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Related Concept Videos

Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
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Uniform Depth Channel Flow01:27

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Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
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Related Experiment Video

Updated: Mar 8, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

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Geometry Guided Multi-Scale Depth Map Fusion via Graph Optimization.

Pengfei Wu, Yiguang Liu, Mao Ye

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |January 17, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces novel depth map fusion methods using geometry consistency and graph optimization to improve accuracy in noisy, discontinuous regions. The new approach significantly enhances depth map completeness and outperforms existing techniques.

    Related Experiment Videos

    Last Updated: Mar 8, 2026

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    16.1K

    Area of Science:

    • Computer Vision
    • 3D Reconstruction

    Background:

    • Depth maps from multiple view stereopsis suffer from noise in discontinuous and untextured areas.
    • Existing depth map fusion methods lack explicit handling of such noise, limiting their effectiveness.

    Purpose of the Study:

    • To develop advanced depth map fusion strategies for improved accuracy in challenging regions.
    • To address limitations of traditional methods by incorporating geometry consistency and multi-scale information.

    Main Methods:

    • A discriminative fusion method based on geometry consistency, evaluating surface geometry stability.
    • A graph optimization approach fusing multi-scale depth maps using graph cuts, considering point sampling scale and inter-point relations.

    Main Results:

    • The proposed geometry consistency method shows superior performance compared to visibility consistency-based methods.
    • The graph optimization method achieves the highest completeness among compared state-of-the-art techniques.
    • Experimental results validate the effectiveness of both proposed fusion strategies.

    Conclusions:

    • The novel fusion methods effectively handle noise in discontinuous and untextured regions.
    • Geometry consistency and multi-scale graph optimization offer significant improvements in depth map fusion.
    • The proposed approach advances the state-of-the-art in 3D reconstruction accuracy and completeness.