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Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

机译:使用生成式稀疏,具有自上而下和横向连接的分层网络的对象检测方法,以结合纹理/颜色检测和形状/轮廓检测

摘要

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.
机译:一种用于检测图像数据集中的对象的方法可以使用具有横向和自顶向下连接的稀疏,生成,分层模型来组合纹理/颜色检测,形状/轮廓检测和/或运动检测。可以使用颜色/纹理检测算法来产生图像数据集中的对象的第一独立表示。可以使用形状/轮廓检测算法来产生图像数据集中的对象的第二独立表示。可以使用运动检测算法来产生图像数据集中的对象的第三独立表示。然后可以使用组合算法将第一,第二和第三独立表示组合为单个相干输出。

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