TECHNIQUES FOR PARALLEL EXECUTION OF RANSAC ALGORITHM

    公开(公告)号:US20170140078A1

    公开(公告)日:2017-05-18

    申请号:US15129816

    申请日:2014-03-27

    CPC classification number: G06F17/5009 G06F17/18 G06F17/50 G06F2217/16 G06T7/35

    Abstract: Various embodiments are generally directed to techniques for employing a hybrid of sequential and parallel processing to perform random sample and consensus (RANSAC). A device to perform RANSAC includes a derivation component to derive a first set of proposed models in parallel from a first set of minimal sample sets of a data set; and a comparison component to recalculate a required quantity of proposed models to derive an accurate model if a proposed model of the first set of proposed models better fits the data set than any proposed model derived prior to derivation of the first set of proposed models, and to determine whether to derive a second set of proposed models following derivation of the first set of proposed models based on a comparison of the required quantity to a quantity of previously derived proposed models that includes the first set. Other embodiments are described and claimed.

    OBJECT OF INTEREST BASED IMAGE PROCESSING
    64.
    发明申请
    OBJECT OF INTEREST BASED IMAGE PROCESSING 审中-公开
    基于兴趣的图像处理对象

    公开(公告)号:US20160112674A1

    公开(公告)日:2016-04-21

    申请号:US14972821

    申请日:2015-12-17

    CPC classification number: H04N7/15 H04N19/115 H04N19/167 H04N19/17 H04N19/59

    Abstract: Various embodiments of this disclosure may describe apparatuses, methods, and systems including an encoding engine to encode and/or compress one or more objects of interest within individual image frames with higher bit densities than the bit density employed to encode and/or compress their background. The image processing system may further include a context engine to identify a region of interest including at least a part of the one or more objects of interest, and scale the region of interest within individual image frames to emphasize the objects of interest. Other embodiments may also be disclosed or claimed.

    Abstract translation: 本公开的各种实施例可以描述包括编码引擎的装置,方法和系统,所述编码引擎在具有比用于编码和/或压缩其背景的比特密度更高的比特密度的单个图像帧内编码和/或压缩一个或多个感兴趣对象 。 图像处理系统还可以包括上下文引擎以识别感兴趣区域的至少一部分,并且在各个图像帧内缩放感兴趣区域以强调感兴趣的对象。 其他实施例也可以被公开或要求保护。

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