belonging to the same vehicle are grouped to obtain at least a location tracking result of single vehicle. When the tracked single vehicle moves to the exit detection window, according to the location tracking result and the time correlation through estimating the information captured at the entry detection window and the exit detection window, at least a traffic parameter is estimated.
摘要翻译： 用于交通参数的基于图像的检测系统首先设置用于监视控制的车道的范围，并且在车道中设置入口检测窗口和出口检测窗口。 当入口检测窗口通过使用在入口检测窗口处获取的图像信息来检测车辆的事件时，在入口检测窗口中检测到多个特征点，并且将在以后跟踪。 然后，将属于同一车辆的特征点分组，以获得至少单个车辆的位置跟踪结果。 当跟踪的单个车辆移动到出口检测窗口时，根据位置跟踪结果和通过估计在入口检测窗口和出口检测窗口处捕获的信息的时间相关性，估计至少一个交通参数。
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公开(公告)号：US08059864B2
公开(公告)日：2011-11-15
申请号：US12111190
申请日：2008-04-28
IPC分类号： G06K9/00
CPC分类号： G08G1/14 , G06K9/00785 , G06K9/6277 , G06K9/6296
摘要： Disclosed is a system and method of image-based space detection. The system includes an image selection module, a 3-layer detection mechanism and an optimization module. At least one image processing area that may affect space-status judgment is selected from plural image processing areas. The 3-layer detection mechanism having an observation layer, a labeling layer, and a semantic layer observes the information about the selected image processing area, associates with a local classification model, and adjacent local constraint model and a global semantics model to completely describe the probability distribution of the links among the three layers, and provide global label constraint information. The optimization module analyzes the probability distribution and global label constraint information, and generates an image-based optimized space detection result.
摘要翻译： 公开了基于图像的空间检测的系统和方法。 该系统包括图像选择模块，3层检测机构和优化模块。 从多个图像处理区域中选择可能影响空间状态判断的至少一个图像处理区域。 具有观察层，标记层和语义层的3层检测机构观察关于所选图像处理区域的信息，与本地分类模型相关联，以及相邻局部约束模型和全局语义模型，以完全描述 在三层之间的链路的概率分布，并提供全局标签约束信息。 优化模块分析概率分布和全局标签约束信息，并生成基于图像的优化空间检测结果。
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3.发明申请公开(公告)号：US20110141288A1
公开(公告)日：2011-06-16
申请号：US12758812
申请日：2010-04-13
IPC分类号： H04N5/225
CPC分类号： G06K9/00771 , G06K9/00979 , G06K9/6256 , G06K9/6259 , G06T7/292 , G06T2207/30196
摘要： An object tracking method for a non-overlapping-sensor network works in a sensor network. The method may comprise a training phase and a detection phase. In the training phase, a plurality of sensor information measured by the sensors in the sensor network is used as training samples. At least an entrance/exit is marked out within the measurement range of each sensor. At least three characteristic functions including sensor spatial relation among the sensors in the sensor network, difference of movement time and similarity in appearance, are estimated by an automatically learning method. The at least three characteristic functions are used as the principles for object tracking and relationship linking in the detection phase.
摘要翻译： 用于非重叠传感器网络的物体跟踪方法在传感器网络中工作。 该方法可以包括训练阶段和检测阶段。 在训练阶段，使用由传感器网络中的传感器测量的多个传感器信息作为训练样本。 在每个传感器的测量范围内至少标出一个入口/出口。 传感器网络中传感器之间的传感器空间关系，运动时间差异，外观相似度等三个特征函数，通过自动学习方法进行估计。 在检测阶段使用至少三个特征函数作为对象跟踪和关系链接的原理。
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公开(公告)号：US20100111362A1
公开(公告)日：2010-05-06
申请号：US12350209
申请日：2009-01-07
申请人： Chung-Hsien Huang , Ruei-Cheng Wu
发明人： Chung-Hsien Huang , Ruei-Cheng Wu
IPC分类号： G06K9/00
CPC分类号： G06K9/4642 , G06T7/254 , G06T7/90 , G06T2207/10016 , G06T2207/10024
摘要： A method for detecting a shadow of an object in an image is provided. A moving object in a plurality of continuous images is detected. A histogram of a color variation of the moving object in each of the images is calculated. The histograms of the color variation are accumulated to obtain a cumulative histogram. A distribution of the color variation in the cumulative histogram is estimated to obtain a shadow distribution function. Whether each pixel in a received image belongs to the shadow is determined by using the shadow distribution function.
摘要翻译： 提供了一种用于检测图像中的对象的阴影的方法。 检测多个连续图像中的移动物体。 计算每个图像中的移动物体的颜色变化的直方图。 累积颜色变化的直方图以获得累积直方图。 估计累积直方图中颜色变化的分布以获得阴影分布函数。 通过使用阴影分布函数确定接收图像中的每个像素属于阴影。
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公开(公告)号：US08189913B2
公开(公告)日：2012-05-29
申请号：US12350209
申请日：2009-01-07
申请人： Chung-Hsien Huang , Ruei-Cheng Wu
发明人： Chung-Hsien Huang , Ruei-Cheng Wu
IPC分类号： G06K9/00
CPC分类号： G06K9/4642 , G06T7/254 , G06T7/90 , G06T2207/10016 , G06T2207/10024
摘要： A method for detecting a shadow of an object in an image is provided. A moving object in a plurality of continuous images is detected. A histogram of a color variation of the moving object in each of the images is calculated. The histograms of the color variation are accumulated to obtain a cumulative histogram. A distribution of the color variation in the cumulative histogram is estimated to obtain a shadow distribution function. Whether each pixel in a received image belongs to the shadow is determined by using the shadow distribution function.
摘要翻译： 提供了一种用于检测图像中的对象的阴影的方法。 检测多个连续图像中的移动物体。 计算每个图像中的移动物体的颜色变化的直方图。 累积颜色变化的直方图以获得累积直方图。 估计累积直方图中颜色变化的分布以获得阴影分布函数。 通过使用阴影分布函数确定接收图像中的每个像素属于阴影。
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6.发明授权公开(公告)号：US08542276B2
公开(公告)日：2013-09-24
申请号：US12758812
申请日：2010-04-13
IPC分类号： G06K9/00
CPC分类号： G06K9/00771 , G06K9/00979 , G06K9/6256 , G06K9/6259 , G06T7/292 , G06T2207/30196
摘要： An object tracking method for a non-overlapping-sensor network works in a sensor network. The method may comprise a training phase and a detection phase. In the training phase, a plurality of sensor information measured by the sensors in the sensor network is used as training samples. At least an entrance/exit is marked out within the measurement range of each sensor. At least three characteristic functions including sensor spatial relation among the sensors in the sensor network, difference of movement time and similarity in appearance, are estimated by an automatically learning method. The at least three characteristic functions are used as the principles for object tracking and relationship linking in the detection phase.
摘要翻译： 用于非重叠传感器网络的物体跟踪方法在传感器网络中工作。 该方法可以包括训练阶段和检测阶段。 在训练阶段，使用由传感器网络中的传感器测量的多个传感器信息作为训练样本。 在每个传感器的测量范围内至少标出一个入口/出口。 传感器网络中传感器之间的传感器空间关系，运动时间差异，外观相似度等三个特征函数，通过自动学习方法进行估计。 在检测阶段使用至少三个特征函数作为对象跟踪和关系链接的原理。
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7.发明申请IMAGE BASED DETECTING SYSTEM AND METHOD FOR TRAFFIC PARAMETERS AND COMPUTER PROGRAM PRODUCT THEREOF 有权基于图像的交通参数检测系统及方法及其计算机程序产品公开(公告)号：US20120148094A1
公开(公告)日：2012-06-14
申请号：US13046689
申请日：2011-03-11
申请人： CHUNG-HSIEN HUANG , Ruei-Cheng Wu
发明人： CHUNG-HSIEN HUANG , Ruei-Cheng Wu
IPC分类号： G06K9/00
CPC分类号： G08G1/054 , G06K9/00785
摘要： An image-based detecting system for traffic parameters first sets a range of a vehicle lane for monitoring control, and sets an entry detection window and an exit detection window in the vehicle lane. When the entry detection window detects an event of a vehicle passing by using the image information captured at the entry detection window, a plurality of feature points are detected in the entry detection window, and will be tracked hereafter. Then, the feature points belonging to the same vehicle are grouped to obtain at least a location tracking result of single vehicle. When the tracked single vehicle moves to the exit detection window, according to the location tracking result and the time correlation through estimating the information captured at the entry detection window and the exit detection window, at least a traffic parameter is estimated.
摘要翻译： 用于交通参数的基于图像的检测系统首先设置用于监视控制的车道的范围，并且在车道中设置入口检测窗口和出口检测窗口。 当入口检测窗口通过使用在入口检测窗口处获取的图像信息来检测车辆的事件时，在入口检测窗口中检测到多个特征点，并且将在以后跟踪。 然后，将属于同一车辆的特征点分组，以获得至少单个车辆的位置跟踪结果。 当跟踪的单个车辆移动到出口检测窗口时，根据位置跟踪结果和通过估计在入口检测窗口和出口检测窗口处捕获的信息的时间相关性，估计至少一个交通参数。
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公开(公告)号：US20090085772A1
公开(公告)日：2009-04-02
申请号：US12111190
申请日：2008-04-28
IPC分类号： G08G1/14
CPC分类号： G08G1/14 , G06K9/00785 , G06K9/6277 , G06K9/6296
摘要： Disclosed is a system and method of image-based space detection. The system includes an image selection module, a 3-layer detection mechanism and an optimization module. At least one image processing area that may affect space-status judgment is selected from plural image processing areas. The 3-layer detection mechanism having an observation layer, a labeling layer, and a semantic layer observes the information about the selected image processing area, associates with a local classification model, and adjacent local constraint model and a global semantics model to completely describe the probability distribution of the links among the three layers, and provide global label constraint information. The optimization module analyzes the probability distribution and global label constraint information, and generates an image-based optimized space detection result.
摘要翻译： 公开了基于图像的空间检测的系统和方法。 该系统包括图像选择模块，3层检测机构和优化模块。 从多个图像处理区域中选择可能影响空间状态判断的至少一个图像处理区域。 具有观察层，标记层和语义层的3层检测机构观察关于所选择的图像处理区域的信息，与本地分类模型相关联，以及相邻的局部约束模型和全局语义模型，以完全描述 在三层之间的链路的概率分布，并提供全局标签约束信息。 优化模块分析概率分布和全局标签约束信息，并生成基于图像的优化空间检测结果。
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