宁爽,宋辉.帧间方向梯度直方图特征关联的行人检测方法[J].电子测量与仪器学报,2024,38(5):112-118 |
帧间方向梯度直方图特征关联的行人检测方法 |
Pedestrian detection method based on inter-frame directionalgradient histogram feature correlation |
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DOI: |
中文关键词: 方向梯度直方图 支持向量机 行人检测 无人驾驶 帧间关联 |
英文关键词:HOG SVM pedestrian detection autonomous driving inter-frame correlation |
基金项目:国家自然科学基金(618032726)项目资助 |
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中文摘要: |
当前行人检测算法是无人驾驶领域的研究热点,但行人遮挡问题由于样本量相对比较少、遮挡情况多样、可视特征减少等因素,仍未得到很好的解决。针对行人之间相互遮挡或行人被其他物体遮挡导致的漏检问题,给出一种帧间方向梯度直方图特征关联的行人检测方法。首先,在YOLOv7基线网络模型的基础上添加跟踪的方法,以发现漏检行人并估计其位置信息;将含有漏检行人的最新局部图像作为新的信息,利用方向梯度直方图特征,采用支持向量机的方法,在漏检目标估计位置处进行行人检测,以改善由于部分遮挡所导致的漏检问题。实验结果与基线网络相比,该方法的精确度(P)值提高了6.25%,被遮挡行人的平均精度(AP)由26.67%提升到了53.42%。实验表明帧间方向梯度直方图特征关联的行人检测方法可以提高行人检测准确率,计算复杂度低,不明显增加原方法的计算开销,具有一定的应用价值。 |
英文摘要: |
The current pedestrian detection algorithm is a research hotspot in the field of driverless driving, but the pedestrian occlusion problem has not been well solved due to factors such as relatively small sample size, diverse occlusion situations, and reduced visual features. Aiming at the problem of missed detection caused by pedestrians blocking each other or pedestrians being blocked by other objects, a pedestrian detection method based on inter-frame directional gradient histogram feature correlation is proposed. First, a tracking method is added based on the YOLOv7 baseline network model to discover missed pedestrians and estimate their location information; the nearest local image containing missed pedestrians is used as the new information, using directional gradient histogram features and support vectors, a machine-based method is used to detect pedestrians at the estimated position of the missed target to improve the missed detection phenomenon caused by partial occlusion. Experimental results compared with the baseline network, the precision (P) value of this method increased by 6.25%, and the average precision (AP) of occluded pedestrians increased from 26.67% to 53.42%. Experiments show that the pedestrian detection method based on inter-frame directional gradient histogram feature correlation can improve pedestrian detection accuracy, has low computational complexity, does not significantly increase the computational overhead of the original method, and has certain application value. |
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