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Related Concept Videos

Body Planes01:06

Body Planes

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Body planes in anatomy are imaginary flat surfaces used as reference points to divide the body into sections for anatomical study. These planes are essential for understanding the orientation, relationships, and spatial organization of anatomical structures.
The sagittal plane is the plane that divides the body or an organ vertically into right and left sides. If this vertical plane runs directly down the middle of the body resulting in equal division, it is called the midsagittal or median...
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Human body segmentation via data-driven graph cut.

Shifeng Li, Huchuan Lu, Xingqing Shao

    IEEE Transactions on Cybernetics
    |October 21, 2014
    PubMed
    Summary

    This study introduces a novel computer vision method for human body segmentation. It combines pose information and visual cues for accurate segmentation of humans in images.

    Area of Science:

    • Computer Vision
    • Image Analysis
    • Machine Learning

    Background:

    • Human body segmentation is crucial in computer vision but challenging.
    • Existing methods often require extensive training and complex shape matching.

    Purpose of the Study:

    • To propose a data-driven method for human body segmentation in static images.
    • To integrate top-down pose information with bottom-up visual cues.

    Main Methods:

    • Utilizes human kinematics and dynamic programming for high-level evidence (body part candidates).
    • Employs body part classifiers for bottom-up low-level visual cues.
    • Integrates both evidence types within a graph cut framework.

    Main Results:

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  • The proposed method effectively segments human bodies in static images.
  • Demonstrates success with arbitrary poses and cluttered backgrounds.
  • Achieved strong qualitative and quantitative experimental results.

    • Conclusions:

    • The integrated approach offers a robust solution for human body segmentation.
    • Outperforms traditional methods by leveraging both kinematic and visual data.
    • Provides a valuable tool for various computer vision applications.