Single-image depth estimation based on multi-scale feature fusion

Handong Wang; Lixin He; Chengying Zhou; Jing Yang; Zhi Cheng; Shenjie Cao

doi:10.1117/12.3035313

19 July 2024 Single-image depth estimation based on multi-scale feature fusion

Handong Wang, Lixin He, Chengying Zhou, Jing Yang, Zhi Cheng, Shenjie Cao

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 1321313 (2024) https://doi.org/10.1117/12.3035313
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Begin Single-image depth estimation holds significant application value in the field of computer vision. Traditional methods have certain limitations in accurately locating distant regions in images and predicting the precision of object edges. Therefore, this paper proposes a depth estimation method from a single image using fusion of multi-scale features. Firstly, we construct a feature extraction module that combines Transformer and multi-scale feature fusion mechanisms. This module effectively captures features at different scales and levels in images while focusing on global features, resulting in a more comprehensive and precise feature representation. Secondly, we design a Scene Feature Encoding Module that utilizes dilated convolution blocks and adaptive average pooling to extract context correlations between pixels in images, enabling effective recognition of distant regions. Finally, we design a Strip Spatial Perception Module to refine the perception of depth changes, thereby enhancing overall estimation accuracy. Experimental results showcase the outstanding performance of this approach across diverse scenarios, proving its practicality and wide-ranging application prospects in the field of depth estimation from a single image.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Handong Wang, Lixin He, Chengying Zhou, Jing Yang, Zhi Cheng, and Shenjie Cao "Single-image depth estimation based on multi-scale feature fusion", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 1321313 (19 July 2024); https://doi.org/10.1117/12.3035313

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KEYWORDS

Feature fusion

Convolution

Scanning electron microscopy

Feature extraction

Design

Image fusion

Depth maps

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