公开(公告)号：US20140301653A1

公开(公告)日：2014-10-09

申请号：US13489407

申请日：2012-06-05

申请人： Erik Murphy-Chutorian ,  Chuck Joseph Rosenberg ,  Shengyang Dai ,  Ehud Rivlin ,  Mei Han ,  Kyle Heath

发明人： Erik Murphy-Chutorian ,  Chuck Joseph Rosenberg ,  Shengyang Dai ,  Ehud Rivlin ,  Mei Han ,  Kyle Heath

IPC分类号： G06K9/62

CPC分类号： G06K9/00456 ,  G06K9/00221 ,  G06K9/00677 ,  G06K9/62 ,  G06K9/6267 ,  G06K2009/00328

摘要： Embodiments generally relate to summarizing a photo album in a social network system. In one embodiment, a method includes grouping photos into a plurality of groups of photos, and selecting a plurality of representative photos, where each representative photo represents a respective group from the plurality of groups, where the selecting is based on a quality score of each of the photos, and where each quality score is based on different types of attributes. The method also includes enabling the plurality of representative photos to be shared.

摘要翻译： 实施例通常涉及在社交网络系统中总结相册。 在一个实施例中，一种方法包括将照片分组成多组照片，并且选择多个代表照片，其中每个代表照片表示来自多个组的相应组，其中选择基于每个组的质量得分 的照片，每个质量得分都基于不同类型的属性。 该方法还包括使多个代表性照片能够共享。

公开(公告)号：US08345976B2

公开(公告)日：2013-01-01

申请号：US12852096

申请日：2010-08-06

申请人： Su Wang ,  Shengyang Dai ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

发明人： Su Wang ,  Shengyang Dai ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

IPC分类号： G06K9/34

CPC分类号： G06K9/6256 ,  G06K9/0014 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/136 ,  G06T7/187 ,  G06T2207/30024

摘要： Methods and systems disclosed herein provide the capability to automatically process digital pathology images quickly and accurately. According to one embodiment, an digital pathology image segmentation task may be divided into at least two parts. An image segmentation task may be carried out utilizing both bottom-up analysis to capture local definition of features and top-down analysis to use global information to eliminate false positives. In some embodiments, an image segmentation task is carried out using a “pseudo-bootstrapping” iterative technique to produce superior segmentation results. In some embodiments, the superior segmentation results produced by the pseudo-bootstrapping method are used as input in a second segmentation task that uses a combination of bottom-up and top-down analysis.

摘要翻译： 本文公开的方法和系统提供了快速且准确地自动处理数字病理图像的能力。 根据一个实施例，数字病理图像分割任务可以被划分为至少两部分。 图像分割任务可以利用自下而上的分析来捕获特征的局部定义和自上而下的分析，以使用全局信息来消除假阳性。 在一些实施例中，使用伪自举迭代技术来执行图像分割任务以产生优异的分割结果。 在一些实施例中，通过伪自举方法产生的优越分割结果被用作使用自下而上和自顶向下分析的组合的第二分段任务中的输入。

公开(公告)号：US20070291984A1

公开(公告)日：2007-12-20

申请号：US11453549

申请日：2006-06-15

申请人： Ming Yang ,  Ying Wu ,  Shengyang Dai ,  Shihong Lao

发明人： Ming Yang ,  Ying Wu ,  Shengyang Dai ,  Shihong Lao

IPC分类号： G06K9/00

CPC分类号： G06T7/20

摘要： A method for tracking objects includes identifying a target, identifying a plurality of auxiliary objects related to the target, and tracking the target using the plurality of auxiliary objects.

摘要翻译： 用于跟踪对象的方法包括识别目标，识别与目标相关的多个辅助对象，以及使用多个辅助对象跟踪目标。

公开(公告)号：US08938119B1

公开(公告)日：2015-01-20

申请号：US13461482

申请日：2012-05-01

申请人： Mei Han ,  Vivek Kwatra ,  Shengyang Dai ,  Sergey Ioffe

发明人： Mei Han ,  Vivek Kwatra ,  Shengyang Dai ,  Sergey Ioffe

IPC分类号： G06K9/00

CPC分类号： G06K9/4661 ,  G06T5/008

摘要： An image comprising color pixels with varying illumination is selected. Instances of a repeating pattern in the image are determined. Illumination values for illuminated pixels at locations within instances of the repeating pattern are calculated based on pixel intensities of non-illuminated pixels at corresponding locations in other instances of the repeating pattern. The illumination variation is removed from the illuminated pixels based on the calculated illumination values to produce enhanced pixels. Color from the non-illuminated pixels at the corresponding locations in other instances of the repeating pattern is propagated to the enhanced pixels.

摘要翻译： 选择包括具有变化的照明的彩色像素的图像。 确定图像中的重复图案的实例。 基于重复图案的其他实例中的相应位置处的非照明像素的像素强度来计算在重复图案的实例内的位置处的照明像素的照明值。 基于所计算的照明值，从照明像素去除照明变化以产生增强像素。 来自重复图案的其他实例中的相应位置处的非照明像素的颜色被传播到增强像素。

公开(公告)号：US20130243289A1

公开(公告)日：2013-09-19

申请号：US13423211

申请日：2012-03-17

申请人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

发明人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

IPC分类号： G06K9/00

CPC分类号： G06T7/162 ,  G06T7/11 ,  G06T7/194 ,  G06T2207/10081 ,  G06T2207/20041 ,  G06T2207/20096 ,  G06T2207/30036

摘要： An interactive segmentation framework for 3-D teeth CT volumetric data enables a user to segment an entire dental region or individual teeth depending upon the types of user input. Graph cuts-based interactive segmentation utilizes a user's scribbles which are collected on several 2-D representative CT slices and are expanded on those slices. Then, a 3-D distance transform is applied to the entire CT volume based on the expanded scribbles. Bony tissue enhancement is added before feeding 3-D CT raw image data into the graph cuts pipeline. The segmented teeth area is able to be directly utilized to reconstruct a 3-D virtual teeth model.

摘要翻译： 用于3D牙齿CT体积数据的交互式分割框架使用户能够根据用户输入的类型来分割整个牙齿区域或单个牙齿。 基于图切割的交互式分割利用用户的涂鸦，这些涂鸦被收集在几个二维代表性的CT切片上，并在这些切片上展开。 然后，基于扩展的涂鸦将3-D距离变换应用于整个CT体积。 在将3-D CT原始图像数据提供给图形切割管道之前，添加骨组织增强。 分段牙齿区域能够直接用于重建3-D虚拟牙齿模型。

公开(公告)号：US20220254137A1

公开(公告)日：2022-08-11

申请号：US17622462

申请日：2019-08-05

申请人： Jilin TU ,  Jiang WANG ,  Huizhong CHEN ,  Xiangxin ZHU ,  Shengyang DAI ,  Google LLC

发明人： Jilin Tu ,  Jiang Wang ,  Huizhong Chen ,  Xiangxin Zhu ,  Shengyang Dai

IPC分类号： G06V10/50 ,  G06V10/778 ,  G06V10/75

摘要： A computing system for detecting objects in an image can perform operations including generating an image pyramid that includes a first level corresponding with the image at a first resolution and a second level corresponding with the image at a second resolution. The operations can include tiling the first level and the second level by dividing the first level into a first plurality of tiles and the second level into a second plurality of tiles; inputting the first plurality of tiles and the second plurality of tiles into a machine-learned object detection model; receiving, as an output of the machine-learned object detection model, object detection data that includes bounding boxes respectively defined with respect to individual ones of the first plurality of tiles and the second plurality of tiles; and generating image object detection output by mapping the object detection data onto an image space of the image.

公开(公告)号：US09202281B2

公开(公告)日：2015-12-01

申请号：US13423209

申请日：2012-03-17

申请人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

发明人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

IPC分类号： G06K9/00 ,  G06T7/00

CPC分类号： G06T7/0081 ,  G06K9/00 ,  G06T7/11 ,  G06T7/143 ,  G06T7/162 ,  G06T7/194 ,  G06T2207/20081

摘要： An integrated interactive segmentation with spatial constraint method utilizes a combination of several of the most popular online learning algorithms into one and implements a spatial constraint which defines a valid mask local to the user's given marks. Additionally, both supervised learning and statistical analysis are integrated, which are able to compensate each other. Once prediction and activation are obtained, pixel-wised multiplication is conducted to fully indicate how likely each pixel belongs to the foreground or background.

摘要翻译： 具有空间约束方法的集成交互式分割将几种最流行的在线学习算法的组合应用于一种，并实现了定义用户给定标记本地的有效掩码的空间约束。 此外，监督学习和统计分析都是综合的，可以相互补偿。 一旦获得了预测和激活，就进行像素增益乘法以完全指示每个像素属于前景或背景的可能性。

公开(公告)号：US08605973B2

公开(公告)日：2013-12-10

申请号：US13423211

申请日：2012-03-17

申请人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

发明人： Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

IPC分类号： G06K9/00

CPC分类号： G06T7/162 ,  G06T7/11 ,  G06T7/194 ,  G06T2207/10081 ,  G06T2207/20041 ,  G06T2207/20096 ,  G06T2207/30036

摘要： An interactive segmentation framework for 3-D teeth CT volumetric data enables a user to segment an entire dental region or individual teeth depending upon the types of user input. Graph cuts-based interactive segmentation utilizes a user's scribbles which are collected on several 2-D representative CT slices and are expanded on those slices. Then, a 3-D distance transform is applied to the entire CT volume based on the expanded scribbles. Bony tissue enhancement is added before feeding 3-D CT raw image data into the graph cuts pipeline. The segmented teeth area is able to be directly utilized to reconstruct a 3-D virtual teeth model.

摘要翻译： 用于3D牙齿CT体积数据的交互式分割框架使用户能够根据用户输入的类型来分割整个牙齿区域或单个牙齿。 基于图切割的交互式分割利用用户的涂鸦，这些涂鸦被收集在几个二维代表性的CT切片上，并在这些切片上展开。 然后，基于扩展的涂鸦将3-D距离变换应用于整个CT体积。 在将3-D CT原始图像数据提供给图形切割管道之前，添加骨组织增强。 分段牙齿区域能够直接用于重建3-D虚拟牙齿模型。

公开(公告)号：US08351676B2

公开(公告)日：2013-01-08

申请号：US12902321

申请日：2010-10-12

申请人： Shengyang Dai ,  Su Wang ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

发明人： Shengyang Dai ,  Su Wang ,  Akira Nakamura ,  Takeshi Ohashi ,  Jun Yokono

IPC分类号： G06K9/00 ,  G06K9/34

CPC分类号： G06K9/0014 ,  G06K9/00147 ,  G06K9/6282

摘要： Systems and methods for implementing a multi-step image recognition framework for classifying digital images are provided. The provided multi-step image recognition framework utilizes a gradual approach to model training and image classification tasks requiring multi-dimensional ground truths. A first step of the multi-step image recognition framework differentiates a first image region from a remainder image region. Each subsequent step operates on a remainder image region from the previous step. The provided multi-step image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-step image recognition frameworks.

摘要翻译： 提供了用于实现用于分类数字图像的多步图像识别框架的系统和方法。 提供的多步图像识别框架利用逐步的方法来模拟需要多维地面真实的训练和图像分类任务。 多步图像识别框架的第一步骤将第一图像区域与剩余图像区域区分开。 每个后续步骤对前一步骤的余数图像区域进行操作。 提供的多步图像识别框架允许模型训练和图像分类任务以比传统的单步图像识别框架更精确和更少资源密集的方式执行。

公开(公告)号：US20120275703A1

公开(公告)日：2012-11-01

申请号：US13204574

申请日：2011-08-05

申请人： Xutao Lv ,  Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

发明人： Xutao Lv ,  Su Wang ,  Shengyang Dai ,  Xun Xu ,  Akira Nakamura

IPC分类号： G06K9/34

CPC分类号： G06T3/4053

摘要： Systems and methods for implementing a superpixel image segmentation technique using a boundary preserving distance metric are disclosed. The disclosed technique segments a digital image into superpixels comprising contiguous pixel regions sharing similar characteristics. Superpixel image segmentation techniques presented herein utilize a boundary preserving distance metric. A boundary preserving distance metric presented herein measures the similarity between two pixels of a digital image at least partially based on a boundary probability values of the two pixels and surrounding pixels.

摘要翻译： 公开了使用边界保留距离度量来实现超像素图像分割技术的系统和方法。 所公开的技术将数字图像分割成包含具有相似特征的相邻像素区域的超像素。 本文提出的超像素图像分割技术利用边界保留距离度量。 这里给出的边界保持距离度量至少部分地基于两个像素和周围像素的边界概率值来测量数字图像的两个像素之间的相似度。