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Bioinspired Approaches to the Selection and Processing of Video Information

机译:BioinSpired途径选择和处理视频信息

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Significant expansion of the range of applications of real-time video systems requires further improvement in their productivity, efficiency and intelligence. Therefore, researchers are increasingly turning to the human eye analyzer as a prototype to create more sophisticated systems of technical vision. The paper proposes a number of approaches and methods for the selection and processing of video information inspired by the human visual analyzer. In particular: the method of hierarchical selective perception of video information; dynamic models of processes for finding objects, tracking them, panning the scene and the mechanisms of attention and allocation of the essence, which, by managing the parameters of reading information from a video sensor, provide reading of a part of the image relevant to the task; information measure of the dynamic image (δ-eutropy), which characterizes its spatial frequencies and is an effective information feature for the search and recognition of objects; methods of expanding the dynamic range of perception of brightness; the principles of circular organization neurons of the central fovea, which provide increased contrast and the allocation of informative features; circular organization of the retinal neurons with a sumation of signal sticks that contribute to increased sensitivity in conditions of insufficient lighting; specialization of neurons and organization multilayer neural network.
机译:实时视频系统应用范围的显着扩展需要进一步提高其生产力,效率和智能。因此,研究人员越来越多地转向人眼分析仪作为原型,以创造更复杂的技术视觉系统。本文提出了许多用于选择和处理受人类视觉分析仪的视频信息的方法和方法。特别是:视频信息的分层选择性感知的方法;寻找对象的动态模型,跟踪它们,淘汰场景和关注机制,通过管理来自视频传感器的读取信息的参数来提供与之相关的图像的一部分的读取任务;动态图像(Δ-eutropy)的信息测量,其表征其空间频率,并且是用于搜索和识别对象的有效信息特征;扩大亮度感知动态范围的方法;中枢神经循环组织神经元的原则,提供了增加的对比度和信息特征的分配;视网膜神经元的圆形组织,信号棒的Sumulation有助于在照明不足条件下提高敏感性;神经元和组织多层神经网络的专业化。

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