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COMPUTER-IMPLEMENTED METHOD FOR 3D LOCALIZATION OF AN OBJECT BASED ON IMAGE DATA AND DEPTH DATA

机译:基于图像数据和深度数据的对象的3D定位的计算机实现的方法

摘要

The invention relates to a computer-implemented method for 3D localization of an object based on image data and depth data indicating distance information for pixels of an image represented by the image data, wherein the method applies a convolutional neural network (1) with a first set (2) of consecutive layers (21), a second set (3) of consecutive layers (31) and a third set (5) of consecutive layers (51), each layer being configured with one or more filters, wherein the convolutional neural network (1) is trained to associate an identification/ classification of an object and corresponding 3D localization data for the identified/classified object to an image data item and a depth data item, comprising the steps of:- Extracting one or more image data features from the image data applying the first set (2) of layers (21) of the convolutional neural network (1);- Extracting one or more depth data features from the depth data applying the second set (3) of layers (31) of the convolutional neural network (1);- Fusing the one or more image data features and the one or more depth data features to obtain at least one fused feature map;- Processing the at least one fused feature map by applying the third set (5) of layers (51) of the convolutional neural network (1) to identify/classify the object and to provide the 3D localization data for the identified/classified object, wherein the 3D localization data includes object reference point data.
机译:本发明涉及一种基于图像数据和深度数据指示由图像数据表示的图像的像素的图像数据和深度数据的对象的3D定位的计算机实现的方法,其中该方法将卷积神经网络(1)与第一连续层(21)的设置(2),连续层(31)的第二组(3)和连续层(51)的第三组(5),每个层配置有一个或多个过滤器,其中卷积的训练神经网络(1),以将对象的标识/分类与识别/分类对象的识别/分类相关联,以包括以下步骤: - 提取一个或多个图像数据的步骤: - 提取一个或多个图像数据来自应用卷积神经网络(1)层(21)的第一组(2)的图像数据的特征; - 从应用层(3)的第二组(3)的深度数据中提取一个或多个深度数据特征卷积Al神经网络(1); - 融合一个或多个图像数据特征和一个或多个深度数据特征,以获得至少一个融合特征图; - 通过应用第三组(5)处理至少一个融合特征映射卷积神经网络(1)的层(51),以识别/分类对象并向识别/分类对象提供3D定位数据,其中3D定位数据包括对象参考点数据。

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