<p class="jove_content">Space Debris Point Cloud Feature Extraction Network (SFENet) combines geometry-guided contour extraction with a multilayer perceptron for space-debris point-cloud feature extraction. The method identifies contour candidates from local point distributions and learns discriminative feature representations for classification. Experiments on SpaceSense-Bench demonstrate effective feature classification and contour extraction under the evaluated simulation conditions.</p>

feature-extraction-from-space-debris-point-clouds-with-geometry

Feature Extraction from Space Debris Point Clouds with Geometry-Guided Contour Extraction and Multilayer Perceptron

Feature extraction of space debris from point cloud data faces challenges such as difficulty in contour extraction, structural complexity, and strong ...

Institution - Xi'an Institute of Optics and Precision Mechanics

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