关键词: RGB-D图像融合, 卷积神经网络, 张量分解, Tucker分解, 物体识别

Abstract: To make full use of?the depth information for RGB-D image recognition, this paper proposes a new object recognition method based on tensor decomposition. Firstly, it represents the RGB-D image as a fourth-order tensor. Then, it decomposes the fourth-order tensor into a core tensor and four factor matrices. Finally, after projecting the fourth-order tensor by factor matrices, the newly obtained tensor is sent to a convolution neural network for object recognition. Comparative experimental results of three group similar objects on RGB-D dataset show that the proposed method obtains higher recognition accuracy than method that no-tensor fusing. Moreover, the single-object recognition accuracy can be improved by up to 99%.

Key words: RGB-D image fusion, convolutional neural network, tensor decomposition, Tucker decomposition, object recognition