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公开(公告)号：US07433495B2
公开(公告)日：2008-10-07
申请号：US11042453
申请日：2005-01-25
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06K9/00234 , G06T7/251 , G06T2207/10016 , G06T2207/30196 , G06T2207/30201
摘要： Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.
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公开(公告)号：US07151843B2
公开(公告)日：2006-12-19
申请号：US11042015
申请日：2005-01-25
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06K9/00234 , G06T7/251 , G06T2207/10016 , G06T2207/30196 , G06T2207/30201
摘要： Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.
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公开(公告)号：US06999599B2
公开(公告)日：2006-02-14
申请号：US10164947
申请日：2002-06-07
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
IPC分类号： G06K9/00
CPC分类号： G06K9/00234 , G06K9/3216 , G06K9/6207 , G06T7/251 , G06T7/277 , G06T2207/10016 , G06T2207/30201
摘要： A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
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4.发明申请System and process for tracking an object state using a particle filter sensor fusion technique 失效使用粒子滤波器传感器融合技术跟踪物体状态的系统和过程公开(公告)号：US20050114079A1
公开(公告)日：2005-05-26
申请号：US10985243
申请日：2004-11-10
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06T7/277 , G10L2021/02166
摘要： A system and process for tracking an object state over time using particle filter sensor fusion and a plurality of logical sensor modules is presented. This new fusion framework combines both the bottom-up and top-down approaches to sensor fusion to probabilistically fuse multiple sensing modalities. At the lower level, individual vision and audio trackers can be designed to generate effective proposals for the fuser. At the higher level, the fuser performs reliable tracking by verifying hypotheses over multiple likelihood models from multiple cues. Different from the traditional fusion algorithms, the present framework is a closed-loop system where the fuser and trackers coordinate their tracking information. Furthermore, to handle non-stationary situations, the present framework evaluates the performance of the individual trackers and dynamically updates their object states. A real-time speaker tracking system based on the proposed framework is feasible by fusing object contour, color and sound source location.
摘要翻译： 提出了一种使用粒子滤波器传感器融合和多个逻辑传感器模块跟踪物体状态随时间变化的系统和过程。 这种新的融合框架将自下而上和自顶向下的方法与传感器融合相结合，以概率地融合多种感测模式。 在较低级别，个人视觉和音频跟踪器可以设计用于为定影器生成有效的建议。 在较高级别，定影器通过从多个线索的多个似然模型上验证假设来执行可靠的跟踪。 与传统融合算法不同，本框架是闭环系统，其中定影器和跟踪器协调其跟踪信息。 此外，为了处理非平稳情况，本框架评估各个跟踪器的性能并动态更新其对象状态。 基于提出的框架的实时扬声器跟踪系统可以通过融合对象轮廓，颜色和声源位置来实现。
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公开(公告)号：US07130446B2
公开(公告)日：2006-10-31
申请号：US10006927
申请日：2001-12-03
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
IPC分类号： G06K9/00
CPC分类号： G06K9/00234 , G06T7/251 , G06T2207/10016 , G06T2207/30196 , G06T2207/30201
摘要： Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.
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6.发明申请公开(公告)号：US20050188013A1
公开(公告)日：2005-08-25
申请号：US11042453
申请日：2005-01-25
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06K9/00234 , G06T7/251 , G06T2207/10016 , G06T2207/30196 , G06T2207/30201
摘要： Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.
摘要翻译： 多个人的自动检测和跟踪包括接收视频和/或音频内容的帧并且识别帧中的新的面部区域的候选区域。 使用一个或多个分级验证级别来验证人脸是否在候选区域中，并且如果所述一个或多个分层验证级别验证人脸在候选区域中，则指示使候选区域包括面部。 使用多个音频和/或视频提示从帧到帧跟踪视频内容中的每个验证的面部。
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7.发明授权公开(公告)号：US06882959B2
公开(公告)日：2005-04-19
申请号：US10428470
申请日：2003-05-02
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06T7/277 , G10L2021/02166
摘要： A system and process for tracking an object state over time using particle filter sensor fusion and a plurality of logical sensor modules is presented. This new fusion framework combines both the bottom-up and top-down approaches to sensor fusion to probabilistically fuse multiple sensing modalities. At the lower level, individual vision and audio trackers can be designed to generate effective proposals for the fuser. At the higher level, the fuser performs reliable tracking by verifying hypotheses over multiple likelihood models from multiple cues. Different from the traditional fusion algorithms, the present framework is a closed-loop system where the fuser and trackers coordinate their tracking information. Furthermore, to handle non-stationary situations, the present framework evaluates the performance of the individual trackers and dynamically updates their object states. A real-time speaker tracking system based on the proposed framework is feasible by fusing object contour, color and sound source location.
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公开(公告)号：US07231064B2
公开(公告)日：2007-06-12
申请号：US11282365
申请日：2005-11-17
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
IPC分类号： G06K9/00
CPC分类号： G06K9/00234 , G06K9/3216 , G06K9/6207 , G06T7/251 , G06T7/277 , G06T2207/10016 , G06T2207/30201
摘要： A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
摘要翻译： 使用基于概率模式的多假设跟踪（MHT）的对象跟踪的系统和方法提供了在复杂环境中运动对象（例如头部和面部）的鲁棒和计算上有效的跟踪。 基于模式的多假设跟踪器使用在参数状态空间中从初始样本精化的局部最大值的模式。 由于模式具有很高的代表性，所以基于模式的多假设跟踪器使用少量假设来有效地建模非线性概率分布。 通过使用参数因果轮廓模型来将初始轮廓细化到附近模式，可以实现实时跟踪性能。 另外，常规MHT方案的一个共同缺点，即仅产生最大似然估计而不是期望的后验概率分布，通过将重要性采样框架引入到MHT中，并从重要性函数估计后验概率分布来解决。
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公开(公告)号：US20060078163A1
公开(公告)日：2006-04-13
申请号：US11282365
申请日：2005-11-17
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
IPC分类号： G06K9/00
CPC分类号： G06K9/00234 , G06K9/3216 , G06K9/6207 , G06T7/251 , G06T7/277 , G06T2207/10016 , G06T2207/30201
摘要： A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
摘要翻译： 使用基于概率模式的多假设跟踪（MHT）的对象跟踪的系统和方法提供了在复杂环境中运动对象（例如头部和面部）的鲁棒和计算上有效的跟踪。 基于模式的多假设跟踪器使用在参数状态空间中从初始样本精化的局部最大值的模式。 由于模式具有很高的代表性，所以基于模式的多假设跟踪器使用少量假设来有效地建模非线性概率分布。 通过使用参数因果轮廓模型来将初始轮廓细化到附近模式，可以实现实时跟踪性能。 另外，常规MHT方案的一个共同缺点，即仅产生最大似然估计而不是期望的后验概率分布，通过将重要性采样框架引入到MHT中，并从重要性函数估计后验概率分布来解决。
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公开(公告)号：US20050210103A1
公开(公告)日：2005-09-22
申请号：US11042766
申请日：2005-01-25
申请人： Yong Rui , Yunqiang Chen
发明人： Yong Rui , Yunqiang Chen
CPC分类号： G06K9/00234 , G06T7/251 , G06T2207/10016 , G06T2207/30196 , G06T2207/30201
摘要： Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.
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