ADAPTIVE SEARCH WINDOW CONTROL FOR VISUAL SEARCH
    1.
    发明申请
    ADAPTIVE SEARCH WINDOW CONTROL FOR VISUAL SEARCH 有权
    自适应搜索窗口控件进行视觉搜索

    公开(公告)号:US20130279762A1

    公开(公告)日:2013-10-24

    申请号:US13869656

    申请日:2013-04-24

    Abstract: Image-processing apparatus and methods to adaptively control a size and/or location of a visual search window used for feature matching in a machine-vision system are described. A search window controller may receive motion vector data and image recognition rate data, and compute a search window size and/or search window location based on the received data. The computed search window size may be a portion of an image frame. The motion vector data and image recognition rate data may be computed from one or more images in a video image sequence. By adaptively controlling search window size and location, an appreciable reduction in data processing burden for feature matching may be achieved.

    Abstract translation: 描述了在机器视觉系统中自适应地控制用于特征匹配的视觉搜索窗口的尺寸和/或位置的图像处理设备和方法。 搜索窗口控制器可以接收运动矢量数据和图像识别率数据,并且基于接收到的数据来计算搜索窗口大小和/或搜索窗口位置。 所计算的搜索窗口大小可以是图像帧的一部分。 可以从视频图像序列中的一个或多个图像计算运动矢量数据和图像识别率数据。 通过自适应地控制搜索窗口大小和位置,可以实现特征匹配的数据处理负担的明显降低。

    METHOD FOR MANAGING A CONVOLUTIONAL COMPUTATION AND CORRESPONDING DEVICE

    公开(公告)号:US20220107990A1

    公开(公告)日:2022-04-07

    申请号:US17480639

    申请日:2021-09-21

    Abstract: In an embodiment a method for managing a convolutional calculation carried out by a calculation unit adapted to calculate output data on output channels from convolution kernels applied to input data blocks on at least one input channel, wherein calculations on each input data block correspond respectively to an output datum on an output channel, and wherein the calculations with each convolution kernel correspond to the output data on each output channel respectively includes identifying a size of a memory location available in a temporary working memory of the calculation unit, pre-loading in the temporary working memory a maximum number of convolution kernels storable at the size of the memory; and controlling the calculation unit to calculate a set of output data calculable from pre-loaded convolution kernels.

    METHOD FOR MEMORY ALLOCATION DURING EXECUTION OF A NEURAL NETWORK

    公开(公告)号:US20220188610A1

    公开(公告)日:2022-06-16

    申请号:US17455770

    申请日:2021-11-19

    Abstract: According to an aspect, a method is proposed for defining placements, in a volatile memory, of temporary scratch buffers used during an execution of an artificial neural network, the method comprising: determining an execution order of layers of the neural network, defining placements, in a heap memory zone of the volatile memory, of intermediate result buffers generated by each layer, according to the execution order of the layers, determining at least one free area of the heap memory zone over the execution of the layers, defining placements of temporary scratch buffers in the at least one free area of the heap memory zone according to the execution order of the layers.

    ADAPTIVE INTEREST RATE CONTROL FOR VISUAL SEARCH
    4.
    发明申请
    ADAPTIVE INTEREST RATE CONTROL FOR VISUAL SEARCH 有权
    适用于视觉搜索的利率控制

    公开(公告)号:US20130279813A1

    公开(公告)日:2013-10-24

    申请号:US13869652

    申请日:2013-04-24

    Abstract: Image-processing apparatus and methods to adaptively vary an interest point threshold value and control a number of interest points identified in an image frame are described. Sub-regions of an image frame may be processed in a sequence, and an interest point threshold value calculated for each sub-region. The calculated value of the interest point threshold may depend upon pre-selected values and values determined from the processing of one or more prior sub-regions. By using adaptive thresholding, a number of interest points detected for each frame in a sequence of image frames may remain substantially constant, even though objects within the frames may vary appreciably.

    Abstract translation: 描述用于自适应地改变兴趣点阈值并控制在图像帧中识别的兴趣点数量的图像处理装置和方法。 图像帧的子区域可以按顺序处理,并且为每个子区域计算出的兴趣点阈值。 所计算的兴趣点阈值可以取决于从一个或多个先前子区域的处理确定的预先选择的值和值。 通过使用自适应阈值处理,对于图像帧序列中的每个帧检测的多个感兴趣点可以保持基本上恒定,即使帧内的对象可能明显变化。

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