Fast and accurate multiscale feature fusion stereo matching network

Jiliang Liu; Fuxin Xu; Faliang Deng

doi:10.1117/12.3034844

11 July 2024 Fast and accurate multiscale feature fusion stereo matching network

Jiliang Liu, Fuxin Xu, Faliang Deng

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132100A (2024) https://doi.org/10.1117/12.3034844
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

In this paper, we propose a novel deep learning network model for stereo matching that achieves higher accuracy and better real-time performance. We achieve the effect of streamlining the complexity of the network model by using the lightweight network model MobileNetV3 for feature extraction. By using feature maps at four different scales, combined with the attention feature blocks in the network, the network can combine contextual information with better sensing ability, and the network model achieves a more accurate and efficient processing effect through multiscale feature fusion. We pretrained the model on the SceneFlow virtual datasets and fine-tuned it with multiple epochs of training on the KITTI datasets, which resulted in better generalization of the stereo matching model and more accurate disparity prediction results for real traffic and road environments. Compared with some existing network models such as PSMNet, GANet, our network achieves a faster processing rate with guaranteed accuracy, which meets the real-time requirements of network models under general conditions.

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

Citation Download Citation

Jiliang Liu, Fuxin Xu, and Faliang Deng "Fast and accurate multiscale feature fusion stereo matching network", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132100A (11 July 2024); https://doi.org/10.1117/12.3034844

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KEYWORDS

Data modeling

Education and training

Performance modeling

Cameras

Deep learning

Image processing

Roads

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