Journal of Shandong University(Engineering Science) ›› 2020, Vol. 50 ›› Issue (4): 22-27.doi: 10.6040/j.issn.1672-3961.0.2019.416

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Depth segment classification algorithm based on convolutional neural network

ZHAO Ningning, TANG Xuesong*, ZHAO Mingbo   

  1. College of Information Science and Technology, Donghua University, Shanghai 201620, China
  • Published:2020-08-13

Abstract: In order to solve the problem that redundant pixels in monocular images influenced depth information detection, a depth segment classification algorithm based on the convolutional neural network was proposed. We used NYU-Depth dataset to detect the segment-based features. Afterward, depth information was represented by line segments and its labels by the data preprocessing. The convolutional neural network was designed for considering the characteristics of the segments, and the classification of depth segments in monocular images was realized. By conducting several multi-group comparison experiments on different hyper-parameters, the accuracy of depth segment classification reached 73.50%. This experimental results proved the implement ability of the depth segment classification based on convolutional neural network, which was helpful to deep estimation using geometric features of images.

Key words: monocular image, depth estimation, convolutional network, depth segment, classification algorithm

CLC Number: 

  • TP183
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