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Surveillance system with landmark localization on objects in images using convolutional neural networks

机译:利用卷积神经网络对图像中的对象进行地标定位的监视系统

摘要

A surveillance system and method are provided. The surveillance system includes an image capture device configured to capture an actual image of a target area depicting an object. The surveillance system further includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, synthetic images with intermediate shape corresponding concept labels. The processor is further configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to generate an image pair including a 2D and 3D geometric structure of the object depicted in the actual image. The surveillance system further includes a display device configured to display the image pair.
机译:提供了一种监视系统和方法。监视系统包括图像捕获设备,该图像捕获设备被配置为捕获描绘对象的目标区域的实际图像。监视系统还包括处理器。处理器被配置为基于一组3D计算机辅助设计(CAD)模型渲染具有中间形状对应概念标签的合成图像。处理器还被配置为形成多层卷积神经网络(CNN),该多层卷积神经网络基于渲染的合成图像共同对多个中间形状概念进行建模。处理器还被配置为通过将CNN应用于实际图像以生成包括所描绘对象的2D和3D几何结构的图像对,从而对实际图像执行类内外观变化感知和遮挡感知3D对象解析。在实际图像中。监视系统还包括配置为显示图像对的显示设备。

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