基于深度和强度特征的道路场景行人检测

S. Gurmu, Min-Woo Park, Soon Ki Jung
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摘要

本文提出了一种融合强度和深度特征的行人检测方法。这些特征的互补融合显著提高了检测性能。将梯度直方图(Histogram of Oriented gradient, HOG)应用于强度和深度图像的特征提取,并通过线性支持向量机进行训练。我们的方法比传统的基于强度图像的方法有优势,因为深度特征对照明、复杂背景和人体姿势变化具有鲁棒性。实验结果表明,该方法具有较好的检测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pedestrian detection of road scenes using depth and intensity features
In this paper, we present pedestrian detection method using fusion of intensity and depth features. Complementary fusion of these features significantly boosts the detection performance. Histogram of Oriented gradient (HOG) is applied for feature extraction in both intensity and depth images and trained by linear SVM. Our approach has an advantage over the conventional intensity image based methods, since depth features are robust against illumination, complex background and human pose variations. The experimental result shows that our proposed method has better detection performance.
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