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    Auxiliary device as augmented reality platform
    1.
    发明授权
    Auxiliary device as augmented reality platform 有权

    公开(公告)号：US10026229B1

    公开(公告)日：2018-07-17

    申请号：US15019257

    申请日：2016-02-09

    Applicant: A9.com, Inc.

    Inventor： Ismet Zeki Yalniz ,  Rahul Bhotika ,  Song Cao ,  Michael Patrick Cutter ,  Colin Jon Taylor ,  Mark Scott Waldo ,  Chun-Kai Wang ,  Daniya Zamalieva

    IPC: G09G5/00 ,  G06T19/00 ,  G06T7/00 ,  G06K9/00

    Abstract: An auxiliary device can be used to display a fiducial that contains information useful in determining the physical size of the fiducial as displayed on the auxiliary device. A primary device can capture image data including a representation of the fiducial. The scale and orientation of the fiducial can be determined, such that a graphical overlay can be generated of an item of interest that corresponds to that scale and orientation. The overlay can then be displayed along with the captured image data, in order to provide an augmented reality experience wherein the image displayed on the primary device represents a scale-appropriate view of the item in a location of interest corresponding to the location of the auxiliary device. As the primary device is moved and the viewpoint of the camera changes, changes in relative scale and orientation to the fiducial are determined and the overlay is updated accordingly.

    Video content alignment
    2.
    发明授权
    Video content alignment 有权

    公开(公告)号：US09984728B2

    公开(公告)日：2018-05-29

    申请号：US14997351

    申请日：2016-01-15

    Applicant: A9.com, Inc.

    Inventor： Ismet Zeki Yalniz ,  Adam Carlson ,  Douglas Ryan Gray ,  Colin Jon Taylor

    IPC: G11B27/30 ,  G11B27/036 ,  G11B27/34 ,  G11B27/031 ,  G11B27/10

    CPC classification number: G11B27/3072 ,  G11B27/031 ,  G11B27/036 ,  G11B27/10 ,  G11B27/3081 ,  G11B27/34

    Abstract: Various embodiments identify differences between frame sequences of a video. For example, to determine a difference between two versions of a video, a fingerprint of each frame of the two versions is generated. From the fingerprints, a run-length encoded representation of each version is generated. The fingerprints which appear only once (i.e., unique fingerprints) in the entire video are identified from each version and compared to identify matching unique fingerprints across versions. The matching unique fingerprints are sorted and filtered to determine split points, which are used to align the two versions of the video. Accordingly, each version is segmented into smaller frame sequences using the split points. Once segmented, the individual frames of each segment are aligned across versions using a dynamic programming algorithm. After aligning the segments at a frame level, the segments are reassembled to generate a global alignment output.

    Image match for featureless objects
    3.
    发明授权
    Image match for featureless objects 有权

    公开(公告)号：US10210423B2

    公开(公告)日：2019-02-19

    申请号：US15166973

    申请日：2016-05-27

    Applicant: A9.com, Inc.

    Inventor： Ismet Zeki Yalniz ,  Colin Jon Taylor ,  Mehmet Nejat Tek ,  Shanghsuan Tsai

    IPC: G06K9/46 ,  G06K9/00 ,  G06T7/60 ,  G06K9/62 ,  G06T7/11 ,  G06T7/90

    Abstract: Object identification through image matching can utilize ratio and other data to accurately identify objects having relatively few feature points otherwise useful for identifying objects. An initial image analysis attempts to locate a “scalar” in the image, such as may include a label, text, icon, or other identifier that can help to narrow a classification of the search, as well as to provide a frame of reference for relative measurements obtained from the image. By comparing the ratios of dimensions of the scalar with other dimensions of the object, it is possible to discriminate between objects containing that scalar in a way that is relatively robust to changes in viewpoint. A ratio signature can be generated for an object for use in matching, while in other embodiments a classification can identify priority ratios that can be used to more accurately identify objects in that classification.

    Video content alignment
    5.
    发明授权
    Video content alignment 有权
    视频内容对齐

    公开(公告)号：US09275682B1

    公开(公告)日：2016-03-01

    申请号：US14498818

    申请日：2014-09-26

    Applicant: A9.com, Inc.

    Inventor： Ismet Zeki Yalniz ,  Adam Carlson ,  Douglas Ryan Gray ,  Colin Jon Taylor

    IPC: G06K9/34 ,  G11B27/30 ,  G11B27/036

    CPC classification number: G11B27/3072 ,  G11B27/031 ,  G11B27/036 ,  G11B27/10 ,  G11B27/3081 ,  G11B27/34

    Abstract: Various embodiments identify differences between frame sequences of a video. For example, to determine a difference between two versions of a video, a fingerprint of each frame of the two versions is generated. From the fingerprints, a run-length encoded representation of each version is generated. The fingerprints which appear only once (i.e., unique fingerprints) in the entire video are identified from each version and compared to identify matching unique fingerprints across versions. The matching unique fingerprints are sorted and filtered to determine split points, which are used to align the two versions of the video. Accordingly, each version is segmented into smaller frame sequences using the split points. Once segmented, the individual frames of each segment are aligned across versions using a dynamic programming algorithm. After aligning the segments at a frame level, the segments are reassembled to generate a global alignment output.

    Abstract translation: 各种实施例识别视频的帧序列之间的差异。 例如，为了确定视频的两个版本之间的差异，生成两个版本的每个帧的指纹。 从指纹中，生成每个版本的游程长度编码表示。 从每个版本识别整个视频中仅出现一次的指纹（即，唯一指纹），并进行比较以识别跨越版本的匹配的唯一指纹。 匹配的唯一指纹被分类和过滤以确定分割点，其用于对准视频的两个版本。 因此，使用分割点将每个版本分割成较小的帧序列。 一旦分段，每个段的各个帧在版本之间使用动态规划算法对齐。 在帧级别对齐段之后，重新组合段以产生全局对准输出。

    Adaptive image sampling for text detection
    8.
    发明授权
    Adaptive image sampling for text detection 有权
    文本检测的自适应图像采样

    公开(公告)号：US09569679B1

    公开(公告)日：2017-02-14

    申请号：US13693542

    申请日：2012-12-04

    Applicant: A9.com, Inc.

    Inventor： Douglas Ryan Gray ,  Arnab Sanat Kumar Dhua ,  Yu Lou ,  Ismet Zeki Yalniz

    IPC: G06K9/34 ,  G06K9/18 ,  H04N1/38 ,  H04N1/387 ,  G06K9/20 ,  G06T7/00 ,  G06K9/00 ,  G06K9/46 ,  G06K9/32

    CPC classification number: G06K9/325 ,  G06K9/00456 ,  G06K9/2054 ,  G06K9/4638 ,  G06K2209/01 ,  H04N1/38 ,  H04N1/387 ,  H04N1/3872 ,  H04N1/40062

    Abstract: Various embodiments enable a device to perform an adaptive sampling method for locating text regions in images of natural scenes. Since only a fraction of pixels in an input image correspond to text regions, it is desirable to eliminate non-text regions early in the text detection process. Therefore, in at least one embodiment, an image is sampled horizontally to identify connected pixel regions indicative of text. In this example, each sampled row of the image is tested for containing Maximally Stable Extremal Regions (MSERs) in order to identify regions containing text. If a respective row contains a connected pixel region indicative of text, the neighboring rows are recursively sampled at finer levels in order to fully contain the text and sampling is terminated for regions which are unlikely to contain text. This sampling process can also be performed for the vertical dimension for regions which are determined to contain text.

    Abstract translation: 各种实施例使得设备能够执行用于在自然场景的图像中定位文本区域的自适应采样方法。 由于输入图像中只有一小部分像素对应于文本区域，因此希望在文本检测过程的早期消除非文本区域。 因此，在至少一个实施例中，水平采样图像以识别指示文本的连接的像素区域。 在该示例中，为了识别包含文本的区域，测试图像的每个采样行以包含最大稳定极值区域（MSER）。 如果相应的行包含指示文本的连接的像素区域，则相邻行以更精细的级别递归采样，以便完全包含文本，并且对于不太可能包含文本的区域的采样被终止。 对于确定为包含文本的区域，也可以针对垂直维度执行此采样过程。

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