EXTENDED REALITY VIRTUAL ASSISTANT
    31.
    发明申请

    公开(公告)号:US20190026936A1

    公开(公告)日:2019-01-24

    申请号:US15655762

    申请日:2017-07-20

    Abstract: Methods, devices, and apparatuses are provided to facilitate a positioning of an item of virtual content in an extended reality environment. For example, a first user may access the extended reality environment through a display of a mobile device, and in some examples, the methods may determine positions and orientations of the first user and a second user within the extended reality environment. The methods may also determine a position for placement of the item of virtual content in the extended reality environment based on the determined positions and orientations of the first user and the second user, and perform operations that insert the item of virtual content into the extended reality environment at the determined placement position.

    Unified multi-image fusion approach

    公开(公告)号:US10186023B2

    公开(公告)日:2019-01-22

    申请号:US15006019

    申请日:2016-01-25

    Abstract: Systems and methods are provided for merging multiple images to produce a single fused image having desirable image characteristics derived from the multiple images. For example, the system may determine image characteristics for first and second images. The image characteristics may be related to contrast, exposure, color saturation, and the like. Based on the image characteristics, the system may generate a combined luma weight map. The system may decompose the first and second images and the combined luma weight map. In an example, the first image, the second image, and the combined luma weight map may be represented as scale-space representations having multiple scales or levels. The system may merge the decomposed representations of the first and second images and the combined luma weight map to form a decomposed representation of the fused image. The system may generate the actual fused image from the decomposed representation of the fused image.

    UNIFIED MULTI-IMAGE FUSION APPROACH
    33.
    发明申请

    公开(公告)号:US20170213330A1

    公开(公告)日:2017-07-27

    申请号:US15006019

    申请日:2016-01-25

    CPC classification number: G06T5/50 G06T2207/20221 H04N5/2355

    Abstract: Systems and methods are provided for merging multiple images to produce a single fused image having desirable image characteristics derived from the multiple images. For example, the system may determine image characteristics for first and second images. The image characteristics may be related to contrast, exposure, color saturation, and the like. Based on the image characteristics, the system may generate a combined luma weight map. The system may decompose the first and second images and the combined luma weight map. In an example, the first image, the second image, and the combined luma weight map may be represented as scale-space representations having multiple scales or levels. The system may merge the decomposed representations of the first and second images and the combined luma weight map to form a decomposed representation of the fused image. The system may generate the actual fused image from the decomposed representation of the fused image.

    Method of perspective correction for devanagari text
    34.
    发明授权
    Method of perspective correction for devanagari text 有权
    偏离文本的透视校正方法

    公开(公告)号:US09171204B2

    公开(公告)日:2015-10-27

    申请号:US13842985

    申请日:2013-03-15

    CPC classification number: G06K9/00469 G06K9/3283 G06K2009/363 G06K2209/01

    Abstract: An electronic device and method identify regions that are likely to be text in a natural image or video frame, followed by processing as follows: lines that are nearly vertical are automatically identified in a selected text region, oriented relative to the vertical axis within a predetermined range −max_theta to +max_theta, followed by determination of an angle θ of the identified lines, followed by use of the angle θ to perform perspective correction by warping the selected text region. After perspective correction in this manner, each text region is processed further, to recognize text therein, by performing OCR on each block among a sequence of blocks obtained by slicing the potential text region. Thereafter, the result of text recognition is used to display to the user, either the recognized text or any other information obtained by use of the recognized text.

    Abstract translation: 电子设备和方法识别可能是自然图像或视频帧中的文本的区域,随后如下处理:在所选择的文本区域中自动识别几乎垂直的行,所述文本区域相对于预定的 范围-max_theta到+ max_theta,然后确定角度和角度; 的确定线,然后使用角度和角度; 通过扭曲所选择的文本区域来执行透视校正。 在以这种方式进行透视校正之后,通过对通过切割潜在文本区域获得的块序列中的每个块执行OCR,进一步处理每个文本区域以识别其中的文本。 此后,文本识别的结果用于向用户显示识别的文本或通过使用识别的文本获得的任何其他信息。

    METHOD AND APPARATUS FOR LOW COMPLEXITY COMPRESSION OF SIGNALS EMPLOYING DIFFERENTIAL OPERATION FOR TRANSIENT SEGMENT DETECTION
    35.
    发明申请
    METHOD AND APPARATUS FOR LOW COMPLEXITY COMPRESSION OF SIGNALS EMPLOYING DIFFERENTIAL OPERATION FOR TRANSIENT SEGMENT DETECTION 有权
    用于瞬态分段检测采用差分运算信号的低复杂度压缩的方法和装置

    公开(公告)号:US20150171998A1

    公开(公告)日:2015-06-18

    申请号:US14634117

    申请日:2015-02-27

    CPC classification number: H04L1/0043 H03M7/30 H04L1/0052 H04L1/22

    Abstract: Certain aspects of the present disclosure relate to techniques for low-complexity encoding (compression) of broad class of signals, which are typically not well modeled as sparse signals in either time-domain or frequency-domain. First, the signal can be split in time-segments that may be either sparse in time domain or sparse in frequency domain, for example by using absolute second order differential operator on the input signal. Next, different encoding strategies can be applied for each of these time-segments depending in which domain the sparsity is present.

    Abstract translation: 本公开的某些方面涉及广泛类别的信号的低复杂度编码(压缩)的技术,其通常不能被良好地建模为时域或频域中的稀疏信号。 首先,信号可以在时域中被分割,时间段可能在时域中稀疏或频域稀疏,例如通过在输入信号上使用绝对二阶微分算子。 接下来,不同的编码策略可以应用于这些时间段中的每一个,这取决于稀疏在哪个域中。

    Identifying a maximally stable extremal region (MSER) in an image by skipping comparison of pixels in the region
    36.
    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

    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。

    Method Of Improving Contrast For Text Extraction And Recognition Applications
    37.
    发明申请
    Method Of Improving Contrast For Text Extraction And Recognition Applications 有权
    改进对比文本提取和识别应用的方法

    公开(公告)号:US20150010233A1

    公开(公告)日:2015-01-08

    申请号:US14023306

    申请日:2013-09-10

    CPC classification number: G06K9/36

    Abstract: An electronic device and method receive (for example, from a memory), a grayscale image of a scene of real world captured by a camera of a mobile device. The electronic device and method also receive a color image from which the grayscale image is generated, wherein each color pixel is stored as a tuple of multiple components. The electronic device and method determine a new intensity for at least one grayscale pixel in the grayscale image, based on at least one component of a tuple of a color pixel located in correspondence to the at least one grayscale pixel. The determination may be done conditionally, by checking whether a local variance of intensities is below a predetermined threshold in a subset of grayscale pixels located adjacent to the at least one grayscale pixel, and selecting the component to provide most local variance of intensities.

    Abstract translation: 接收(例如,从存储器)的电子设备和方法,由移动设备的照相机捕获的真实世界场景的灰度图像。 电子设备和方法还接收生成灰度图像的彩色图像,其中每个颜色像素被存储为多个分量的元组。 电子设备和方法基于与至少一个灰度像素相对应的彩色像素的元组的至少一个分量,确定灰度图像中的至少一个灰度像素的新强度。 可以通过在位于与至少一个灰度像素相邻的灰度级像素的子集中检查强度的局部方差是否低于预定阈值,并且选择该组件以提供最大局部的强度方差来有条件地进行确定。

    METHOD AND APPARATUS FOR PROCESSING AND RECONSTRUCTING DATA
    38.
    发明申请
    METHOD AND APPARATUS FOR PROCESSING AND RECONSTRUCTING DATA 有权
    用于处理和重构数据的方法和装置

    公开(公告)号:US20150006598A1

    公开(公告)日:2015-01-01

    申请号:US14487898

    申请日:2014-09-16

    CPC classification number: G06F7/02 G06F2207/02 H03M7/30 H03M7/3059 H03M7/3062

    Abstract: Certain aspects of the present disclosure relate to a method for quantizing signals and reconstructing signals, and/or encoding or decoding data for storage or transmission. Points of a signal may be determined as local extrema or points where an absolute rise of the signal is greater than a threshold. The tread and value of the points may be quantized, and certain of the quantizations may be discarded before the quantizations are transmitted. After being received, the signal may be reconstructed from the quantizations using an iterative process.

    Abstract translation: 本公开的某些方面涉及用于量化信号和重构信号的方法,和/或用于存储或传输的数据的编码或解码的方法。 可以将信号的点确定为局部极值或信号的绝对上升大于阈值的点。 可以对点的胎面和值进行量化,并且在量化被发送之前某些量化可能被丢弃。 在接收之后,可以使用迭代过程从量化重构信号。

    Feature Extraction And Use With A Probability Density Function (PDF) Divergence Metric
    39.
    发明申请
    Feature Extraction And Use With A Probability Density Function (PDF) Divergence Metric 有权
    特征提取和使用概率密度函数(PDF)发散度

    公开(公告)号:US20140023278A1

    公开(公告)日:2014-01-23

    申请号:US13789549

    申请日:2013-03-07

    CPC classification number: G06K9/4671 G06K9/4647 G06K2209/01

    Abstract: An image of real world is processed to identify blocks as candidates to be recognized. Each block is subdivided into sub-blocks, and each sub-block is traversed to obtain counts, in a group for each sub-block. Each count in the group is either of presence of transitions between intensity values of pixels or of absence of transition between intensity values of pixels. Hence, each pixel in a sub-block contributes to at least one of the counts in each group. The counts in a group for a sub-block are normalized, based at least on a total number of pixels in the sub-block. Vector(s) for each sub-block including such normalized counts may be compared with multiple predetermined vectors of corresponding symbols in a set, using any metric of divergence between probability density functions (e.g. Jensen-Shannon divergence metric). Whichever symbol has a predetermined vector that most closely matches the vector(s) is identified and stored.

    Abstract translation: 处理真实世界的图像以识别块作为要被识别的候选。 每个块被细分为子块,并且每个子块被遍历以在每个子块的组中获得计数。 组中的每个计数是存在像素的强度值之间的转换或像素的强度值之间不存在转换。 因此,子块中的每个像素有助于每个组中的至少一个计数。 至少基于子块中的像素总数,子块中的计数被归一化。 可以使用概率密度函数(例如,Jensen-Shannon散度度量)之间的任何度量的度量,将包括这种归一化计数的每个子块的向量与集合中的相应符号的多个预定向量进行比较。 无论哪个符号具有与矢量最接近匹配的预定向量被识别和存储。

    Method Of Handling Complex Variants Of Words Through Prefix-Tree Based Decoding For Devanagiri OCR
    40.
    发明申请
    Method Of Handling Complex Variants Of Words Through Prefix-Tree Based Decoding For Devanagiri OCR 有权
    通过基于前缀树的解码处理复杂变体的方法用于Devanagiri OCR

    公开(公告)号:US20140023274A1

    公开(公告)日:2014-01-23

    申请号:US13828060

    申请日:2013-03-14

    Abstract: An electronic device and method identify a block of text in a portion of an image of real world captured by a camera of a mobile device, slice sub-blocks from the block and identify characters in the sub-blocks that form a first sequence to a predetermined set of sequences to identify a second sequence therein. The second sequence may be identified as recognized (as a modifier-absent word) when not associated with additional information. When the second sequence is associated with additional information, a check is made on pixels in the image, based on a test specified in the additional information. When the test is satisfied, a copy of the second sequence in combination with the modifier is identified as recognized (as a modifier-present word). Storage and use of modifier information in addition to a set of sequences of characters enables recognition of words with or without modifiers.

    Abstract translation: 电子设备和方法识别由移动设备的照相机捕获的真实世界的图像的一部分中的文本块,从块中切片子块,并将形成第一序列的子块中的字符识别为 用于识别其中的第二序列的预定序列集合。 当不与附加信息相关联时,第二序列可以被识别为被识别(作为不包含修饰词的词)。 当第二个序列与附加信息相关联时,将根据附加信息中指定的测试对图像中的像素进行检查。 当测试被满足时,与修饰符组合的第二个序列的拷贝被识别为识别(作为修饰语现在的词)。 修改器信息的存储和使用除了一组字符序列之外,还可以识别具有或不具有修饰符的单词。

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