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    • 2. 发明授权
    • Clustering videos by location
    • 按位置分组视频
    • US08184913B2
    • 2012-05-22
    • US12416152
    • 2009-04-01
    • Simon J. BakerCharles Lawrence Zitnick, IIIGerhard Florian Schroff
    • Simon J. BakerCharles Lawrence Zitnick, IIIGerhard Florian Schroff
    • G06K9/68
    • G06K9/00718G06F17/30781G06F17/3082G06K9/6219Y02D10/45
    • Described is a technology in which video shots are clustered based upon the location at which the shots were captured. A global energy function is optimized, including a first term that computes clusters so as to be reasonably dense and well connected, to match the possible shots that are captured at a location, e.g., based on similarity scores between pairs of shots. A second term is a temporal prior that encourages subsequent shots to be placed in the same cluster. The shots may be represented as nodes of a minimum spanning tree having edges with weights that are based on the similarity score between the shots represented by their respective nodes. Agglomerative clustering is performed by selecting pairs of available clusters, merging the pairs and keeping the pair with the lowest cost. Clusters are iteratively merged until a stopping criterion or criteria is met (e.g., only a single cluster remains).
    • 描述了一种基于拍摄拍摄位置来进行视频拍摄的技术。 优化了全局能量函数,包括计算集群以便相当密集和良好连接的第一项,以匹配在某个位置捕获的可能的拍摄,例如,基于拍摄对之间的相似性得分。 第二个术语是时间先前,鼓励后续的镜头被放置在同一个集群中。 拍摄可以被表示为具有基于由它们各自的节点表示的拍摄之间的相似性得分的权重的边缘的最小生成树的节点。 通过选择成对的可用集群,合并对并保持成本最低的组合来执行集群聚类。 集群被迭代合并,直到满足停止标准或条件(例如,仅剩下一个集群)。
    • 4. 发明授权
    • Realtime user guidance for freehand drawing
    • 实时用户指导手绘
    • US08827710B2
    • 2014-09-09
    • US13110923
    • 2011-05-19
    • Charles Lawrence Zitnick, IIIYong Jae LeeMichael Cohen
    • Charles Lawrence Zitnick, IIIYong Jae LeeMichael Cohen
    • G09B11/10G09B11/00
    • G09B11/10G09B11/00
    • Architecture that guides the freeform drawing of objects by a user to enable the user to produce improved drawings without significant training. As the user draws, the architecture dynamically updates a relevant shadow image proximate (e.g., underlying) the user's strokes. The strokes overlay an evolving shadow image, which shadow image is suggestive of object contours that guide the user during the drawing process. Relevant edge images selected from a large database are automatically blended to construct the shadow image. As the user draws, the strokes are dynamically analyzed using an encoding of overlapping windows for fast matching with the database of images. A top ranked set of matching database edge images are aligned to the drawing, a set of spatially varying weights blend the edge images into the shadow image, and a scoring technique is employed to select the optimum shadow image for display.
    • 指导用户自由绘制对象的架构,以使用户能够在不进行重大培训的情况下生成改进的图纸。 当用户绘制时,体系结构动态地更新用户笔画的邻近(例如,底层)的相关阴影图像。 笔画覆盖了不断变化的阴影图像,阴影图像暗示着在绘图过程中引导用户的对象轮廓。 从大数据库中选择的相关边缘图像将自动混合以构建阴影图像。 当用户绘制时,使用重叠窗口的编码动态地分析笔画,以便与图像数据库快速匹配。 匹配数据库边缘图像的顶级排列集合与图形对齐,一组空间变化的权重将边缘图像混合到阴影图像中,并且使用评分技术来选择用于显示的最佳阴影图像。
    • 7. 发明授权
    • Local bi-gram model for object recognition
    • 用于对象识别的本地bi-gram模型
    • US07903883B2
    • 2011-03-08
    • US11694938
    • 2007-03-30
    • Charles Lawrence Zitnick, IIIXiangyang LanRichard S. Szeliski
    • Charles Lawrence Zitnick, IIIXiangyang LanRichard S. Szeliski
    • G06K9/00
    • G06K9/468G06K9/6296
    • A local bi-gram model object recognition system and method for constructing a local bi-gram model and using the model to recognize objects in a query image. In a learning phase, the local bi-gram model is constructed that represents objects found in a set of training images. The local bi-gram model is a local spatial model that only models the relationship of neighboring features without any knowledge of their global context. Object recognition is performed by finding a set of matching primitives in the query image. A tree structure of matching primitives is generated and a search is performed to find a tree structure of matching primitives that obeys the local bi-gram model. The local bi-gram model can be found using unsupervised learning. The system and method also can be used to recognize objects unsupervised that are undergoing non-rigid transformations for both object instance recognition and category recognition.
    • 一种局部双向模型对象识别系统和方法,用于构建局部双向模型,并使用该模型来识别查询图像中的对象。 在学习阶段,构建了表示在一组训练图像中发现的对象的局部双语模型。 当地的双语模型是一种局部空间模型,它只对相邻特征的关系进行建模,而无需了解其全局环境。 通过在查询图像中找到一组匹配的基元来执行对象识别。 生成匹配原语的树形结构,并执行搜索以找到符合本地双语模型的匹配原语的树结构。 可以使用无监督学习找到当地的双语模型。 系统和方法也可用于识别无监督的对象实例识别和类别识别正在进行非刚性转换的对象。
    • 10. 发明申请
    • REALTIME USER GUIDANCE FOR FREEHAND DRAWING
    • 实时用户指导免费绘图
    • US20120295231A1
    • 2012-11-22
    • US13110923
    • 2011-05-19
    • Charles Lawrence Zitnick, IIIYong Jae LeeMichael Cohen
    • Charles Lawrence Zitnick, IIIYong Jae LeeMichael Cohen
    • G09B11/00
    • G09B11/10G09B11/00
    • Architecture that guides the freeform drawing of objects by a user to enable the user to produce improved drawings without significant training. As the user draws, the architecture dynamically updates a relevant shadow image proximate (e.g., underlying) the user's strokes. The strokes overlay an evolving shadow image, which shadow image is suggestive of object contours that guide the user during the drawing process. Relevant edge images selected from a large database are automatically blended to construct the shadow image. As the user draws, the strokes are dynamically analyzed using an encoding of overlapping windows for fast matching with the database of images. A top ranked set of matching database edge images are aligned to the drawing, a set of spatially varying weights blend the edge images into the shadow image, and a scoring technique is employed to select the optimum shadow image for display.
    • 指导用户自由绘制对象的架构,以使用户能够在不进行重大培训的情况下生成改进的图纸。 当用户绘制时,体系结构动态地更新用户笔画的邻近(例如,底层)的相关阴影图像。 笔画覆盖了不断变化的阴影图像,阴影图像暗示着在绘图过程中引导用户的对象轮廓。 从大数据库中选择的相关边缘图像将自动混合以构建阴影图像。 当用户绘制时,使用重叠窗口的编码动态地分析笔画,以便与图像数据库快速匹配。 匹配数据库边缘图像的顶级排列集合与图形对齐,一组空间变化的权重将边缘图像混合到阴影图像中,并且使用评分技术来选择用于显示的最佳阴影图像。