公开(公告)号：US07155033B1

公开(公告)日：2006-12-26

申请号：US09494514

申请日：2000-02-01

申请人： Thumpudi Naveen ,  Anil M. Murching ,  Ali Tabatabai

发明人： Thumpudi Naveen ,  Anil M. Murching ,  Ali Tabatabai

IPC分类号： G06K9/00

CPC分类号： G06T9/20 ,  Y10S707/99937

摘要： A method of coarse representation of a visual object's shape for search/query/filtering applications uses a binding box that fully encompasses the object of interest within the image to extract a feature vector. Once the feature vector is available, matching based on specific queries may be performed using a search engine to compare the query number to an appropriate element of the feature vector, performing sorting to pick the best matches.

摘要翻译： 用于搜索/查询/过滤应用的视觉对象形状的粗略表示的方法使用完全包含图像内的感兴趣对象的绑定框来提取特征向量。 一旦特征向量可用，可以使用搜索引擎来执行基于特定查询的匹配，以将查询号码与特征向量的适当元素进行比较，执行排序以选择最佳匹配。

公开(公告)号：US06917692B1

公开(公告)日：2005-07-12

申请号：US09318682

申请日：1999-05-25

申请人： Anil M. Murching ,  Thumpudi Naveen ,  Radu S. Jasinschi ,  Ali Tabatabai

发明人： Anil M. Murching ,  Thumpudi Naveen ,  Radu S. Jasinschi ,  Ali Tabatabai

IPC分类号： G06K9/00 ,  G06T7/20

CPC分类号： G06K9/32 ,  G06T7/277

摘要： A semi-automatic method of tracking color objects in a video image sequence starts by separating the objects on the basis of color and identifying an object of interest to track. A Kalman predictive algotithm in used to predict the position of the centroid of the object of interest through successive frames. From the predicted position the actual centroid is measured and the position and velocity are smoothed using a Kalman filter. Error recovery is provided in the event the centroid falls outside the field of view or falls into an area of a different color, or in the event the tracking algorithm breaks down.

摘要翻译： 在视频图像序列中跟踪颜色对象的半自动方法通过基于颜色分离对象并识别要跟踪的感兴趣对象来开始。 卡尔曼预测算法用于通过连续帧预测感兴趣对象的质心的位置。 从预测位置，使用卡尔曼滤波器测量实际质心并使位置和速度平滑。 如果重心落在视野之外或落入不同颜色的区域，或者跟踪算法发生故障的情况下，则会提供错误恢复。

公开(公告)号：US07016531B1

公开(公告)日：2006-03-21

申请号：US09496068

申请日：2000-02-01

申请人： Anil M. Murching ,  Thumpudi Naveen ,  Ali Tabatabai

发明人： Anil M. Murching ,  Thumpudi Naveen ,  Ali Tabatabai

IPC分类号： G06K9/34

CPC分类号： G06K9/342 ,  G06T7/11 ,  G06T7/155 ,  G06T2207/10024 ,  G06T2207/20021 ,  G06T2207/20152

摘要： A method of extracting regions of homogeneous color from a digital picture divides the digital picture into blocks and generates a feature vector for each block as a set of moments of the data for the block. The distance between the feature vector of each block and the feature vectors of the nearest neighboring blocks are determined using either a weighted Euclidean distance metric or a probability mass function-based distance metric. The maximum distance is the gradient value for the block, and the set of gradient values over all the blocks form a color gradient field. The gradient field is digitized and smoothed, and then segmented into regions of similar color characteristics using a watershed algorithm.

摘要翻译： 从数字图像提取均匀颜色的区域的方法将数字图像划分成块，并且为块的数据的一组时刻产生每个块的特征向量。 使用加权欧几里德距离度量或基于概率质量函数的距离度量来确定每个块的特征向量与最近相邻块的特征向量之间的距离。 最大距离是块的梯度值，并且所有块上的梯度值集合都形成一个颜色渐变字段。 梯度场被数字化和平滑化，然后使用分水岭算法将其分割成具有相似颜色特征的区域。

公开(公告)号：US06526169B1

公开(公告)日：2003-02-25

申请号：US09270233

申请日：1999-03-15

申请人： Anil M. Murching ,  Ali Tabatabai ,  Thumpudi Naveen

发明人： Anil M. Murching ,  Ali Tabatabai ,  Thumpudi Naveen

IPC分类号： G06K900

CPC分类号： G06K9/4652 ,  G06K9/2081 ,  G06T7/11 ,  G06T7/90 ,  G06T2207/10016 ,  G06T2207/20021

摘要： A histogram-based segmentation of an image, frame or picture of a video signal into objects via color moments is initiated by defining a relatively large area within the object. The defined area is characterized by its color information in the form of a limited set of color moments representing a color histogram for the area. Based upon the set of color moments, color moments generated for small candidate blocks within the image, an automatically generated weighting vector, distance measures for the blocks from a central block in the object and a tolerance the area is grown to encompass the object to the extent of its boundaries. The initial set of color moments are then updated for the entire object. Those candidate blocks within the object serve to segment the object from the image.

摘要翻译： 通过在对象内定义一个相对较大的区域，启动通过颜色时刻将视频信号的图像，帧或图像分割成对象的基于直方图的分割。 所定义的区域的特征在于其颜色信息的形式是表示该区域的颜色直方图的有限的一组颜色矩。 基于颜色矩的集合，为图像内的小候选块生成的颜色矩，自动生成的权重向量，来自对象中的中心块的块的距离度量以及该区域生长的容差以包含对象到 其边界范围。 然后针对整个对象更新初始颜色时刻集。 对象内的候选块用于从图像中分割对象。

公开(公告)号：US06381363B1

公开(公告)日：2002-04-30

申请号：US09326164

申请日：1999-06-04

申请人： Anil M. Murching ,  Ali Tabatabai ,  Thumpudi Naveen

发明人： Anil M. Murching ,  Ali Tabatabai ,  Thumpudi Naveen

IPC分类号： G06K900

CPC分类号： G06K9/4652 ,  G06K9/2081 ,  G06T7/11 ,  G06T7/90 ,  G06T2207/10016 ,  G06T2207/20021

摘要： A histogram-based segmentation of images in a video signal via color moments is initialized by a user defining regions in objects of interest from one or more images, key frames or pictures of the video signal. For each rectangle a normalized average color moment and associated co-variance matrix are determined which define a color class for that rectangle. From the normalized average color moment and associated co-variance garbage parameters are generated. Segmentation is then performed on a block basis on each image of the video sequence, a normalized color moment being generated for each block. Using a log likelihood test the closest color class for the block is determined. Based upon the closest color class and the garbage parameters for that color class a final determination is made in a two stage test as to whether the block belongs to the closest class or to a “garbage” class. All the continguous blocks that belong to a specific color class form the segmented object, and all of the objects are segmented in this manner.

摘要翻译： 通过颜色时刻的视频信号中的图像的基于直方图的分割由用户定义来自视频信号的一个或多个图像，关键帧或图片的关注对象的区域来初始化。 对于每个矩形，确定归一化的平均色矩和相关协方差矩阵，其定义该矩形的颜色类。 从标准化的平均颜色时刻和相关的协方差垃圾参数生成。 然后以视频序列的每个图像为基础执行分段，为每个块生成归一化的颜色矩。 使用对数似然检验确定块的最接近的颜色等级。 基于最近的颜色等级和该颜色类的垃圾参数，在两级测试中进行关于块是属于最接近的类还是“垃圾”类的最终确定。 属于特定颜色类的所有相关块形成分段对象，并且所有对象都以此方式分段。

公开(公告)号：US06882746B1

公开(公告)日：2005-04-19

申请号：US09495597

申请日：2000-02-01

申请人： Thumpudi Naveen ,  Anil M. Murching

发明人： Thumpudi Naveen ,  Anil M. Murching

IPC分类号： G06F17/30 ,  G06K9/34 ,  G06K9/42 ,  G06K9/64

CPC分类号： G06K9/6203 ,  G06F17/30259 ,  G06K9/42 ,  Y10S707/99945 ,  Y10S707/99948

摘要： A method of generating normalized bitmap representation for the shape of a visual object for use in search/query/filtering applications segments an image into visual objects. The samples belonging to a visual object of interest are identified. The identified samples that form the largest connected blob are reduced to an un-normalized bitmap. The un-normalized bitmap is then normalized using the mean and covariance of the valid samples to generate the normalized bitmap representation having a standard height and having an orientation such that a principal direction is along a vertical direction. The normalized bitmap representation may be used with a query to search a database of images where the visual objects all have associated normalized bitmap representations. The query bitmap is normalized and matched to each normalized bitmap representation. The visual objects having the lowest mismatch values of their normalized bitmap representation with the query bitmap are identified as the objects of the search.

摘要翻译： 为了在搜索/查询/过滤应用中使用的视觉对象的形状生成归一化位图表示的方法将图像分割为可视对象。 识别属于感兴趣的视觉对象的样本。 形成最大连接斑点的识别样本被减少为非归一化位图。 然后使用有效样本的平均和协方差来归一化非归一化位图，以生成具有标准高度并且具有使得主方向沿着垂直方向的取向的归一化位图表示。 归一化位图表示可以与查询一起使用，以搜索视觉对象都具有关联的归一化位图表示的图像的数据库。 查询位图被归一化并与每个归一化位图表示相匹配。 将具有查询位图的其归一化位图表示具有最低失配值的可视对象识别为搜索对象。

公开(公告)号：US06594389B1

公开(公告)日：2003-07-15

申请号：US09585729

申请日：2000-05-31

申请人： Anil M. Murching

发明人： Anil M. Murching

IPC分类号： G06K934

CPC分类号： G06T7/11 ,  G06T2207/20012 ,  G06T2207/20021

摘要： A method of refining a pixel-based segmentation mask derived by upsampling a block-based segmentation mask for an image having multiple object classes determines a likelihood that each pixel in the pixel-based segmentation mask exists in each object class. Boundary pixels between bordering classes are extracted and processed to find a true class for each boundary pixel. The pixel-based segmentation mask is then updated with the true class for each of the boundary pixels to produce a smoothed pixel-based segmentation mask.

摘要翻译： 通过对具有多个对象类别的图像的基于块的分割掩码进行上采样而导出的基于像素的分割掩码的方法确定了每个对象类中存在基于像素的分割掩码中的每个像素的可能性。 提取和处理边界类之间的边界像素，以找到每个边界像素的真实类。 然后基于像素的分割掩模用每个边界像素的真实类别更新，以产生平滑的基于像素的分割掩码。