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REAL-TIME OBJECT DETECTION USING DEPTH SENSORS

机译:使用深度传感器进行实时对象检测

摘要

A depth-based object-detection convolutional neural network is disclosed. The depth-based object-detection convolutional neural network described herein incorporates a base network and additional structure. The base network is configured to receive a depth image formatted as RGB image data as input, and compute output data indicative of at least one feature of an object in the RGB image data. The additional structure is configured to receive the output data of the base network as input, and compute predictions of the location of a region in the received depth image that includes the object and of a class of the object as output. An object detection device incorporating the depth-based object-detection convolutional neural network is operable in real time using an embedded GPU.
机译:公开了一种基于深度的目标检测卷积神经网络。本文所述的基于深度的对象检测卷积神经网络结合了基础网络和附加结构。基础网络被配置为接收被格式化为RGB图像数据的深度图像作为输入,并且计算指示RGB图像数据中的对象的至少一个特征的输出数据。附加结构被配置为接收基本网络的输出数据作为输入,并且计算所接收的深度图像中包括对象的区域的位置的预测以及作为输出的对象的类别。结合了基于深度的对象检测卷积神经网络的对象检测设备可使用嵌入式GPU进行实时操作。

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