To address the problems appearing in multi-view three-dimensional (3D) reconstruction, such as the improvement of the accuracy and completeness of the 3D reconstructed images, a two-stage multi-level depth network is proposed. In the stage 1 of the proposed network, several convolutional block attention modules (CBAMs) are applied in the lateral connections of the feature pyramid network (FPN). This is targeted to enhance the spatial and channel relativity of the different hierarchical feature maps so as to bring more semantic information. In the stage 2, the obtained multi-scale feature maps in the stage 1 are tackled by a set of cascaded processing procedures, such as adaptive propagation, single-trees transform, and matching cost computation. As a result, a depth map could be generated and then be further refined in the processing. Comparing with other state-of-the-art methods, the subjective and objective experiments based on the DTU dataset show that our method performs better result in completeness meanwhile maintaining a considerable overall metric. The investigation of applying the proposed method for reconstructing agricultural crop images was carried out, which is based on a set of self-collected images. The experiment shows that a suitable human visual perception for the images could be obtained.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.