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System and method for toy recognition and detection based on convolutional neural networks

机译:基于卷积神经网络的玩具识别与检测系统及方法

摘要

System and method for automatic computer aided optical recognition of toys, for example, construction toy elements, recognition of those elements on digital images and associating the elements with existing information is presented. The method and system may recognize toy elements of various sizes invariant of toy element distance from the image acquiring device for example camera, invariant of rotation of the toy element, invariant of angle of the camera, invariant of background, invariant of illumination and without the need of predefined region where a toy element should be placed. The system and method may detect more than one toy element on the image and identify them. The system is configured to learn to recognize and detect any number of various toy elements by training a deep convolutional neural network.
机译:提出了一种用于玩具的自动计算机辅助光学识别的系统和方法,例如玩具,建筑玩具元件,数字图像上的那些元件的识别以及将这些元件与现有信息相关联。该方法和系统可以识别各种尺寸的玩具元件,其中玩具元件与图像获取装置的距离例如相机是不变的,玩具元件的旋转是不变的,相机的角度是不变的,背景的种类是不变的,照明的种类是不变的,并且没有需要放置玩具元素的预定义区域。该系统和方法可以检测图像上的一个以上的玩具元件并识别它们。该系统配置为通过训练深度卷积神经网络来学习识别和检测任意数量的各种玩具元素。

著录项

  • 公开/公告号GB201419928D0

    专利类型

  • 公开/公告日2014-12-24

    原文格式PDF

  • 申请/专利权人 VELIC MARKO;

    申请/专利号GB20140019928

  • 发明设计人

    申请日2014-11-10

  • 分类号

  • 国家 GB

  • 入库时间 2022-08-21 14:54:03

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