公开(公告)号：US09008359B2

公开(公告)日：2015-04-14

申请号：US13535461

申请日：2012-06-28

申请人： Rogerio S. Feris ,  Yun Zhai

发明人： Rogerio S. Feris ,  Yun Zhai

IPC分类号： G06K9/00 ,  G06T7/20

CPC分类号： G06K9/00771 ,  G06K9/00805 ,  G06T7/194 ,  G06T7/254 ,  G06T7/269 ,  G06T2207/10016 ,  G06T2207/30232 ,  G06T2207/30236 ,  G06T2207/30241

摘要： Foreground object image features are extracted from input video via application of a background subtraction mask, and optical flow image features from a region of the input video image data defined by the extracted foreground object image features. If estimated movement features indicate that the underlying object is in motion, a dominant moving direction of the underlying object is determined. If the dominant moving direction is parallel to an orientation of the second, crossed thoroughfare, an event alarm indicating that a static object is blocking travel on the crossing second thoroughfare is not generated. If the estimated movement features indicate that the underlying object is static, or that its determined dominant moving direction is not parallel to the second thoroughfare, an appearance of the foreground object region is determined and a static-ness timer run while the foreground object region comprises the extracted foreground object image features.

公开(公告)号：US20080232681A1

公开(公告)日：2008-09-25

申请号：US11688372

申请日：2007-03-20

申请人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

发明人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

IPC分类号： G06K9/62

CPC分类号： G06K9/6228

摘要： A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.

摘要翻译： 公开了一种用于检测图像中的对象的存在的方法，系统和计算机程序产品。 根据实施例，用于检测图像中的对象的存在的方法包括：接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征，与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。

公开(公告)号：US09070020B2

公开(公告)日：2015-06-30

申请号：US13590269

申请日：2012-08-21

申请人： Russell P. Bobbitt ,  Rogerio S. Feris ,  Yun Zhai

发明人： Russell P. Bobbitt ,  Rogerio S. Feris ,  Yun Zhai

IPC分类号： G06K9/00

CPC分类号： G06K9/00771 ,  G06K9/00718 ,  G06K9/00765 ,  G06K9/6212 ,  G06T7/11

摘要： Foreground feature data and motion feature data is determined for frames of video data acquired from a train track area region of interest. The frames are labeled as “train present” if the determined foreground feature data value meets a threshold value, else as “train absent”; and as “motion present” if the motion feature data meets a motion threshold, else as “static.” The labels are used to classify segments of the video data comprising groups of consecutive video frames, namely as within a “no train present” segment for groups with “train absent” and “static” labels; within a “train present and in transition” segment for groups “train present” and “motion present” labels; and within a “train present and stopped” segment for groups with “train present” and “static” labels. The presence or motion state of a train at a time of inquiry is thereby determined from the respective segment classification.

摘要翻译： 确定从感兴趣的列车轨道区域获取的视频数据的帧的前景特征数据和运动特征数据。 如果确定的前景特征数据值满足阈值，则帧被标记为“列车存在”，否则被标记为“列车存在”，否则被标记为“列车存在” 如果运动特征数据满足运动阈值，则作为“运动呈现”，否则为“静态”。标签用于对包括连续视频帧组的视频数据的段进行分类，即在“无列车存在”段内 对于具有“火车不在”和“静态”标签的组; 在“火车现在”和“现场演出”标签的“火车现在和转型期”段内， 在“火车现在”和“静态”标签的组别内的“火车现在和停止”部分。 因此，从相应的段分类确定列车在询问时的存在或运动状态。

公开(公告)号：US20130101208A1

公开(公告)日：2013-04-25

申请号：US13279504

申请日：2011-10-24

申请人： Rogerio S. Feris ,  Yun Zhai

发明人： Rogerio S. Feris ,  Yun Zhai

IPC分类号： G06K9/34

CPC分类号： G06K9/00711 ,  G06K9/00744 ,  G06K9/00771 ,  G06K9/4604 ,  G06K9/4652 ,  G06T5/50 ,  G06T7/11 ,  G06T7/174 ,  G06T7/194 ,  G06T7/75 ,  G06T2207/10016 ,  G06T2207/10024 ,  G06T2207/20024 ,  G06T2207/20216

摘要： Long-term understanding of background modeling includes determining first and second dimension gradient model derivatives of image brightness data of an image pixel along respective dimensions of two-dimensional, single channel image brightness data of a static image scene. The determined gradients are averaged with previous determined gradients of the image pixels, and with gradients of neighboring pixels as a function of their respective distances to the image pixel, the averaging generating averaged pixel gradient models for each of a plurality of pixels of the video image data of the static image scene that each have mean values and weight values. Background models for the static image scene are constructed as a function of the averaged pixel gradients and weights, wherein the background model pixels are represented by averaged pixel gradient models having similar orientation and magnitude and weights meeting a threshold weight requirement.

公开(公告)号：US08655018B2

公开(公告)日：2014-02-18

申请号：US13353485

申请日：2012-01-19

申请人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

发明人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

IPC分类号： G06K9/00

CPC分类号： G06K9/6228

摘要： A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.

摘要翻译： 公开了一种用于检测图像中的对象的存在的方法，系统和计算机程序产品。 根据实施例，用于检测图像中的对象的存在的方法包括：接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征，与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。

公开(公告)号：US20140003724A1

公开(公告)日：2014-01-02

申请号：US13535461

申请日：2012-06-28

申请人： Rogerio S. Feris ,  Yun Zhai

发明人： Rogerio S. Feris ,  Yun Zhai

IPC分类号： G06K9/46

CPC分类号： G06K9/00771 ,  G06K9/00805 ,  G06T7/194 ,  G06T7/254 ,  G06T7/269 ,  G06T2207/10016 ,  G06T2207/30232 ,  G06T2207/30236 ,  G06T2207/30241

摘要： Foreground object image features are extracted from input video via application of a background subtraction mask, and optical flow image features from a region of the input video image data defined by the extracted foreground object image features. If estimated movement features indicate that the underlying object is in motion, a dominant moving direction of the underlying object is determined. If the dominant moving direction is parallel to an orientation of the second, crossed thoroughfare, an event alarm indicating that a static object is blocking travel on the crossing second thoroughfare is not generated. If the estimated movement features indicate that the underlying object is static, or that its determined dominant moving direction is not parallel to the second thoroughfare, an appearance of the foreground object region is determined and a static-ness timer run while the foreground object region comprises the extracted foreground object image features.

摘要翻译： 通过应用背景减影掩模从输入视频提取前景对象图像特征，以及从提取的前景对象图像特征定义的输入视频图像数据的区域中的光流图像特征。 如果估计运动特征表明底层对象处于运动状态，则确定底层物体的主要移动方向。 如果主导移动方向平行于第二条交叉通道的方向，则不会产生指示静态物体在交叉第二条通道上阻挡行驶的事件警报。 如果估计的运动特征指示下面的对象是静态的，或者其确定的主要移动方向不与第二通道平行，则确定前景对象区域的外观，并且静态定时器在前景对象区域包括 提取的前景对象图像特征。

公开(公告)号：US08483481B2

公开(公告)日：2013-07-09

申请号：US12844330

申请日：2010-07-27

申请人： Rogerio S. Feris ,  Arun Hampapur ,  Frederik C. Kjeldsen ,  Hao-Wei Liu

发明人： Rogerio S. Feris ,  Arun Hampapur ,  Frederik C. Kjeldsen ,  Hao-Wei Liu

IPC分类号： G06T7/0081

CPC分类号： G06K9/46 ,  G06K9/00711 ,  G06K9/00744 ,  G06K9/00771 ,  G06K2009/4666 ,  G06T11/20 ,  H04N7/18

摘要： Techniques are provided. The techniques include identifying a region of interest in a video scene, applying a background subtraction algorithm to the region of interest to detect a static foreground object in the region of interest, and determining whether the static foreground object is abandoned or removed, wherein determining whether the static foreground object is abandoned or removed comprises performing a foreground analysis based on edge energy and region growing, and pruning one or more false alarms using one or more track statistics.

摘要翻译： 提供技术。 这些技术包括识别视频场景中的感兴趣区域，将感兴趣的区域应用背景减法算法来检测感兴趣区域中的静态前景对象，以及确定是否放弃或去除静态前景对象，其中确定是否 静态前景对象被放弃或移除包括基于边缘能量和区域增长执行前景分析，以及使用一个或多个轨道统计修剪一个或多个虚假报警。

公开(公告)号：US08170276B2

公开(公告)日：2012-05-01

申请号：US11688372

申请日：2007-03-20

申请人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

发明人： Rogerio S. Feris ,  Arun Hampapur ,  Ying-Li Tian

IPC分类号： G06K9/00

CPC分类号： G06K9/6228

摘要： A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.

摘要翻译： 公开了一种用于检测图像中的对象的存在的方法，系统和计算机程序产品。 根据实施例，用于检测图像中的对象的存在的方法包括：接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征，与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。