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Research on pedestrian detection technology based on improved DPM model

机译:基于改进DPM模型的行人检测技术研究

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摘要

Pedestrian detection plays an important role in unmanned technology. Because of the high efficiency and robustness of the deformable part model, it has been widely applied to the field of pedestrian detection. At present, how to effectively reduce the risk of partial screening of pedestrians has been based on the pattern recognition of pedestrian detection technology in the hot spots. Aiming at this problem, after analyzing the deformable part model deeply, this paper creatively proposes a pedestrian detection method with improved deformable part model. By training the two-pedestrian deformable part model, the method is adopted to reduce the pedestrian detection in the pedestrian detection by matching the image sub-region and matching the matching result. It is shown that the method can improve the detection efficiency while ensuring the detection efficiency, while ensuring the effectiveness of the whole algorithm to meet the real-time requirements of unmanned technology.
机译:行人检测在无人驾驶技术中起着重要作用。由于可变形零件模型的高效性和鲁棒性,它已被广泛应用于行人检测领域。目前,如何有效降低行人局部筛查的风险已经基于热点中行人检测技术的模式识别。针对该问题,在对可变形部分模型进行深入分析之后,创造性地提出了一种改进了可变形部分模型的行人检测方法。通过训练两行人可变形部分模型,通过匹配图像子区域和匹配结果,减少行人检测中的行人检测。结果表明,该方法可以在保证检测效率的同时,提高检测效率,同时保证整个算法的有效性,满足无人技术的实时性要求。

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