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    ADAPTIVE EDGE-LIKE FEATURE SELECTION DURING OBJECT DETECTION
    23.
    发明申请
    ADAPTIVE EDGE-LIKE FEATURE SELECTION DURING OBJECT DETECTION 有权
    在对象检测期间自适应边缘特征选择

    公开(公告)号：US20160239708A1

    公开(公告)日：2016-08-18

    申请号：US14625588

    申请日：2015-02-18

    Applicant: QUALCOMM Incorporated

    Inventor： Raghuraman Krishnamoorthi ,  Bojan Vrcelj

    IPC: G06K9/00 ,  G06K9/46 ,  G06F17/30 ,  G06T7/00

    CPC classification number: G06K9/00624 ,  G06F17/30047 ,  G06F17/30247 ,  G06K9/4604 ,  G06K9/4671 ,  G06K9/6228 ,  G06T7/13

    Abstract: A method of recognizing an object of interest in an image includes extracting a first set of features from within the image. Each extracted feature in the first set of features is then categorized as either blob-like or edge-like. A second set of features is then taken from the first set, where a number of the edge-like features to include in the second set of features is based on a relative number of edge-like features to blob-like features included in the first set of extracted features. An object of interest within the image is detected according to the second set of features.

    Abstract translation: 识别图像中的感兴趣对象的方法包括从图像内提取第一组特征。 然后将第一组特征中的每个提取的特征分类为斑点状或边缘状。 然后从第一组获取第二组特征，其中包括在第二组特征中的多个边缘状特征基于包括在第一组中的类似于边缘的特征到类似斑点的特征 提取的功能集。 根据第二组特征来检测图像内的感兴趣对象。

    3D OBJECT SEGMENTATION
    24.
    发明申请
    3D OBJECT SEGMENTATION 有权
    3D对象分段

    公开(公告)号：US20160196659A1

    公开(公告)日：2016-07-07

    申请号：US14866771

    申请日：2015-09-25

    Applicant: QUALCOMM Incorporated

    Inventor： Bojan Vrcelj ,  Young Hoon Lee ,  Gerhard Reitmayr

    IPC: G06T7/00 ,  G06K9/62 ,  H04N13/02 ,  G06K9/34

    CPC classification number: H04N13/204 ,  G01B11/22 ,  G06K9/00214 ,  G06K9/34 ,  G06K9/6215 ,  G06T7/11 ,  G06T7/12 ,  G06T7/13 ,  G06T7/136 ,  G06T7/50 ,  G06T2207/10012 ,  G06T2207/10021 ,  G06T2207/10028 ,  G06T2207/30244 ,  H04N2013/0092

    Abstract: Disclosed are a system, apparatus, and method for 3D object segmentation within an environment. Image frames are obtained from one or more depth cameras or at different times and planar segments are extracted from data obtained from the image frames. Candidate segments that comprise a non-planar object surface are identified from the extracted planar segments. In one aspect, certain extracted planar segments are identified as comprising a non-planar object surface, and are referred to as candidate segments. Confidence of preexisting candidate segments are adjusted in response to determining correspondence with a candidate segment. In one aspect, one or more preexisting candidate segments are determined to comprise a surface of a preexisting non-planar object hypothesis. Confidence in the non-planar object hypothesis is updated in response to determining correspondence with a candidate segment.

    Abstract translation: 公开了一种用于环境内的3D对象分割的系统，装置和方法。 图像帧从一个或多个深度相机获得或在不同时间获得，并且从从图像帧获得的数据中提取平面片段。 从提取的平面段识别构成非平面物体表面的候选段。 在一个方面，某些提取的平面段被识别为包括非平面物体表面，并且被称为候选段。 响应于确定与候选片段的对应关系，调整预先存在的候选片段的置信度。 在一个方面，一个或多个预先存在的候选片段被确定为包括预先存在的非平面对象假设的表面。 响应于确定与候选片段的对应关系，更新非平面物体假设的置信度。

    Reducing object detection time by utilizing space localization of features
    25.
    发明授权
    Reducing object detection time by utilizing space localization of features 有权
    通过利用特征的空间定位来减少对象检测时间

    公开(公告)号：US09202129B2

    公开(公告)日：2015-12-01

    申请号：US13796444

    申请日：2013-03-12

    Applicant: QUALCOMM Incorporated

    Inventor： Raghuraman Krishnamoorthi ,  Gary G. McGrath ,  Bojan Vrcelj

    IPC: G06K9/46 ,  G06K9/62 ,  G06K9/68

    CPC classification number: G06K9/46 ,  G06K9/6211 ,  G06K9/6857

    Abstract: In one example, a method for exiting an object detection pipeline includes determining, while in the object detection pipeline, a number of features within a first tile of an image, wherein the image consists of a plurality of tiles, performing a matching procedure using at least a subset of the features within the first tile if the number of features within the first tile meets a threshold value, exiting the object detection pipeline if a result of the matching procedure indicates an object is recognized in the image, and presenting the result of the matching procedure.

    Abstract translation: 在一个示例中，用于退出对象检测流水线的方法包括在对象检测流水线中确定图像的第一瓦片内的多个特征，其中所述图像由多个瓦片组成，其中使用 如果所述第一瓦片内的特征数目满足阈值，则在所述第一瓦片内的所述特征的至少一部分，如果所述匹配过程的结果指示对象在所述图像中被识别，则退出所述对象检测流水线， 匹配程序。

    Identifying a maximally stable extremal region (MSER) in an image by skipping comparison of pixels in the region
    27.
    发明授权
    Identifying a maximally stable extremal region (MSER) in an image by skipping comparison of pixels in the region 有权
    通过跳过该区域中的像素的比较来识别图像中最大稳定的极值区域（MSER）

    公开(公告)号：US09014480B2

    公开(公告)日：2015-04-21

    申请号：US13797433

    申请日：2013-03-12

    Applicant: QUALCOMM Incorporated

    Inventor： Pawan Kumar Baheti ,  Kishor K. Barman ,  Raghuraman Krishnamoorthi ,  Bojan Vrcelj

    IPC: G06K9/48 ,  G06K9/46 ,  G06K9/32

    CPC classification number: G06K9/4661 ,  G06K9/3233 ,  G06K9/3258 ,  G06K9/4638 ,  G06K9/4642 ,  G06K2209/01

    Abstract: A difference in intensities of a pair of pixels in an image is repeatedly compared to a threshold, with the pair of pixels being separated by at least one pixel (“skipped pixel”). When the threshold is found to be exceeded, a selected position of a selected pixel in the pair, and at least one additional position adjacent to the selected position are added to a set of positions. The comparing and adding are performed multiple times to generate multiple such sets, each set identifying a region in the image, e.g. an MSER. Sets of positions, identifying regions whose attributes satisfy a test, are merged to obtain a merged set. Intensities of pixels identified in the merged set are used to generate binary values for the region, followed by classification of the region as text/non-text. Regions classified as text are supplied to an optical character recognition (OCR) system.

    Abstract translation: 图像中的一对像素的强度的差异与阈值重复比较，其中该对像素被至少一个像素（“跳过的像素”）分开。 当发现阈值被超过时，将一对所选择的像素的选定位置和与选定位置相邻的至少一个附加位置添加到一组位置。 执行比较和添加多次以产生多个这样的集合，每个集合标识图像中的区域，例如。 一个MSER。 集合的位置，识别属性满足测试的区域被合并以获得合并集。 在合并集中识别的像素的强度用于生成该区域的二进制值，随后将该区域分类为文本/非文本。 分类为文本的区域被提供给光学字符识别（OCR）系统。

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