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    • 4. 发明申请
    • Bi-Directional Tracking Using Trajectory Segment Analysis
    • 使用轨迹段分析进行双向跟踪
    • US20070086622A1
    • 2007-04-19
    • US11380635
    • 2006-04-27
    • Jian SunWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • Jian SunWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • G06K9/00G06K9/34
    • G06K9/3241G06K9/32G06T7/277
    • The present video tracking technique outputs a Maximum A Posterior (MAP) solution for a target object based on two object templates obtained from a start and an end keyframe of a whole state sequence. The technique first minimizes the whole state space of the sequence by generating a sparse set of local two-dimensional modes in each frame of the sequence. The two-dimensional modes are converted into three-dimensional points within a three-dimensional volume. The three-dimensional points are clustered using a spectral clustering technique where each cluster corresponds to a possible trajectory segment of the target object. If there is occlusion in the sequence, occlusion segments are generated so that an optimal trajectory of the target object can be obtained.
    • 本视频跟踪技术基于从整个状态序列的开始和结束关键帧获得的两个对象模板,为目标对象输出最大A后验(MAP)解决方案。 该技术首先通过在序列的每个帧中生成稀疏的局部二维模式集来最小化序列的整个状态空间。 二维模式在三维体积内被转换成三维点。 使用光谱聚类技术对三维点进行聚类,其中每个聚类对应于目标对象的可能的轨迹段。 如果序列中存在闭塞,则生成闭塞段,从而可以获得目标对象的最佳轨迹。
    • 5. 发明授权
    • Picture collage systems and methods
    • 图片拼贴系统和方法
    • US07576755B2
    • 2009-08-18
    • US11674243
    • 2007-02-13
    • Jian SunXiaoou TangHeung-Yeung Shum
    • Jian SunXiaoou TangHeung-Yeung Shum
    • G09G5/00
    • G06T11/60
    • Systems and methods provide picture collage systems and methods. In one implementation, a system determines a salient region in each of multiple images and develops a Bayesian model to maximize visibility of the salient regions in a collage that overlaps the images. The Bayesian model can also minimize blank spaces in the collage and normalize the percentage of each salient region that can be visibly displayed in the collage. Images are placed with diversified rotational orientation to provide a natural artistic collage appearance. A Markov Chain Monte Carlo technique is applied to the parameters of the Bayesian model to obtain image placement, orientation, and layering. The MCMC technique can combine optimization proposals that include local, global, and pairwise samplings from a distribution of state variables.
    • 系统和方法提供图片拼贴系统和方法。 在一个实现中,系统确定多个图像中的每一个中的显着区域,并且开发贝叶斯模型以最大化与图像重叠的拼贴中的显着区域的可见性。 贝叶斯模型还可以将拼贴中的空白空间最小化,并将每个显着区域的百分比归一化,可以在拼贴画中显示。 图像以多样化的旋转方向放置,以提供自然的艺术拼贴外观。 将马尔科夫链蒙特卡罗技术应用于贝叶斯模型的参数,以获得图像放置,取向和分层。 MCMC技术可以结合来自状态变量分布的本地,全局和成对采样的优化提议。
    • 6. 发明申请
    • Digital Video Effects
    • 数码影像效果
    • US20070216675A1
    • 2007-09-20
    • US11467859
    • 2006-08-28
    • Jian SunQiang WangWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • Jian SunQiang WangWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • H04N13/04G06T15/00
    • G06T11/00
    • Digital video effects are described. In one aspect, a foreground object in a video stream is identified. The video stream comprises multiple image frames. The foreground object is modified by rendering a 3-dimensional (3-D) visual feature over the foreground object for presentation to a user in a modified video stream. Pose of the foreground object is tracked in 3-D space across respective ones of the image frames to identify when the foreground object changes position in respective ones of the image frames. Based on this pose tracking, aspect ratio of the 3-D visual feature is adaptively modified and rendered over the foreground object in corresponding image frames for presentation to the user in the modified video stream.
    • 描述数字视频效果。 在一个方面,识别视频流中的前景对象。 视频流包括多个图像帧。 通过在前景对象上呈现三维(3-D)视觉特征来修改前景对象,以呈现给经修改的视频流中的用户。 前景物体的姿态在相应的图像帧中的3-D空间中被跟​​踪,以识别前景对象何时改变相应图像帧中的位置。 基于这种姿态跟踪,3-D视觉特征的宽高比被自适应地修改并在相应图像帧中的前景对象上呈现,以便在修改的视频流中呈现给用户。
    • 9. 发明授权
    • Digital video effects
    • 数字视频效果
    • US08026931B2
    • 2011-09-27
    • US11467859
    • 2006-08-28
    • Jian SunQiang WangWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • Jian SunQiang WangWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • G09G5/00G06K9/34
    • G06T11/00
    • Digital video effects are described. In one aspect, a foreground object in a video stream is identified. The video stream comprises multiple image frames. The foreground object is modified by rendering a 3-dimensional (3-D) visual feature over the foreground object for presentation to a user in a modified video stream. Pose of the foreground object is tracked in 3-D space across respective ones of the image frames to identify when the foreground object changes position in respective ones of the image frames. Based on this pose tracking, aspect ratio of the 3-D visual feature is adaptively modified and rendered over the foreground object in corresponding image frames for presentation to the user in the modified video stream.
    • 描述数字视频效果。 在一个方面,识别视频流中的前景对象。 视频流包括多个图像帧。 通过在前景对象上呈现三维(3-D)视觉特征来修改前景对象,以呈现给经修改的视频流中的用户。 前景物体的姿态在相应的图像帧中的3-D空间中被跟​​踪,以识别前景对象何时改变相应图像帧中的位置。 基于这种姿态跟踪,3-D视觉特征的宽高比被自适应地修改并在相应图像帧中的前景对象上呈现,以便在修改的视频流中呈现给用户。
    • 10. 发明授权
    • Bi-directional tracking using trajectory segment analysis
    • 使用轨迹段分析进行双向跟踪
    • US07817822B2
    • 2010-10-19
    • US11380635
    • 2006-04-27
    • Jian SunWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • Jian SunWeiwei ZhangXiaoou TangHeung-Yeung Shum
    • G06K9/00
    • G06K9/3241G06K9/32G06T7/277
    • The present video tracking technique outputs a Maximum A Posterior (MAP) solution for a target object based on two object templates obtained from a start and an end keyframe of a whole state sequence. The technique first minimizes the whole state space of the sequence by generating a sparse set of local two-dimensional modes in each frame of the sequence. The two-dimensional modes are converted into three-dimensional points within a three-dimensional volume. The three-dimensional points are clustered using a spectral clustering technique where each cluster corresponds to a possible trajectory segment of the target object. If there is occlusion in the sequence, occlusion segments are generated so that an optimal trajectory of the target object can be obtained.
    • 本视频跟踪技术基于从整个状态序列的开始和结束关键帧获得的两个对象模板,为目标对象输出最大A后验(MAP)解决方案。 该技术首先通过在序列的每个帧中生成稀疏的局部二维模式集来最小化序列的整个状态空间。 二维模式在三维体积内被转换成三维点。 使用光谱聚类技术对三维点进行聚类,其中每个聚类对应于目标对象的可能的轨迹段。 如果序列中存在闭塞,则生成闭塞段,从而可以获得目标对象的最佳轨迹。