公开(公告)号：US20140157209A1

公开(公告)日：2014-06-05

申请号：US13796772

申请日：2013-03-12

Applicant: Google Inc.

Inventor： Navneet Dalal ,  Mehul Nariyawala ,  Ankit Mohan ,  Varun Gulshan

IPC: G06F3/01

CPC classification number: G06F3/017 ,  G06F3/012 ,  G06F3/0482 ,  G06F2203/011 ,  G06K9/00355 ,  G06K9/2018 ,  G06K9/6807

Abstract: A system and method that includes detecting an application change within a multi-application operating framework; updating an application hierarchy model for gesture-to-action responses with the detected application change; detecting a gesture; according to the hierarchy model, mapping the detected gesture to an action of an application; and triggering the action.

Abstract translation: 一种包括检测多应用操作框架内的应用变化的系统和方法; 用检测到的应用改变来更新用于手势对动作响应的应用层级模型; 检测手势; 根据层次模型，将检测到的手势映射到应用的动作; 并触发动作。

公开(公告)号：US20140254864A1

公开(公告)日：2014-09-11

申请号：US13788900

申请日：2013-03-07

Applicant: Google Inc.

Inventor： Navneet Dalal ,  Rahul Garg ,  Varun Gulshan ,  Ankit Mohan

IPC: G06K9/62 ,  G06K9/00

CPC classification number: G06K9/00335 ,  G06K2009/4666

Abstract: System and method for image detection that include collecting image data; at a processor, over a plurality of support regions of the image data, computing a dimensionality component of a support region of the image data, wherein the, non-nucleus pixels of a support region; calculating a normalizing factor of the dimensionality component; for at least one weighted pattern of a pattern set, applying a weighted pattern to the dimensionality component to create a gradient vector, mapping the gradient vector to a probabilistic model, and normalizing the gradient vector by the normalizing factor; condensing probabilistic models of the plurality of support regions into a probabilistic distribution feature for at least one cell of the image data; applying a classifier to at least the probabilistic distribution feature; and detecting an object in the image data according to a result of the applied classifier.

Abstract translation: 包括收集图像数据的图像检测系统和方法; 在处理器处，在图像数据的多个支持区域上，计算图像数据的支持区域的维数分量，其中支持区域的非核心像素; 计算维度分量的归一化因子; 对于图案组的至少一个加权图案，将加权图案应用于所述维度分量以创建梯度向量，将所述梯度向量映射到概率模型，以及通过所述归一化因子归一化所述梯度向量; 将所述多个支持区域的概率模型缩放为所述图像数据的至少一个单元的概率分布特征; 将分类器应用于至少概率分布特征; 以及根据应用的分类器的结果检测图像数据中的对象。